Resources/Example_MultiCrossStudy.R
In Wolfffff/RATrak: Time series analysis tools optimized for use with D. Melanogaster phenotype data
###Needs to be cleaned and rewritten with updated commands - Process is retained however, so this file remains ##
##### Example analysis pipeline #####
#Experiment with multiple crosses and tracking data from both parents and F1s (WARNING: quite messy)
# - Calls flies.sleepActivity() for all tracking runs
# - Combines the results from all tracking runs
# - Regress out plate effects
# - Fit linear models to quantify effects of family, treatment, family*treatment, sex, plate etc
load('180529_NN_NCcross180425_offspring.RData')
load('180530_NN_NCcross180425_parents.RData')
load('180529_NN_NCcross180503_offspring.RData')
load('180529_NN_NCcross180503_parents.RData')
load('180531_NN_NCcross180506_offspring.RData')
load('180531_NN_NCcross180506_parents.RData')
#Reprocess the phenotypes with the somewhat updated flies.sleepActivity()
#Eventually, I should probably do some more upstream cleaning of the speed data first
#Cross 1
NN_NC_cross180425_offspring1.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180425_offspring1.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180425_offspring2.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180425_offspring2.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180425_offspring3.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180425_offspring3.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180425_offspring4.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180425_offspring4.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180425_parents.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180425_parents.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
#Cross 2
NN_NC_cross180503_offspring1.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180503_offspring1.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180503_offspring3.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180503_offspring3.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180503_offspring4.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180503_offspring4.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180503_parents.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180503_parents.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
#Cross 3
NN_NC_cross180506_offspring1.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180506_offspring1.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180506_offspring2.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180506_offspring2.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180506_offspring3.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180506_offspring3.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180506_offspring4.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180506_offspring4.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180506_parents.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180506_parents.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
#Merge all the offspring meta data
NN_NC_180531_allOffspring <- rbind(data.frame(well = NN_NC_cross180425_offspring1.data_noEmpt[,1], NN_NC_cross180425_offspring1.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180425_offspring1.data_noEmpt$Plate, '_180425Off1', sep = ''), Family = NN_NC_cross180425_offspring1.data_noEmpt$Family),
data.frame(well = NN_NC_cross180425_offspring2.data_noEmpt[,1], NN_NC_cross180425_offspring2.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180425_offspring2.data_noEmpt$Plate, '_180425Off2', sep = ''), Family = NN_NC_cross180425_offspring2.data_noEmpt$Family),
data.frame(well = NN_NC_cross180425_offspring3.data_noEmpt[,1], NN_NC_cross180425_offspring3.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180425_offspring3.data_noEmpt$Plate, '_180425Off3', sep = ''), Family = NN_NC_cross180425_offspring3.data_noEmpt$Family),
data.frame(well = NN_NC_cross180425_offspring4.data_noEmpt[,1], NN_NC_cross180425_offspring4.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180425_offspring4.data_noEmpt$Plate, '_180425Off4', sep = ''), Family = NN_NC_cross180425_offspring4.data_noEmpt$Family),
data.frame(well = NN_NC_cross180503_offspring1.data_noEmpt[,1], NN_NC_cross180503_offspring1.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180503_offspring1.data_noEmpt$Plate, '_180503Off1', sep = ''), Family = NN_NC_cross180503_offspring1.data_noEmpt$Family),
# NN_NC_cross180503_offspring2.data_noEmpt[,2:4], paste('plate', NN_NC_cross180503_offspring2.data_noEmpt$Plate, '_180503Off2', sep = ''), NN_NC_cross180503_offspring2.data_noEmpt$Family,
data.frame(well = NN_NC_cross180503_offspring3.data_noEmpt[,1], NN_NC_cross180503_offspring3.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180503_offspring3.data_noEmpt$Plate, '_180503Off3', sep = ''), Family = NN_NC_cross180503_offspring3.data_noEmpt$Family),
data.frame(well = NN_NC_cross180503_offspring4.data_noEmpt[,1], NN_NC_cross180503_offspring4.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180503_offspring4.data_noEmpt$Plate, '_180503Off4', sep = ''), Family = NN_NC_cross180503_offspring4.data_noEmpt$Family),
data.frame(well = NN_NC_cross180506_offspring1.data_noEmpt[,1], NN_NC_cross180506_offspring1.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180506_offspring1.data_noEmpt$Plate, '_180506Off1', sep = ''), Family = NN_NC_cross180506_offspring1.data_noEmpt$Family),
data.frame(well = NN_NC_cross180506_offspring2.data_noEmpt[,1], NN_NC_cross180506_offspring2.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180506_offspring2.data_noEmpt$Plate, '_180506Off2', sep = ''), Family = NN_NC_cross180506_offspring2.data_noEmpt$Family),
data.frame(well = NN_NC_cross180506_offspring3.data_noEmpt[,1], NN_NC_cross180506_offspring3.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180506_offspring3.data_noEmpt$Plate, '_180506Off3', sep = ''), Family = NN_NC_cross180506_offspring3.data_noEmpt$Family),
data.frame(well = NN_NC_cross180506_offspring4.data_noEmpt[,1], NN_NC_cross180506_offspring4.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180506_offspring4.data_noEmpt$Plate, '_180506Off4', sep = ''), Family = NN_NC_cross180506_offspring4.data_noEmpt$Family))
#Add empty cols for phenotypes
NN_NC_180531_allOffspring <- cbind(NN_NC_180531_allOffspring, sleepNr = NA, mvNr = NA, avgMvLength = NA, avgSleepLength = NA, avgBoutSpeed = NA, totSleep = NA,
midP_sleep = NA, midP_mv = NA, midP_avgMvLength = NA, midP_avgSleepLength = NA, midP_avgBoutSpeed = NA, midP_totSleep = NA)
#Merge all the parent meta data
parents180425.plate <- NN_NC_cross180425_parents.data_noEmpt$Well_orderAsTracked
parents180425.plate[parents180425.plate < 25] <- 1
parents180425.plate[parents180425.plate > 1 & parents180425.plate < 49] <- 2
parents180425.plate[parents180425.plate > 2 & parents180425.plate < 73] <- 3
parents180425.plate[parents180425.plate > 3] <- 4
NN_NC_180531_allParents <- rbind(data.frame(Well = NN_NC_cross180425_parents.data_noEmpt$Well_orderAsTracked, Family = NN_NC_cross180425_parents.data_noEmpt$family, Empty = NN_NC_cross180425_parents.data_noEmpt$Empty, Male = NN_NC_cross180425_parents.data_noEmpt$Male, plate = paste('plate', parents180425.plate, '_180425', sep = '')),
data.frame(Well = NN_NC_cross180503_parents.data_noEmpt$Well_orderAsTracked, Family = NN_NC_cross180503_parents.data_noEmpt$Family, Empty = NN_NC_cross180503_parents.data_noEmpt$Empty, Male = NN_NC_cross180503_parents.data_noEmpt$Male, plate = paste('plate', NN_NC_cross180503_parents.data_noEmpt$Plate, '_180503', sep = '')),
data.frame(Well = NN_NC_cross180506_parents.data_noEmpt$Well_orderAsTracked, Family = NN_NC_cross180506_parents.data_noEmpt$Family, Empty = NN_NC_cross180506_parents.data_noEmpt$Empty, Male = NN_NC_cross180506_parents.data_noEmpt$Male, plate = paste('plate', NN_NC_cross180506_parents.data_noEmpt$Plate, '_180506', sep = '')))
#Merge meta data for all flies
NN_NC_180531_allFlies <- rbind(data.frame(well = NN_NC_cross180425_parents.data_noEmpt$Well_orderAsTracked, Rotenone = F, Family = NN_NC_cross180425_parents.data_noEmpt$family, Male = NN_NC_cross180425_parents.data_noEmpt$Male, Empty = NN_NC_cross180425_parents.data_noEmpt$Empty, plate = paste('plate', parents180425.plate, '_180425', sep = ''), parent = T),
data.frame(well = NN_NC_cross180503_parents.data_noEmpt$Well_orderAsTracked, Rotenone = F, Family = NN_NC_cross180503_parents.data_noEmpt$Family, Male = NN_NC_cross180503_parents.data_noEmpt$Male, Empty = NN_NC_cross180503_parents.data_noEmpt$Empty, plate = paste('plate', NN_NC_cross180503_parents.data_noEmpt$Plate, '_180503', sep = ''), parent = T),
data.frame(well = NN_NC_cross180506_parents.data_noEmpt$Well_orderAsTracked, Rotenone = F, Family = NN_NC_cross180506_parents.data_noEmpt$Family, Male = NN_NC_cross180506_parents.data_noEmpt$Male, Empty = NN_NC_cross180506_parents.data_noEmpt$Empty, plate = paste('plate', NN_NC_cross180506_parents.data_noEmpt$Plate, '_180506', sep = ''), parent = T),
