data-raw/hemibrain/pnts/processAV2.R
In jefferislab/lhns: Skeleton data for neurons associated with the lateral horn of Drosophila melanogaster
#######
# PV5 #
#######
if(!exists("process")){
source("data-raw/hemibrain/startupHemibrain.R")
process = TRUE
}
# First read all LHNs in the related cell body fibres
### Use plot3d(), nlscan() and find.neuron() to choose IDs.
# Groups
x = c( "573346324",
"574710121", "604735525", "578151363",
"484377189", "578841489", "517117602", "452331917", "483038957",
"513357277", "423684795", "485736803", "422644053",
"483354202", "422666053", "517458316")
y = c("699212545", "733005935", "5813012462", "606492411", "5813069285",
"5813040903", "606479285", "360595711", "5812980329", "486073599",
"855043038", "5813039931", "424384254", "485723857", "391276906",
"390586997", "455728985", "5813106089", "667841133", "516762858",
"5813039980", "580546081", "5813013792", "5813013530", "640220321",
"516771668", "576774002", "609168709", "485732870", "547115923",
"948135822", "612285653", "486444499", "674001478", "391945237",
"329206270", "359560118", "360237353", "5812980039", "452327439",
"454377810", "514406435", "636792984", "640915837", "549521047",
"5813013203", "574723544", "5813061564", "577801333", "575042709",
"668152044", "5813057923", "638476210", "5813013183", "638148213",
"883030091", "638826442", "886066221", "575418068", "607109790",
"574352231", "606431658", "542665187", "761239957", "543770627",
"607130326", "574128034", "850636610", "450933288", "450951445",
"450933392", "481989534", "574378565", "5813011770", "419880359",
"511970945", "603007915", "546123239", "638196102", "668552668")
z = c("455033548", "5812980824", "5813047212", "5813048297", "5813087655",
"422971316", "975750913", "454693209", "456082779", "881620582",
"947795335", "518476551", "580547055", "5813015004", "882003599",
"574378463", "759585675", "574382779", "5813041458", "944720631",
"945058110", "1259218128", "944423023", "881995193", "978177557",
"886820993", "947168406", "1039923193", "1101984860", "1538181953",
"1414046770", "1006142645", "944724233", "944729222", "5813048319",
"1260582361", "5813016204", "821612285", "851961337", "730562993",
"852302293", "852302504", "1037510115", "881999404", "819943010",
"825359499", "5813093028", "850972999", "919526332", "850260732",
"944047683", "762961590", "912667199", "1013296065", "819895218",
"919845196", "5813056386", "977123707", "1199181443", "668497214",
"667827599", "421650994", "1130947782")
w = c("574377562")
v = c("5813105722", "696126258","481264051")
av2 = c(x,y,z,w,v)
### Get FAFB assigned hemilineage information
# x.match = unique(hemibrain_lhns[x,"FAFB.match"])
# x.match = x.match[!is.na(x.match)]
# x.match = read.neurons.catmaid.meta(x.match)
# z.match = unique(hemibrain_lhns[z,"FAFB.match"])
# z.match = z.match[!is.na(z.match)]
# z.match = read.neurons.catmaid.meta(z.match)
# y.match = unique(hemibrain_lhns[y,"FAFB.match"])
# y.match = y.match[!is.na(y.match)]
# y.match = read.neurons.catmaid.meta(y.match)
#
# ### Meta info
# mx = neuprint_get_meta(x)
# my = neuprint_get_meta(y)
# mz = neuprint_get_meta(z)
# table(mx$cellBodyFiber)
# table(my$cellBodyFiber)
# table(mz$cellBodyFiber)
# ### CBFs:
# ### ADL22^LBDL3 ADL04^LBDL7 AVL07^LEA1
# ADL22 = neuprint_read_neurons("ADL22")
# ADL22 = ADL22[names(ADL22)%in%hemibrain.lhn.bodyids]
# ADL04 = neuprint_read_neurons("ADL04")
# ADL04 = ADL04[names(ADL04)%in%hemibrain.lhn.bodyids]
# AVL07 = neuprint_read_neurons("AVL07")
# AVL07 = AVL07[names(AVL07)%in%hemibrain.lhn.bodyids]
# av2.hemi = c(ADL22,ADL04,AVL07)
#
# ### Re-define some of these CBFs
# sd = setdiff(av2, names(av2.hemi))
# ds = setdiff(names(av2.hemi),av2)
# av2 = unique(av2, names(av2.hemi))
### Set-up data.frame
df = subset(namelist, bodyid %in% av2)
df$cbf.change = FALSE
df$class = "LHN"
df$cell.type = NA
rownames(df) = df$bodyid
### Hemilineages:
df[x,"ItoLee_Hemilineage"] = "SLPav3"