data.frame(well = NN_NC_cross180425_offspring1.data_noEmpt[,1], NN_NC_cross180425_offspring1.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180425_offspring1.data_noEmpt$Plate, '_180425Off1', sep = ''), Family = NN_NC_cross180425_offspring1.data_noEmpt$Family, parent = F),
data.frame(well = NN_NC_cross180425_offspring2.data_noEmpt[,1], NN_NC_cross180425_offspring2.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180425_offspring2.data_noEmpt$Plate, '_180425Off2', sep = ''), Family = NN_NC_cross180425_offspring2.data_noEmpt$Family, parent = F),
data.frame(well = NN_NC_cross180425_offspring3.data_noEmpt[,1], NN_NC_cross180425_offspring3.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180425_offspring3.data_noEmpt$Plate, '_180425Off3', sep = ''), Family = NN_NC_cross180425_offspring3.data_noEmpt$Family, parent = F),
data.frame(well = NN_NC_cross180425_offspring4.data_noEmpt[,1], NN_NC_cross180425_offspring4.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180425_offspring4.data_noEmpt$Plate, '_180425Off4', sep = ''), Family = NN_NC_cross180425_offspring4.data_noEmpt$Family, parent = F),
data.frame(well = NN_NC_cross180503_offspring1.data_noEmpt[,1], NN_NC_cross180503_offspring1.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180503_offspring1.data_noEmpt$Plate, '_180503Off1', sep = ''), Family = NN_NC_cross180503_offspring1.data_noEmpt$Family, parent = F),
# NN_NC_cross180503_offspring2.data_noEmpt[,2:4], paste('plate', NN_NC_cross180503_offspring2.data_noEmpt$Plate, '_180503Off2', sep = ''), NN_NC_cross180503_offspring2.data_noEmpt$Family,
data.frame(well = NN_NC_cross180503_offspring3.data_noEmpt[,1], NN_NC_cross180503_offspring3.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180503_offspring3.data_noEmpt$Plate, '_180503Off3', sep = ''), Family = NN_NC_cross180503_offspring3.data_noEmpt$Family, parent = F),
data.frame(well = NN_NC_cross180503_offspring4.data_noEmpt[,1], NN_NC_cross180503_offspring4.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180503_offspring4.data_noEmpt$Plate, '_180503Off4', sep = ''), Family = NN_NC_cross180503_offspring4.data_noEmpt$Family, parent = F),
data.frame(well = NN_NC_cross180506_offspring1.data_noEmpt[,1], NN_NC_cross180506_offspring1.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180506_offspring1.data_noEmpt$Plate, '_180506Off1', sep = ''), Family = NN_NC_cross180506_offspring1.data_noEmpt$Family, parent = F),
data.frame(well = NN_NC_cross180506_offspring2.data_noEmpt[,1], NN_NC_cross180506_offspring2.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180506_offspring2.data_noEmpt$Plate, '_180506Off2', sep = ''), Family = NN_NC_cross180506_offspring2.data_noEmpt$Family, parent = F),
data.frame(well = NN_NC_cross180506_offspring3.data_noEmpt[,1], NN_NC_cross180506_offspring3.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180506_offspring3.data_noEmpt$Plate, '_180506Off3', sep = ''), Family = NN_NC_cross180506_offspring3.data_noEmpt$Family, parent = F),
data.frame(well = NN_NC_cross180506_offspring4.data_noEmpt[,1], NN_NC_cross180506_offspring4.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180506_offspring4.data_noEmpt$Plate, '_180506Off4', sep = ''), Family = NN_NC_cross180506_offspring4.data_noEmpt$Family, parent = F)
)
#Add empty cols for phenotypes
NN_NC_180531_allFlies <- cbind(NN_NC_180531_allFlies, sleepNr = NA, mvNr = NA, avgMvLength = NA, avgSleepLength = NA, avgBoutSpeed = NA, totSleep = NA,
midP_sleep = NA, midP_mv = NA, midP_avgMvLength = NA, midP_avgSleepLength = NA, midP_avgBoutSpeed = NA, midP_totSleep = NA)
families <- as.character(levels(NN_NC_180531_allParents$Family))
families <- families[2:length(families)]
for(i in 1:length(families)){
#Indexes in the merged data frames
parIndex <- which(NN_NC_180531_allParents$Family == families[i])
offIndex <- which(NN_NC_180531_allOffspring$Family == families[i])
#Parents
if(length(parIndex) == 2){ #Both parents phenotyped
#Determine which data.frame to get the parental phenotypes from
if(length(grep(pattern = '180425', x = NN_NC_180531_allParents$plate[parIndex])) == 2){
index <- which(NN_NC_cross180425_parents.data_noEmpt$family == families[i]) #The index in the original list
if(length(index) != 2)
warning(paste('Didn\'t find parents for family', families[i]))
dad <- which(NN_NC_cross180425_parents.data_noEmpt$family == families[i] & NN_NC_cross180425_parents.data_noEmpt$Male)
mom <- which(NN_NC_cross180425_parents.data_noEmpt$family == families[i] & !NN_NC_cross180425_parents.data_noEmpt$Male)
dad.pheno <- NN_NC_cross180425_parents.speed_noEmpt_filt06.activity[[dad]]
mom.pheno <- NN_NC_cross180425_parents.speed_noEmpt_filt06.activity[[mom]]
#Put parental phenotypes into NN_NC_180531_allFlies
NN_NC_180531_allFlies.dad <- NN_NC_180531_allFlies$Family == families[i] & NN_NC_180531_allFlies$parent & NN_NC_180531_allFlies$Male
NN_NC_180531_allFlies.mom <- NN_NC_180531_allFlies$Family == families[i] & NN_NC_180531_allFlies$parent & !NN_NC_180531_allFlies$Male
#Dad
NN_NC_180531_allFlies$sleepNr[NN_NC_180531_allFlies.dad] <- dad.pheno$sleepNr
NN_NC_180531_allFlies$mvNr[NN_NC_180531_allFlies.dad] <- dad.pheno$mvNr
NN_NC_180531_allFlies$avgMvLength[NN_NC_180531_allFlies.dad] <- mean(dad.pheno$mvLengths)
NN_NC_180531_allFlies$avgSleepLength[NN_NC_180531_allFlies.dad] <- mean(dad.pheno$sleepLengths)
NN_NC_180531_allFlies$avgBoutSpeed[NN_NC_180531_allFlies.dad] <- mean(dad.pheno$boutSpeeds)
NN_NC_180531_allFlies$totSleep[NN_NC_180531_allFlies.dad] <- sum(dad.pheno$sleepLengths)
#Mom
NN_NC_180531_allFlies$sleepNr[NN_NC_180531_allFlies.mom] <- mom.pheno$sleepNr
NN_NC_180531_allFlies$mvNr[NN_NC_180531_allFlies.mom] <- mom.pheno$mvNr
NN_NC_180531_allFlies$avgMvLength[NN_NC_180531_allFlies.mom] <- mean(mom.pheno$mvLengths)
NN_NC_180531_allFlies$avgSleepLength[NN_NC_180531_allFlies.mom] <- mean(mom.pheno$sleepLengths)
NN_NC_180531_allFlies$avgBoutSpeed[NN_NC_180531_allFlies.mom] <- mean(mom.pheno$boutSpeeds)
NN_NC_180531_allFlies$totSleep[NN_NC_180531_allFlies.mom] <- sum(mom.pheno$sleepLengths)
}
else if(length(grep(pattern = '180503', x = NN_NC_180531_allParents$plate[parIndex])) == 2){
index <- which(NN_NC_cross180503_parents.data_noEmpt$Family == families[i])
if(length(index) != 2)
warning(paste('Didn\'t find parents for family', families[i]))
dad <- which(NN_NC_cross180503_parents.data_noEmpt$Family == families[i] & NN_NC_cross180503_parents.data_noEmpt$Male)
mom <- which(NN_NC_cross180503_parents.data_noEmpt$Family == families[i] & !NN_NC_cross180503_parents.data_noEmpt$Male)
dad.pheno <- NN_NC_cross180503_parents.speed_noEmpt_filt06.activity[[dad]]
mom.pheno <- NN_NC_cross180503_parents.speed_noEmpt_filt06.activity[[mom]]
#Put parental phenotypes into NN_NC_180531_allFlies
NN_NC_180531_allFlies.dad <- NN_NC_180531_allFlies$Family == families[i] & NN_NC_180531_allFlies$parent & NN_NC_180531_allFlies$Male
NN_NC_180531_allFlies.mom <- NN_NC_180531_allFlies$Family == families[i] & NN_NC_180531_allFlies$parent & !NN_NC_180531_allFlies$Male
#Dad
NN_NC_180531_allFlies$sleepNr[NN_NC_180531_allFlies.dad] <- dad.pheno$sleepNr
NN_NC_180531_allFlies$mvNr[NN_NC_180531_allFlies.dad] <- dad.pheno$mvNr
NN_NC_180531_allFlies$avgMvLength[NN_NC_180531_allFlies.dad] <- mean(dad.pheno$mvLengths)
NN_NC_180531_allFlies$avgSleepLength[NN_NC_180531_allFlies.dad] <- mean(dad.pheno$sleepLengths)
NN_NC_180531_allFlies$avgBoutSpeed[NN_NC_180531_allFlies.dad] <- mean(dad.pheno$boutSpeeds)
NN_NC_180531_allFlies$totSleep[NN_NC_180531_allFlies.dad] <- sum(dad.pheno$sleepLengths)
#Mom
NN_NC_180531_allFlies$sleepNr[NN_NC_180531_allFlies.mom] <- mom.pheno$sleepNr
NN_NC_180531_allFlies$mvNr[NN_NC_180531_allFlies.mom] <- mom.pheno$mvNr
NN_NC_180531_allFlies$avgMvLength[NN_NC_180531_allFlies.mom] <- mean(mom.pheno$mvLengths)
NN_NC_180531_allFlies$avgSleepLength[NN_NC_180531_allFlies.mom] <- mean(mom.pheno$sleepLengths)
NN_NC_180531_allFlies$avgBoutSpeed[NN_NC_180531_allFlies.mom] <- mean(mom.pheno$boutSpeeds)
NN_NC_180531_allFlies$totSleep[NN_NC_180531_allFlies.mom] <- sum(mom.pheno$sleepLengths)
}
else if(length(grep(pattern = '180506', x = NN_NC_180531_allParents$plate[parIndex])) == 2){
index <- which(NN_NC_cross180506_parents.data_noEmpt$Family == families[i])
if(length(index) != 2)
warning(paste('Didn\'t find parents for family', families[i]))
dad <- which(NN_NC_cross180506_parents.data_noEmpt$Family == families[i] & NN_NC_cross180506_parents.data_noEmpt$Male)
mom <- which(NN_NC_cross180506_parents.data_noEmpt$Family == families[i] & !NN_NC_cross180506_parents.data_noEmpt$Male)
dad.pheno <- NN_NC_cross180506_parents.speed_noEmpt_filt06.activity[[dad]]
mom.pheno <- NN_NC_cross180506_parents.speed_noEmpt_filt06.activity[[mom]]
#Put parental phenotypes into NN_NC_180531_allFlies
NN_NC_180531_allFlies.dad <- NN_NC_180531_allFlies$Family == families[i] & NN_NC_180531_allFlies$parent & NN_NC_180531_allFlies$Male
NN_NC_180531_allFlies.mom <- NN_NC_180531_allFlies$Family == families[i] & NN_NC_180531_allFlies$parent & !NN_NC_180531_allFlies$Male
#Dad
NN_NC_180531_allFlies$sleepNr[NN_NC_180531_allFlies.dad] <- dad.pheno$sleepNr
NN_NC_180531_allFlies$mvNr[NN_NC_180531_allFlies.dad] <- dad.pheno$mvNr
NN_NC_180531_allFlies$avgMvLength[NN_NC_180531_allFlies.dad] <- mean(dad.pheno$mvLengths)
NN_NC_180531_allFlies$avgSleepLength[NN_NC_180531_allFlies.dad] <- mean(dad.pheno$sleepLengths)
NN_NC_180531_allFlies$avgBoutSpeed[NN_NC_180531_allFlies.dad] <- mean(dad.pheno$boutSpeeds)
NN_NC_180531_allFlies$totSleep[NN_NC_180531_allFlies.dad] <- sum(dad.pheno$sleepLengths)
#Mom
NN_NC_180531_allFlies$sleepNr[NN_NC_180531_allFlies.mom] <- mom.pheno$sleepNr
NN_NC_180531_allFlies$mvNr[NN_NC_180531_allFlies.mom] <- mom.pheno$mvNr
NN_NC_180531_allFlies$avgMvLength[NN_NC_180531_allFlies.mom] <- mean(mom.pheno$mvLengths)
NN_NC_180531_allFlies$avgSleepLength[NN_NC_180531_allFlies.mom] <- mean(mom.pheno$sleepLengths)
NN_NC_180531_allFlies$avgBoutSpeed[NN_NC_180531_allFlies.mom] <- mean(mom.pheno$boutSpeeds)
NN_NC_180531_allFlies$totSleep[NN_NC_180531_allFlies.mom] <- sum(mom.pheno$sleepLengths)
}
#Mid parent values
if(is.list(dad.pheno) & is.list(mom.pheno)){
NN_NC_180531_allOffspring$midP_sleep[offIndex] <- mean(c(dad.pheno$sleepNr, mom.pheno$sleepNr))
NN_NC_180531_allOffspring$midP_mv[offIndex] <- mean(c(dad.pheno$mvNr, mom.pheno$mvNr))
NN_NC_180531_allOffspring$midP_avgMvLength[offIndex] <- mean(c(mean(dad.pheno$mvLengths), mean(mom.pheno$mvLengths)))
NN_NC_180531_allOffspring$midP_avgSleepLength[offIndex] <- mean(c(mean(dad.pheno$sleepLengths), mean(mom.pheno$sleepLengths)))
NN_NC_180531_allOffspring$midP_avgBoutSpeed[offIndex] <- mean(c(mean(dad.pheno$boutSpeeds), mean(mom.pheno$boutSpeeds)))
NN_NC_180531_allOffspring$midP_totSleep[offIndex] <- mean(c(sum(dad.pheno$sleepLengths), sum(mom.pheno$sleepLengths)))
}
dad.pheno <- mom.pheno <- NA
}
else
print(i)
#Offspring
#Retrieve the offspring phenotypes from the right list
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180425Off1', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180425_offspring1.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180425_offspring1.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180425_offspring1.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring1.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring1.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring1.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180425_offspring1.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180425Off2', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180425_offspring2.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180425_offspring2.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180425_offspring2.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring2.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring2.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring2.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180425_offspring2.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180425Off3', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180425_offspring3.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180425_offspring3.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180425_offspring3.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring3.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring3.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring3.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180425_offspring3.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180425Off4', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180425_offspring4.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180425_offspring4.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180425_offspring4.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring4.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring4.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring4.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180425_offspring4.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Cross 2
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180503Off1', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180503_offspring1.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180503_offspring1.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180503_offspring1.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring1.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring1.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring1.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180503_offspring1.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180503Off2', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180503_offspring2.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180503_offspring2.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180503_offspring2.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring2.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring2.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring2.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180503_offspring2.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180503Off3', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180503_offspring3.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180503_offspring3.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180503_offspring3.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring3.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring3.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring3.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180503_offspring3.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180503Off4', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180503_offspring4.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180503_offspring4.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180503_offspring4.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring4.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring4.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring4.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180503_offspring4.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Cross 3
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180506Off1', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180506_offspring1.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180506_offspring1.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180506_offspring1.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring1.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring1.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring1.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180506_offspring1.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180506Off2', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180506_offspring2.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180506_offspring2.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180506_offspring2.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring2.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring2.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring2.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180506_offspring2.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180506Off3', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180506_offspring3.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180506_offspring3.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180506_offspring3.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring3.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring3.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring3.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180506_offspring3.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180506Off4', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180506_offspring4.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180506_offspring4.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180506_offspring4.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring4.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring4.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring4.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180506_offspring4.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
}
#Put the offspring phenotypes into NN_NC_180531_allFlies
offspring <- !NN_NC_180531_allFlies$parent
NN_NC_180531_allFlies[!NN_NC_180531_allFlies$parent, 8:17] <- NN_NC_180531_allOffspring[, 7:16]
#Save
save(list = c('NN_NC_180531_allOffspring', 'NN_NC_180531_allParents', 'NN_NC_180531_allFlies'), file = '180611_TrackingAllFliesSummary.RData')
save(list = c('NN_NC_cross180425_offspring1.speed_noEmpt_filt06', 'NN_NC_cross180425_offspring1.data_noEmpt', 'NN_NC_cross180425_offspring1.speed_noEmpt_filt06.activity',
'NN_NC_cross180425_offspring2.speed_noEmpt_filt06', 'NN_NC_cross180425_offspring2.data_noEmpt', 'NN_NC_cross180425_offspring2.speed_noEmpt_filt06.activity',
'NN_NC_cross180425_offspring3.speed_noEmpt_filt06', 'NN_NC_cross180425_offspring3.data_noEmpt', 'NN_NC_cross180425_offspring3.speed_noEmpt_filt06.activity',
'NN_NC_cross180425_offspring4.speed_noEmpt_filt06', 'NN_NC_cross180425_offspring4.data_noEmpt', 'NN_NC_cross180425_offspring4.speed_noEmpt_filt06.activity',
'NN_NC_cross180425_parents.speed_noEmpt_filt06', 'NN_NC_cross180425_parents.data_noEmpt', 'NN_NC_cross180425_parents.speed_noEmpt_filt06.activity'),
file = '180611_NN_NCcross180425_speed.RData')
save(list = c('NN_NC_cross180503_offspring1.speed_noEmpt_filt06', 'NN_NC_cross180503_offspring1.data_noEmpt', 'NN_NC_cross180503_offspring1.speed_noEmpt_filt06.activity',
'NN_NC_cross180503_offspring3.speed_noEmpt_filt06', 'NN_NC_cross180503_offspring3.data_noEmpt', 'NN_NC_cross180503_offspring3.speed_noEmpt_filt06.activity',
'NN_NC_cross180503_offspring4.speed_noEmpt_filt06', 'NN_NC_cross180503_offspring4.data_noEmpt', 'NN_NC_cross180503_offspring4.speed_noEmpt_filt06.activity',
'NN_NC_cross180503_parents.speed_noEmpt_filt06', 'NN_NC_cross180503_parents.data_noEmpt', 'NN_NC_cross180503_parents.speed_noEmpt_filt06.activity'),
file = '180611_NN_NCcross180503_speed.RData')
save(list = c('NN_NC_cross180506_offspring1.speed_noEmpt_filt06', 'NN_NC_cross180506_offspring1.data_noEmpt', 'NN_NC_cross180506_offspring1.speed_noEmpt_filt06.activity',
'NN_NC_cross180506_offspring2.speed_noEmpt_filt06', 'NN_NC_cross180506_offspring2.data_noEmpt', 'NN_NC_cross180506_offspring2.speed_noEmpt_filt06.activity',
'NN_NC_cross180506_offspring3.speed_noEmpt_filt06', 'NN_NC_cross180506_offspring3.data_noEmpt', 'NN_NC_cross180506_offspring3.speed_noEmpt_filt06.activity',
'NN_NC_cross180506_offspring4.speed_noEmpt_filt06', 'NN_NC_cross180506_offspring4.data_noEmpt', 'NN_NC_cross180506_offspring4.speed_noEmpt_filt06.activity',
'NN_NC_cross180506_parents.speed_noEmpt_filt06', 'NN_NC_cross180506_parents.data_noEmpt', 'NN_NC_cross180506_parents.speed_noEmpt_filt06.activity'),
file = '180611_NN_NCcross180506_speed.RData')
#Fix mid parent
for(i in 1:6){
trait <- colnames(NN_NC_180531_allOffspring)[7:12][i]
y <- NN_NC_180531_allFlies[, trait]
#Mid parent values
for(j in 1:length(families)){
parents <- which(NN_NC_180531_allFlies$parent & NN_NC_180531_allFlies$Family == families[j])
F1s <- which(!NN_NC_180531_allFlies$parent & NN_NC_180531_allFlies$Family == families[j])
if(length(parents) != 2)
warning(paste('Found', length(parents), 'parents , trait:', trait, ', fam:', families[j]))
parents.col <- which(colnames(NN_NC_180531_allFlies) == trait) + 6
NN_NC_180531_allFlies[F1s, parents.col] <- mean(y[parents])
}
}
#Regress plate
NN_NC_180531_allFlies.plateResid <- NN_NC_180531_allFlies
NN_NC_180531_allFlies.plateResid[1:5, 8:19] <- NA
families <- as.character(unique(NN_NC_180531_allOffspring$Family))
for(i in 1:6){
trait <- colnames(NN_NC_180531_allOffspring)[7:12][i]
y <- unlist(NN_NC_180531_allFlies[, trait])
#Regress out plate
y.resid <- resid(lm(y ~ NN_NC_180531_allFlies$plate, na.action=na.exclude))
NN_NC_180531_allFlies.plateResid[, trait] <- y.resid
#Mid parent values
for(j in 1:length(families)){
parents <- which(NN_NC_180531_allFlies$parent & NN_NC_180531_allFlies$Family == families[j])
F1s <- which(!NN_NC_180531_allFlies$parent & NN_NC_180531_allFlies$Family == families[j])
if(length(parents) != 2)
warning(paste('Found', length(parents), 'parents , trait:', trait, ', fam:', families[j]))
parents.col <- which(colnames(NN_NC_180531_allFlies) == trait) + 6
NN_NC_180531_allFlies.plateResid[F1s, parents.col] <- mean(y.resid[parents])
}
}
#Summarize effects
NN_NC_180531_allOffspring.effects <- data.frame(rotenone.p = rep(NA, 6), rotenone.r2 = NA, sex.p = NA, sex.r2 = NA,
plate.p = NA, plate.r2 = NA, family.p = NA, family.r2 = NA,
parentOff_allFlies.p = NA, parentOff_NC.p = NA, parentOff_NN.p = NA,
parentOff_allFlies.r2 = NA, parentOff_NC.r2 = NA, parentOff_NN.r2 = NA,
familyPlusRot.p = NA, familyPlusRot.r2 = NA,
familyTimesRot.p = NA, familyTimesRot.r2 = NA)
rownames(NN_NC_180531_allOffspring.effects) <- colnames(NN_NC_180531_allOffspring)[7:12]
NN_NC_180531_allOffspring.effects_plateResid <- NN_NC_180531_allOffspring.effects
offspring <- NN_NC_180531_allFlies[!NN_NC_180531_allFlies$parent, ]
offspring.resid <- NN_NC_180531_allFlies.plateResid[!NN_NC_180531_allFlies.plateResid$parent, ]
NC <- grep(pattern = 'NC', x = offspring$Family)
NC <- 1:nrow(offspring) %in% NC
NN <- grep(pattern = 'NN', x = offspring$Family)
NN <- 1:nrow(offspring) %in% NN
for(i in 1:6){
trait <- rownames(NN_NC_180531_allOffspring.effects)[i]
midp <- which(colnames(NN_NC_180531_allFlies) == trait) + 6
#Raw speed
y <- offspring[, trait]
model <- lm(y ~ offspring$Rotenone)
NN_NC_180531_allOffspring.effects[trait, "rotenone.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects[trait, "rotenone.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring$Male)
NN_NC_180531_allOffspring.effects[trait, "sex.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects[trait, "sex.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring$plate)
NN_NC_180531_allOffspring.effects[trait, "plate.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects[trait, "plate.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring$Family)
NN_NC_180531_allOffspring.effects[trait, "family.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects[trait, "family.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring[, midp])
NN_NC_180531_allOffspring.effects[trait, "parentOff_allFlies.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects[trait, "parentOff_allFlies.r2"] <- summary(model)$adj.r.squared
model <- lm(y[NC] ~ offspring[NC, midp])
NN_NC_180531_allOffspring.effects[trait, "parentOff_NC.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects[trait, "parentOff_NC.r2"] <- summary(model)$adj.r.squared
model <- lm(y[NN] ~ offspring[NN, midp])
NN_NC_180531_allOffspring.effects[trait, "parentOff_NN.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects[trait, "parentOff_NN.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring$Family + offspring$Rotenone)
NN_NC_180531_allOffspring.effects[trait, "familyPlusRot.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects[trait, "familyPlusRot.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring$Family * offspring$Rotenone)
NN_NC_180531_allOffspring.effects[trait, "familyTimesRot.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects[trait, "familyTimesRot.r2"] <- summary(model)$adj.r.squared
#Residuals
y <- offspring.resid[, trait]
model <- lm(y ~ offspring.resid$Rotenone)
NN_NC_180531_allOffspring.effects_plateResid[trait, "rotenone.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects_plateResid[trait, "rotenone.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring.resid$Male)
NN_NC_180531_allOffspring.effects_plateResid[trait, "sex.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects_plateResid[trait, "sex.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring.resid$plate)
NN_NC_180531_allOffspring.effects_plateResid[trait, "plate.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects_plateResid[trait, "plate.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring.resid$Family)
NN_NC_180531_allOffspring.effects_plateResid[trait, "family.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects_plateResid[trait, "family.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring.resid[, midp])
NN_NC_180531_allOffspring.effects_plateResid[trait, "parentOff_allFlies.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects_plateResid[trait, "parentOff_allFlies.r2"] <- summary(model)$adj.r.squared
model <- lm(y[NC] ~ offspring.resid[NC, midp])
NN_NC_180531_allOffspring.effects_plateResid[trait, "parentOff_NC.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects_plateResid[trait, "parentOff_NC.r2"] <- summary(model)$adj.r.squared
model <- lm(y[NN] ~ offspring.resid[NN, midp])
NN_NC_180531_allOffspring.effects_plateResid[trait, "parentOff_NN.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects_plateResid[trait, "parentOff_NN.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring.resid$Family + offspring.resid$Rotenone)
NN_NC_180531_allOffspring.effects_plateResid[trait, "familyPlusRot.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects_plateResid[trait, "familyPlusRot.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring.resid$Family * offspring.resid$Rotenone)
NN_NC_180531_allOffspring.effects_plateResid[trait, "familyTimesRot.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects_plateResid[trait, "familyTimesRot.r2"] <- summary(model)$adj.r.squared
}
save(list = c('NN_NC_180531_allOffspring.effects', 'NN_NC_180531_allOffspring.effects_plateResid'), file = '180613_phenoEffSummary.RData')
Wolfffff/RATrak documentation built on May 8, 2020, 11:40 p.m.
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###Needs to be cleaned and rewritten with updated commands - Process is retained however, so this file remains ##
##### Example analysis pipeline #####
#Experiment with multiple crosses and tracking data from both parents and F1s (WARNING: quite messy)
# - Calls flies.sleepActivity() for all tracking runs
# - Combines the results from all tracking runs
# - Regress out plate effects
# - Fit linear models to quantify effects of family, treatment, family*treatment, sex, plate etc
load('180529_NN_NCcross180425_offspring.RData')
load('180530_NN_NCcross180425_parents.RData')
load('180529_NN_NCcross180503_offspring.RData')
load('180529_NN_NCcross180503_parents.RData')
load('180531_NN_NCcross180506_offspring.RData')
load('180531_NN_NCcross180506_parents.RData')
#Reprocess the phenotypes with the somewhat updated flies.sleepActivity()
#Eventually, I should probably do some more upstream cleaning of the speed data first
#Cross 1
NN_NC_cross180425_offspring1.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180425_offspring1.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180425_offspring2.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180425_offspring2.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180425_offspring3.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180425_offspring3.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180425_offspring4.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180425_offspring4.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180425_parents.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180425_parents.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
#Cross 2
NN_NC_cross180503_offspring1.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180503_offspring1.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180503_offspring3.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180503_offspring3.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180503_offspring4.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180503_offspring4.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180503_parents.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180503_parents.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
#Cross 3
NN_NC_cross180506_offspring1.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180506_offspring1.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180506_offspring2.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180506_offspring2.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180506_offspring3.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180506_offspring3.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180506_offspring4.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180506_offspring4.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
NN_NC_cross180506_parents.speed_noEmpt_filt06.activity <- flies.sleepActivity(NN_NC_cross180506_parents.speed_noEmpt_filt06, mvThreshold = 2,
deathThreshold = 4*60^2, erroneousSleepDataThreshold = 5, smoothingFactor = 2)
#Merge all the offspring meta data
NN_NC_180531_allOffspring <- rbind(data.frame(well = NN_NC_cross180425_offspring1.data_noEmpt[,1], NN_NC_cross180425_offspring1.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180425_offspring1.data_noEmpt$Plate, '_180425Off1', sep = ''), Family = NN_NC_cross180425_offspring1.data_noEmpt$Family),
data.frame(well = NN_NC_cross180425_offspring2.data_noEmpt[,1], NN_NC_cross180425_offspring2.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180425_offspring2.data_noEmpt$Plate, '_180425Off2', sep = ''), Family = NN_NC_cross180425_offspring2.data_noEmpt$Family),
data.frame(well = NN_NC_cross180425_offspring3.data_noEmpt[,1], NN_NC_cross180425_offspring3.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180425_offspring3.data_noEmpt$Plate, '_180425Off3', sep = ''), Family = NN_NC_cross180425_offspring3.data_noEmpt$Family),
data.frame(well = NN_NC_cross180425_offspring4.data_noEmpt[,1], NN_NC_cross180425_offspring4.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180425_offspring4.data_noEmpt$Plate, '_180425Off4', sep = ''), Family = NN_NC_cross180425_offspring4.data_noEmpt$Family),
data.frame(well = NN_NC_cross180503_offspring1.data_noEmpt[,1], NN_NC_cross180503_offspring1.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180503_offspring1.data_noEmpt$Plate, '_180503Off1', sep = ''), Family = NN_NC_cross180503_offspring1.data_noEmpt$Family),
# NN_NC_cross180503_offspring2.data_noEmpt[,2:4], paste('plate', NN_NC_cross180503_offspring2.data_noEmpt$Plate, '_180503Off2', sep = ''), NN_NC_cross180503_offspring2.data_noEmpt$Family,
data.frame(well = NN_NC_cross180503_offspring3.data_noEmpt[,1], NN_NC_cross180503_offspring3.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180503_offspring3.data_noEmpt$Plate, '_180503Off3', sep = ''), Family = NN_NC_cross180503_offspring3.data_noEmpt$Family),
data.frame(well = NN_NC_cross180503_offspring4.data_noEmpt[,1], NN_NC_cross180503_offspring4.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180503_offspring4.data_noEmpt$Plate, '_180503Off4', sep = ''), Family = NN_NC_cross180503_offspring4.data_noEmpt$Family),
data.frame(well = NN_NC_cross180506_offspring1.data_noEmpt[,1], NN_NC_cross180506_offspring1.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180506_offspring1.data_noEmpt$Plate, '_180506Off1', sep = ''), Family = NN_NC_cross180506_offspring1.data_noEmpt$Family),
data.frame(well = NN_NC_cross180506_offspring2.data_noEmpt[,1], NN_NC_cross180506_offspring2.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180506_offspring2.data_noEmpt$Plate, '_180506Off2', sep = ''), Family = NN_NC_cross180506_offspring2.data_noEmpt$Family),
data.frame(well = NN_NC_cross180506_offspring3.data_noEmpt[,1], NN_NC_cross180506_offspring3.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180506_offspring3.data_noEmpt$Plate, '_180506Off3', sep = ''), Family = NN_NC_cross180506_offspring3.data_noEmpt$Family),
data.frame(well = NN_NC_cross180506_offspring4.data_noEmpt[,1], NN_NC_cross180506_offspring4.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180506_offspring4.data_noEmpt$Plate, '_180506Off4', sep = ''), Family = NN_NC_cross180506_offspring4.data_noEmpt$Family))
#Add empty cols for phenotypes
NN_NC_180531_allOffspring <- cbind(NN_NC_180531_allOffspring, sleepNr = NA, mvNr = NA, avgMvLength = NA, avgSleepLength = NA, avgBoutSpeed = NA, totSleep = NA,
midP_sleep = NA, midP_mv = NA, midP_avgMvLength = NA, midP_avgSleepLength = NA, midP_avgBoutSpeed = NA, midP_totSleep = NA)
#Merge all the parent meta data
parents180425.plate <- NN_NC_cross180425_parents.data_noEmpt$Well_orderAsTracked
parents180425.plate[parents180425.plate < 25] <- 1
parents180425.plate[parents180425.plate > 1 & parents180425.plate < 49] <- 2
parents180425.plate[parents180425.plate > 2 & parents180425.plate < 73] <- 3
parents180425.plate[parents180425.plate > 3] <- 4
NN_NC_180531_allParents <- rbind(data.frame(Well = NN_NC_cross180425_parents.data_noEmpt$Well_orderAsTracked, Family = NN_NC_cross180425_parents.data_noEmpt$family, Empty = NN_NC_cross180425_parents.data_noEmpt$Empty, Male = NN_NC_cross180425_parents.data_noEmpt$Male, plate = paste('plate', parents180425.plate, '_180425', sep = '')),
data.frame(Well = NN_NC_cross180503_parents.data_noEmpt$Well_orderAsTracked, Family = NN_NC_cross180503_parents.data_noEmpt$Family, Empty = NN_NC_cross180503_parents.data_noEmpt$Empty, Male = NN_NC_cross180503_parents.data_noEmpt$Male, plate = paste('plate', NN_NC_cross180503_parents.data_noEmpt$Plate, '_180503', sep = '')),
data.frame(Well = NN_NC_cross180506_parents.data_noEmpt$Well_orderAsTracked, Family = NN_NC_cross180506_parents.data_noEmpt$Family, Empty = NN_NC_cross180506_parents.data_noEmpt$Empty, Male = NN_NC_cross180506_parents.data_noEmpt$Male, plate = paste('plate', NN_NC_cross180506_parents.data_noEmpt$Plate, '_180506', sep = '')))
#Merge meta data for all flies
NN_NC_180531_allFlies <- rbind(data.frame(well = NN_NC_cross180425_parents.data_noEmpt$Well_orderAsTracked, Rotenone = F, Family = NN_NC_cross180425_parents.data_noEmpt$family, Male = NN_NC_cross180425_parents.data_noEmpt$Male, Empty = NN_NC_cross180425_parents.data_noEmpt$Empty, plate = paste('plate', parents180425.plate, '_180425', sep = ''), parent = T),
data.frame(well = NN_NC_cross180503_parents.data_noEmpt$Well_orderAsTracked, Rotenone = F, Family = NN_NC_cross180503_parents.data_noEmpt$Family, Male = NN_NC_cross180503_parents.data_noEmpt$Male, Empty = NN_NC_cross180503_parents.data_noEmpt$Empty, plate = paste('plate', NN_NC_cross180503_parents.data_noEmpt$Plate, '_180503', sep = ''), parent = T),
data.frame(well = NN_NC_cross180506_parents.data_noEmpt$Well_orderAsTracked, Rotenone = F, Family = NN_NC_cross180506_parents.data_noEmpt$Family, Male = NN_NC_cross180506_parents.data_noEmpt$Male, Empty = NN_NC_cross180506_parents.data_noEmpt$Empty, plate = paste('plate', NN_NC_cross180506_parents.data_noEmpt$Plate, '_180506', sep = ''), parent = T),
data.frame(well = NN_NC_cross180425_offspring1.data_noEmpt[,1], NN_NC_cross180425_offspring1.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180425_offspring1.data_noEmpt$Plate, '_180425Off1', sep = ''), Family = NN_NC_cross180425_offspring1.data_noEmpt$Family, parent = F),
data.frame(well = NN_NC_cross180425_offspring2.data_noEmpt[,1], NN_NC_cross180425_offspring2.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180425_offspring2.data_noEmpt$Plate, '_180425Off2', sep = ''), Family = NN_NC_cross180425_offspring2.data_noEmpt$Family, parent = F),
data.frame(well = NN_NC_cross180425_offspring3.data_noEmpt[,1], NN_NC_cross180425_offspring3.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180425_offspring3.data_noEmpt$Plate, '_180425Off3', sep = ''), Family = NN_NC_cross180425_offspring3.data_noEmpt$Family, parent = F),
data.frame(well = NN_NC_cross180425_offspring4.data_noEmpt[,1], NN_NC_cross180425_offspring4.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180425_offspring4.data_noEmpt$Plate, '_180425Off4', sep = ''), Family = NN_NC_cross180425_offspring4.data_noEmpt$Family, parent = F),
data.frame(well = NN_NC_cross180503_offspring1.data_noEmpt[,1], NN_NC_cross180503_offspring1.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180503_offspring1.data_noEmpt$Plate, '_180503Off1', sep = ''), Family = NN_NC_cross180503_offspring1.data_noEmpt$Family, parent = F),
# NN_NC_cross180503_offspring2.data_noEmpt[,2:4], paste('plate', NN_NC_cross180503_offspring2.data_noEmpt$Plate, '_180503Off2', sep = ''), NN_NC_cross180503_offspring2.data_noEmpt$Family,
data.frame(well = NN_NC_cross180503_offspring3.data_noEmpt[,1], NN_NC_cross180503_offspring3.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180503_offspring3.data_noEmpt$Plate, '_180503Off3', sep = ''), Family = NN_NC_cross180503_offspring3.data_noEmpt$Family, parent = F),
data.frame(well = NN_NC_cross180503_offspring4.data_noEmpt[,1], NN_NC_cross180503_offspring4.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180503_offspring4.data_noEmpt$Plate, '_180503Off4', sep = ''), Family = NN_NC_cross180503_offspring4.data_noEmpt$Family, parent = F),
data.frame(well = NN_NC_cross180506_offspring1.data_noEmpt[,1], NN_NC_cross180506_offspring1.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180506_offspring1.data_noEmpt$Plate, '_180506Off1', sep = ''), Family = NN_NC_cross180506_offspring1.data_noEmpt$Family, parent = F),
data.frame(well = NN_NC_cross180506_offspring2.data_noEmpt[,1], NN_NC_cross180506_offspring2.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180506_offspring2.data_noEmpt$Plate, '_180506Off2', sep = ''), Family = NN_NC_cross180506_offspring2.data_noEmpt$Family, parent = F),
data.frame(well = NN_NC_cross180506_offspring3.data_noEmpt[,1], NN_NC_cross180506_offspring3.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180506_offspring3.data_noEmpt$Plate, '_180506Off3', sep = ''), Family = NN_NC_cross180506_offspring3.data_noEmpt$Family, parent = F),
data.frame(well = NN_NC_cross180506_offspring4.data_noEmpt[,1], NN_NC_cross180506_offspring4.data_noEmpt[,2:4], plate = paste('plate', NN_NC_cross180506_offspring4.data_noEmpt$Plate, '_180506Off4', sep = ''), Family = NN_NC_cross180506_offspring4.data_noEmpt$Family, parent = F)
)
#Add empty cols for phenotypes
NN_NC_180531_allFlies <- cbind(NN_NC_180531_allFlies, sleepNr = NA, mvNr = NA, avgMvLength = NA, avgSleepLength = NA, avgBoutSpeed = NA, totSleep = NA,
midP_sleep = NA, midP_mv = NA, midP_avgMvLength = NA, midP_avgSleepLength = NA, midP_avgBoutSpeed = NA, midP_totSleep = NA)
families <- as.character(levels(NN_NC_180531_allParents$Family))
families <- families[2:length(families)]
for(i in 1:length(families)){
#Indexes in the merged data frames
parIndex <- which(NN_NC_180531_allParents$Family == families[i])
offIndex <- which(NN_NC_180531_allOffspring$Family == families[i])
#Parents
if(length(parIndex) == 2){ #Both parents phenotyped
#Determine which data.frame to get the parental phenotypes from
if(length(grep(pattern = '180425', x = NN_NC_180531_allParents$plate[parIndex])) == 2){
index <- which(NN_NC_cross180425_parents.data_noEmpt$family == families[i]) #The index in the original list
if(length(index) != 2)
warning(paste('Didn\'t find parents for family', families[i]))
dad <- which(NN_NC_cross180425_parents.data_noEmpt$family == families[i] & NN_NC_cross180425_parents.data_noEmpt$Male)
mom <- which(NN_NC_cross180425_parents.data_noEmpt$family == families[i] & !NN_NC_cross180425_parents.data_noEmpt$Male)
dad.pheno <- NN_NC_cross180425_parents.speed_noEmpt_filt06.activity[[dad]]
mom.pheno <- NN_NC_cross180425_parents.speed_noEmpt_filt06.activity[[mom]]
#Put parental phenotypes into NN_NC_180531_allFlies
NN_NC_180531_allFlies.dad <- NN_NC_180531_allFlies$Family == families[i] & NN_NC_180531_allFlies$parent & NN_NC_180531_allFlies$Male
NN_NC_180531_allFlies.mom <- NN_NC_180531_allFlies$Family == families[i] & NN_NC_180531_allFlies$parent & !NN_NC_180531_allFlies$Male
#Dad
NN_NC_180531_allFlies$sleepNr[NN_NC_180531_allFlies.dad] <- dad.pheno$sleepNr
NN_NC_180531_allFlies$mvNr[NN_NC_180531_allFlies.dad] <- dad.pheno$mvNr
NN_NC_180531_allFlies$avgMvLength[NN_NC_180531_allFlies.dad] <- mean(dad.pheno$mvLengths)
NN_NC_180531_allFlies$avgSleepLength[NN_NC_180531_allFlies.dad] <- mean(dad.pheno$sleepLengths)
NN_NC_180531_allFlies$avgBoutSpeed[NN_NC_180531_allFlies.dad] <- mean(dad.pheno$boutSpeeds)
NN_NC_180531_allFlies$totSleep[NN_NC_180531_allFlies.dad] <- sum(dad.pheno$sleepLengths)
#Mom
NN_NC_180531_allFlies$sleepNr[NN_NC_180531_allFlies.mom] <- mom.pheno$sleepNr
NN_NC_180531_allFlies$mvNr[NN_NC_180531_allFlies.mom] <- mom.pheno$mvNr
NN_NC_180531_allFlies$avgMvLength[NN_NC_180531_allFlies.mom] <- mean(mom.pheno$mvLengths)
NN_NC_180531_allFlies$avgSleepLength[NN_NC_180531_allFlies.mom] <- mean(mom.pheno$sleepLengths)
NN_NC_180531_allFlies$avgBoutSpeed[NN_NC_180531_allFlies.mom] <- mean(mom.pheno$boutSpeeds)
NN_NC_180531_allFlies$totSleep[NN_NC_180531_allFlies.mom] <- sum(mom.pheno$sleepLengths)
}
else if(length(grep(pattern = '180503', x = NN_NC_180531_allParents$plate[parIndex])) == 2){
index <- which(NN_NC_cross180503_parents.data_noEmpt$Family == families[i])
if(length(index) != 2)
warning(paste('Didn\'t find parents for family', families[i]))
dad <- which(NN_NC_cross180503_parents.data_noEmpt$Family == families[i] & NN_NC_cross180503_parents.data_noEmpt$Male)
mom <- which(NN_NC_cross180503_parents.data_noEmpt$Family == families[i] & !NN_NC_cross180503_parents.data_noEmpt$Male)
dad.pheno <- NN_NC_cross180503_parents.speed_noEmpt_filt06.activity[[dad]]
mom.pheno <- NN_NC_cross180503_parents.speed_noEmpt_filt06.activity[[mom]]
#Put parental phenotypes into NN_NC_180531_allFlies
NN_NC_180531_allFlies.dad <- NN_NC_180531_allFlies$Family == families[i] & NN_NC_180531_allFlies$parent & NN_NC_180531_allFlies$Male
NN_NC_180531_allFlies.mom <- NN_NC_180531_allFlies$Family == families[i] & NN_NC_180531_allFlies$parent & !NN_NC_180531_allFlies$Male
#Dad
NN_NC_180531_allFlies$sleepNr[NN_NC_180531_allFlies.dad] <- dad.pheno$sleepNr
NN_NC_180531_allFlies$mvNr[NN_NC_180531_allFlies.dad] <- dad.pheno$mvNr
NN_NC_180531_allFlies$avgMvLength[NN_NC_180531_allFlies.dad] <- mean(dad.pheno$mvLengths)
NN_NC_180531_allFlies$avgSleepLength[NN_NC_180531_allFlies.dad] <- mean(dad.pheno$sleepLengths)
NN_NC_180531_allFlies$avgBoutSpeed[NN_NC_180531_allFlies.dad] <- mean(dad.pheno$boutSpeeds)
NN_NC_180531_allFlies$totSleep[NN_NC_180531_allFlies.dad] <- sum(dad.pheno$sleepLengths)
#Mom
NN_NC_180531_allFlies$sleepNr[NN_NC_180531_allFlies.mom] <- mom.pheno$sleepNr
NN_NC_180531_allFlies$mvNr[NN_NC_180531_allFlies.mom] <- mom.pheno$mvNr
NN_NC_180531_allFlies$avgMvLength[NN_NC_180531_allFlies.mom] <- mean(mom.pheno$mvLengths)
NN_NC_180531_allFlies$avgSleepLength[NN_NC_180531_allFlies.mom] <- mean(mom.pheno$sleepLengths)
NN_NC_180531_allFlies$avgBoutSpeed[NN_NC_180531_allFlies.mom] <- mean(mom.pheno$boutSpeeds)
NN_NC_180531_allFlies$totSleep[NN_NC_180531_allFlies.mom] <- sum(mom.pheno$sleepLengths)
}
else if(length(grep(pattern = '180506', x = NN_NC_180531_allParents$plate[parIndex])) == 2){
index <- which(NN_NC_cross180506_parents.data_noEmpt$Family == families[i])
if(length(index) != 2)
warning(paste('Didn\'t find parents for family', families[i]))
dad <- which(NN_NC_cross180506_parents.data_noEmpt$Family == families[i] & NN_NC_cross180506_parents.data_noEmpt$Male)
mom <- which(NN_NC_cross180506_parents.data_noEmpt$Family == families[i] & !NN_NC_cross180506_parents.data_noEmpt$Male)
dad.pheno <- NN_NC_cross180506_parents.speed_noEmpt_filt06.activity[[dad]]
mom.pheno <- NN_NC_cross180506_parents.speed_noEmpt_filt06.activity[[mom]]
#Put parental phenotypes into NN_NC_180531_allFlies
NN_NC_180531_allFlies.dad <- NN_NC_180531_allFlies$Family == families[i] & NN_NC_180531_allFlies$parent & NN_NC_180531_allFlies$Male
NN_NC_180531_allFlies.mom <- NN_NC_180531_allFlies$Family == families[i] & NN_NC_180531_allFlies$parent & !NN_NC_180531_allFlies$Male
#Dad
NN_NC_180531_allFlies$sleepNr[NN_NC_180531_allFlies.dad] <- dad.pheno$sleepNr
NN_NC_180531_allFlies$mvNr[NN_NC_180531_allFlies.dad] <- dad.pheno$mvNr
NN_NC_180531_allFlies$avgMvLength[NN_NC_180531_allFlies.dad] <- mean(dad.pheno$mvLengths)
NN_NC_180531_allFlies$avgSleepLength[NN_NC_180531_allFlies.dad] <- mean(dad.pheno$sleepLengths)
NN_NC_180531_allFlies$avgBoutSpeed[NN_NC_180531_allFlies.dad] <- mean(dad.pheno$boutSpeeds)
NN_NC_180531_allFlies$totSleep[NN_NC_180531_allFlies.dad] <- sum(dad.pheno$sleepLengths)
#Mom
NN_NC_180531_allFlies$sleepNr[NN_NC_180531_allFlies.mom] <- mom.pheno$sleepNr
NN_NC_180531_allFlies$mvNr[NN_NC_180531_allFlies.mom] <- mom.pheno$mvNr
NN_NC_180531_allFlies$avgMvLength[NN_NC_180531_allFlies.mom] <- mean(mom.pheno$mvLengths)
NN_NC_180531_allFlies$avgSleepLength[NN_NC_180531_allFlies.mom] <- mean(mom.pheno$sleepLengths)
NN_NC_180531_allFlies$avgBoutSpeed[NN_NC_180531_allFlies.mom] <- mean(mom.pheno$boutSpeeds)
NN_NC_180531_allFlies$totSleep[NN_NC_180531_allFlies.mom] <- sum(mom.pheno$sleepLengths)
}
#Mid parent values
if(is.list(dad.pheno) & is.list(mom.pheno)){
NN_NC_180531_allOffspring$midP_sleep[offIndex] <- mean(c(dad.pheno$sleepNr, mom.pheno$sleepNr))
NN_NC_180531_allOffspring$midP_mv[offIndex] <- mean(c(dad.pheno$mvNr, mom.pheno$mvNr))
NN_NC_180531_allOffspring$midP_avgMvLength[offIndex] <- mean(c(mean(dad.pheno$mvLengths), mean(mom.pheno$mvLengths)))
NN_NC_180531_allOffspring$midP_avgSleepLength[offIndex] <- mean(c(mean(dad.pheno$sleepLengths), mean(mom.pheno$sleepLengths)))
NN_NC_180531_allOffspring$midP_avgBoutSpeed[offIndex] <- mean(c(mean(dad.pheno$boutSpeeds), mean(mom.pheno$boutSpeeds)))
NN_NC_180531_allOffspring$midP_totSleep[offIndex] <- mean(c(sum(dad.pheno$sleepLengths), sum(mom.pheno$sleepLengths)))
}
dad.pheno <- mom.pheno <- NA
}
else
print(i)
#Offspring
#Retrieve the offspring phenotypes from the right list
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180425Off1', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180425_offspring1.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180425_offspring1.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180425_offspring1.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring1.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring1.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring1.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180425_offspring1.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180425Off2', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180425_offspring2.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180425_offspring2.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180425_offspring2.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring2.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring2.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring2.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180425_offspring2.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180425Off3', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180425_offspring3.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180425_offspring3.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180425_offspring3.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring3.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring3.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring3.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180425_offspring3.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180425Off4', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180425_offspring4.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180425_offspring4.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180425_offspring4.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring4.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring4.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180425_offspring4.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180425_offspring4.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Cross 2
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180503Off1', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180503_offspring1.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180503_offspring1.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180503_offspring1.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring1.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring1.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring1.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180503_offspring1.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180503Off2', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180503_offspring2.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180503_offspring2.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180503_offspring2.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring2.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring2.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring2.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180503_offspring2.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180503Off3', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180503_offspring3.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180503_offspring3.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180503_offspring3.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring3.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring3.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring3.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180503_offspring3.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180503Off4', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180503_offspring4.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180503_offspring4.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180503_offspring4.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring4.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring4.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180503_offspring4.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180503_offspring4.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Cross 3
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180506Off1', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180506_offspring1.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180506_offspring1.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180506_offspring1.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring1.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring1.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring1.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180506_offspring1.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180506Off2', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180506_offspring2.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180506_offspring2.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180506_offspring2.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring2.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring2.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring2.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180506_offspring2.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180506Off3', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180506_offspring3.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180506_offspring3.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180506_offspring3.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring3.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring3.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring3.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180506_offspring3.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
#Get the positions of offspring from this tracking run in the merged data.frame
tmp <- grep(pattern = '180506Off4', x = NN_NC_180531_allOffspring$plate)
offspringInRun <- which(1:nrow(NN_NC_180531_allOffspring) %in% tmp & NN_NC_180531_allOffspring$Family == families[i])
if(length(offspringInRun) > 0){
index <- which(NN_NC_cross180506_offspring4.data_noEmpt$Family == families[i]) #Their positions in the original data frames and list
if(length(index) != length(offspringInRun))
warning(paste('Didn\'t find offspring for family', families[i]))
#Put phenotypes into the merged data.frame
NN_NC_180531_allOffspring$sleepNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180506_offspring4.speed_noEmpt_filt06.activity[[x]]$sleepNr})
NN_NC_180531_allOffspring$mvNr[offspringInRun] <- sapply(index, function(x){NN_NC_cross180506_offspring4.speed_noEmpt_filt06.activity[[x]]$mvNr})
NN_NC_180531_allOffspring$avgMvLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring4.speed_noEmpt_filt06.activity[[x]]$mvLengths)})
NN_NC_180531_allOffspring$avgSleepLength[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring4.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
NN_NC_180531_allOffspring$avgBoutSpeed[offspringInRun] <- sapply(index, function(x){mean(NN_NC_cross180506_offspring4.speed_noEmpt_filt06.activity[[x]]$boutSpeeds)})
NN_NC_180531_allOffspring$totSleep[offspringInRun] <- sapply(index, function(x){sum(NN_NC_cross180506_offspring4.speed_noEmpt_filt06.activity[[x]]$sleepLengths)})
}
}
#Put the offspring phenotypes into NN_NC_180531_allFlies
offspring <- !NN_NC_180531_allFlies$parent
NN_NC_180531_allFlies[!NN_NC_180531_allFlies$parent, 8:17] <- NN_NC_180531_allOffspring[, 7:16]
#Save
save(list = c('NN_NC_180531_allOffspring', 'NN_NC_180531_allParents', 'NN_NC_180531_allFlies'), file = '180611_TrackingAllFliesSummary.RData')
save(list = c('NN_NC_cross180425_offspring1.speed_noEmpt_filt06', 'NN_NC_cross180425_offspring1.data_noEmpt', 'NN_NC_cross180425_offspring1.speed_noEmpt_filt06.activity',
'NN_NC_cross180425_offspring2.speed_noEmpt_filt06', 'NN_NC_cross180425_offspring2.data_noEmpt', 'NN_NC_cross180425_offspring2.speed_noEmpt_filt06.activity',
'NN_NC_cross180425_offspring3.speed_noEmpt_filt06', 'NN_NC_cross180425_offspring3.data_noEmpt', 'NN_NC_cross180425_offspring3.speed_noEmpt_filt06.activity',
'NN_NC_cross180425_offspring4.speed_noEmpt_filt06', 'NN_NC_cross180425_offspring4.data_noEmpt', 'NN_NC_cross180425_offspring4.speed_noEmpt_filt06.activity',
'NN_NC_cross180425_parents.speed_noEmpt_filt06', 'NN_NC_cross180425_parents.data_noEmpt', 'NN_NC_cross180425_parents.speed_noEmpt_filt06.activity'),
file = '180611_NN_NCcross180425_speed.RData')
save(list = c('NN_NC_cross180503_offspring1.speed_noEmpt_filt06', 'NN_NC_cross180503_offspring1.data_noEmpt', 'NN_NC_cross180503_offspring1.speed_noEmpt_filt06.activity',
'NN_NC_cross180503_offspring3.speed_noEmpt_filt06', 'NN_NC_cross180503_offspring3.data_noEmpt', 'NN_NC_cross180503_offspring3.speed_noEmpt_filt06.activity',
'NN_NC_cross180503_offspring4.speed_noEmpt_filt06', 'NN_NC_cross180503_offspring4.data_noEmpt', 'NN_NC_cross180503_offspring4.speed_noEmpt_filt06.activity',
'NN_NC_cross180503_parents.speed_noEmpt_filt06', 'NN_NC_cross180503_parents.data_noEmpt', 'NN_NC_cross180503_parents.speed_noEmpt_filt06.activity'),
file = '180611_NN_NCcross180503_speed.RData')
save(list = c('NN_NC_cross180506_offspring1.speed_noEmpt_filt06', 'NN_NC_cross180506_offspring1.data_noEmpt', 'NN_NC_cross180506_offspring1.speed_noEmpt_filt06.activity',
'NN_NC_cross180506_offspring2.speed_noEmpt_filt06', 'NN_NC_cross180506_offspring2.data_noEmpt', 'NN_NC_cross180506_offspring2.speed_noEmpt_filt06.activity',
'NN_NC_cross180506_offspring3.speed_noEmpt_filt06', 'NN_NC_cross180506_offspring3.data_noEmpt', 'NN_NC_cross180506_offspring3.speed_noEmpt_filt06.activity',
'NN_NC_cross180506_offspring4.speed_noEmpt_filt06', 'NN_NC_cross180506_offspring4.data_noEmpt', 'NN_NC_cross180506_offspring4.speed_noEmpt_filt06.activity',
'NN_NC_cross180506_parents.speed_noEmpt_filt06', 'NN_NC_cross180506_parents.data_noEmpt', 'NN_NC_cross180506_parents.speed_noEmpt_filt06.activity'),
file = '180611_NN_NCcross180506_speed.RData')
#Fix mid parent
for(i in 1:6){
trait <- colnames(NN_NC_180531_allOffspring)[7:12][i]
y <- NN_NC_180531_allFlies[, trait]
#Mid parent values
for(j in 1:length(families)){
parents <- which(NN_NC_180531_allFlies$parent & NN_NC_180531_allFlies$Family == families[j])
F1s <- which(!NN_NC_180531_allFlies$parent & NN_NC_180531_allFlies$Family == families[j])
if(length(parents) != 2)
warning(paste('Found', length(parents), 'parents , trait:', trait, ', fam:', families[j]))
parents.col <- which(colnames(NN_NC_180531_allFlies) == trait) + 6
NN_NC_180531_allFlies[F1s, parents.col] <- mean(y[parents])
}
}
#Regress plate
NN_NC_180531_allFlies.plateResid <- NN_NC_180531_allFlies
NN_NC_180531_allFlies.plateResid[1:5, 8:19] <- NA
families <- as.character(unique(NN_NC_180531_allOffspring$Family))
for(i in 1:6){
trait <- colnames(NN_NC_180531_allOffspring)[7:12][i]
y <- unlist(NN_NC_180531_allFlies[, trait])
#Regress out plate
y.resid <- resid(lm(y ~ NN_NC_180531_allFlies$plate, na.action=na.exclude))
NN_NC_180531_allFlies.plateResid[, trait] <- y.resid
#Mid parent values
for(j in 1:length(families)){
parents <- which(NN_NC_180531_allFlies$parent & NN_NC_180531_allFlies$Family == families[j])
F1s <- which(!NN_NC_180531_allFlies$parent & NN_NC_180531_allFlies$Family == families[j])
if(length(parents) != 2)
warning(paste('Found', length(parents), 'parents , trait:', trait, ', fam:', families[j]))
parents.col <- which(colnames(NN_NC_180531_allFlies) == trait) + 6
NN_NC_180531_allFlies.plateResid[F1s, parents.col] <- mean(y.resid[parents])
}
}
#Summarize effects
NN_NC_180531_allOffspring.effects <- data.frame(rotenone.p = rep(NA, 6), rotenone.r2 = NA, sex.p = NA, sex.r2 = NA,
plate.p = NA, plate.r2 = NA, family.p = NA, family.r2 = NA,
parentOff_allFlies.p = NA, parentOff_NC.p = NA, parentOff_NN.p = NA,
parentOff_allFlies.r2 = NA, parentOff_NC.r2 = NA, parentOff_NN.r2 = NA,
familyPlusRot.p = NA, familyPlusRot.r2 = NA,
familyTimesRot.p = NA, familyTimesRot.r2 = NA)
rownames(NN_NC_180531_allOffspring.effects) <- colnames(NN_NC_180531_allOffspring)[7:12]
NN_NC_180531_allOffspring.effects_plateResid <- NN_NC_180531_allOffspring.effects
offspring <- NN_NC_180531_allFlies[!NN_NC_180531_allFlies$parent, ]
offspring.resid <- NN_NC_180531_allFlies.plateResid[!NN_NC_180531_allFlies.plateResid$parent, ]
NC <- grep(pattern = 'NC', x = offspring$Family)
NC <- 1:nrow(offspring) %in% NC
NN <- grep(pattern = 'NN', x = offspring$Family)
NN <- 1:nrow(offspring) %in% NN
for(i in 1:6){
trait <- rownames(NN_NC_180531_allOffspring.effects)[i]
midp <- which(colnames(NN_NC_180531_allFlies) == trait) + 6
#Raw speed
y <- offspring[, trait]
model <- lm(y ~ offspring$Rotenone)
NN_NC_180531_allOffspring.effects[trait, "rotenone.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects[trait, "rotenone.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring$Male)
NN_NC_180531_allOffspring.effects[trait, "sex.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects[trait, "sex.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring$plate)
NN_NC_180531_allOffspring.effects[trait, "plate.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects[trait, "plate.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring$Family)
NN_NC_180531_allOffspring.effects[trait, "family.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects[trait, "family.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring[, midp])
NN_NC_180531_allOffspring.effects[trait, "parentOff_allFlies.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects[trait, "parentOff_allFlies.r2"] <- summary(model)$adj.r.squared
model <- lm(y[NC] ~ offspring[NC, midp])
NN_NC_180531_allOffspring.effects[trait, "parentOff_NC.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects[trait, "parentOff_NC.r2"] <- summary(model)$adj.r.squared
model <- lm(y[NN] ~ offspring[NN, midp])
NN_NC_180531_allOffspring.effects[trait, "parentOff_NN.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects[trait, "parentOff_NN.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring$Family + offspring$Rotenone)
NN_NC_180531_allOffspring.effects[trait, "familyPlusRot.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects[trait, "familyPlusRot.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring$Family * offspring$Rotenone)
NN_NC_180531_allOffspring.effects[trait, "familyTimesRot.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects[trait, "familyTimesRot.r2"] <- summary(model)$adj.r.squared
#Residuals
y <- offspring.resid[, trait]
model <- lm(y ~ offspring.resid$Rotenone)
NN_NC_180531_allOffspring.effects_plateResid[trait, "rotenone.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects_plateResid[trait, "rotenone.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring.resid$Male)
NN_NC_180531_allOffspring.effects_plateResid[trait, "sex.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects_plateResid[trait, "sex.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring.resid$plate)
NN_NC_180531_allOffspring.effects_plateResid[trait, "plate.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects_plateResid[trait, "plate.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring.resid$Family)
NN_NC_180531_allOffspring.effects_plateResid[trait, "family.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects_plateResid[trait, "family.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring.resid[, midp])
NN_NC_180531_allOffspring.effects_plateResid[trait, "parentOff_allFlies.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects_plateResid[trait, "parentOff_allFlies.r2"] <- summary(model)$adj.r.squared
model <- lm(y[NC] ~ offspring.resid[NC, midp])
NN_NC_180531_allOffspring.effects_plateResid[trait, "parentOff_NC.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects_plateResid[trait, "parentOff_NC.r2"] <- summary(model)$adj.r.squared
model <- lm(y[NN] ~ offspring.resid[NN, midp])
NN_NC_180531_allOffspring.effects_plateResid[trait, "parentOff_NN.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects_plateResid[trait, "parentOff_NN.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring.resid$Family + offspring.resid$Rotenone)
NN_NC_180531_allOffspring.effects_plateResid[trait, "familyPlusRot.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects_plateResid[trait, "familyPlusRot.r2"] <- summary(model)$adj.r.squared
model <- lm(y ~ offspring.resid$Family * offspring.resid$Rotenone)
NN_NC_180531_allOffspring.effects_plateResid[trait, "familyTimesRot.p"] <- lmp(model)
NN_NC_180531_allOffspring.effects_plateResid[trait, "familyTimesRot.r2"] <- summary(model)$adj.r.squared
}
save(list = c('NN_NC_180531_allOffspring.effects', 'NN_NC_180531_allOffspring.effects_plateResid'), file = '180613_phenoEffSummary.RData')
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