df[x,"Hartenstein_Hemilineage"] = "BLVa2a"
df[z,"ItoLee_Hemilineage"] = "SLPal1"
df[z,"Hartenstein_Hemilineage"] = "VLPl2_dorsal"
df[y,"ItoLee_Hemilineage"] = "LHa2"
df[y,"Hartenstein_Hemilineage"] = "BLVa1"
df[w,"ItoLee_Hemilineage"] = "primary"
df[w,"Hartenstein_Hemilineage"] = "primary"
df[v,"ItoLee_Hemilineage"] = "LHl3"
df[v,"Hartenstein_Hemilineage"] = "BLD6"
##############################
# Make and review cell types #
##############################
# hemibrain_type_plot(bodyids = a, meta = lh.meta, someneuronlist = db);plot3d(most.lhns.hemibrain[light],col="black")
### Plot your candidate type alongside the equivalent Ito groupings
# hemibrain_milti3d(a1, a2)
### Easily plot several of your candidate types at once
############
### av2x ###
############
#####
# a #
#####
f1 = c("422666053", "483038957","452331917", "423684795", "517458316", "485736803", "517117602", "422644053", "483354202") #light = c("L876#6", "L876#3", "JJ83")
df[f1,"cell.type"] = "AV2f1"
f2 = c("604735525", "573346324", "574710121") # light = c("L876#2", "L876#1","L876#5")
df[f2,"cell.type"] = "AV2f2"
f3 = c("484377189", "578841489","513357277")
df[f3,"cell.type"] = "AV2f3"
f4 = c("578151363")
df[f4,"cell.type"] = "AV2f4"
#####
# h #
#####
# h1 = "674009814" # dead
p1 = "668552668"
df[p1,"cell.type"] = "AV2p1"
############
### AV2y ###
############
#####
# a #
#####
k1 = c("5813012462", "5813040903", "5813069285") # light = "Gad1-F-600244"
df[k1,"cell.type"] = "AV2k1"
k2 = c("549521047", "5813061564", "574723544", "5813013203")
df[k2,"cell.type"] = "AV2k2"
k3 = c("360595711", "5813039980") # light = c("fru-F-200126", "Gad1-F-000298", "Cha-F-800106","L907#1","VGlut-F-500323")
df[k3,"cell.type"] = "AV2k3"
k4 = c("329206270", "360237353", "359560118", "391945237", "5812980039", "452327439", "454377810", "5812980329")
df[k4,"cell.type"] = "AV2k4"
k5 = c("516762858", "485723857", "486073599") #
df[k5,"cell.type"] = "AV2k5"
k6 = "546123239"
df[k6,"cell.type"] = "AV2k6"
k7 = c("391276906", "606479285") # light = c("Gad1-F-000203", "Gad1-F-000006")
df[k7,"cell.type"] = "AV2k7"
k8 = "638196102"
df[k8,"cell.type"] = "AV2k8"
k9 = c("5813039931", "424384254", "855043038")
df[k9,"cell.type"] = "AV2k9"
k10 = c("5813106089", "390586997", "455728985") #light = c("Cak-F-200387")
df[k10,"cell.type"] = "AV2k10"
k11 = c("514406435", "547115923", "640915837") # light = c("Gad1-F-000096", "JJ140")
df[k11,"cell.type"] = "AV2k11"
k12 = c("606492411", "667841133", "699212545") #light = c("Gad1-F-800100","JJ82")
df[k12,"cell.type"] = "AV2k12"
k13 = "636792984"
df[k13,"cell.type"] = "AV2k13"
#####
# d #
#####
a1 = c("883030091", "638826442", "886066221") # light = c("L629#2", "L629#6", "L629#1","L629#5", "L1385#20","L1385#17","L1385#5")
df[a1,"cell.type"] = "AV2a1"
a2 = c("612285653", "486444499", "674001478", "948135822") #light = c("Gak1-F-000240")
df[a2,"cell.type"] = "AV2a2"
a3 = c("5813013530", "640220321", "580546081", "5813013792") # light = c("L629#2", "Gak1-F-800214")
df[a3,"cell.type"] = "AV2a3" # keep
a4 = c("575418068", "638476210", "668152044") # light = c("Gad1-F-600244")
df[a4,"cell.type"] = "AV2a4"
a5 = c("5813057923", "5813013183", "607109790", "638148213") # light = c("L1385#2")
df[a5,"cell.type"] = "AV2a5"
#####
# e #
#####
e3 = c("516771668", "577801333")
df[e3,"cell.type"] = "AV2e3"
e4 = c("485732870", "576774002")
df[e4,"cell.type"] = "AV2e4"
e2 = "609168709"
df[e2,"cell.type"] = "AV2e2"
e1 = c("575042709") # light = c("Gad1-F-600244")
df[e1,"cell.type"] = "AV2e1"
#####
# f #
#####
h1 = c("542665187", "574378565", "606431658", "574352231", "761239957")
df[h1,"cell.type"] = "AV2h1"
#####
# i #
#####
i1 = c("511970945", "603007915","5813011770")
df[i1,"cell.type"] = "AV2i1"
i2 = c("543770627", "574128034", "850636610")
df[i2,"cell.type"] = "AV2i2"
i3 = "607130326"
df[i3,"cell.type"] = "AV2i3"
i4 = c("450933288", "419880359", "450933392")
df[i4,"cell.type"] = "AV2i4"
i5 = c("450951445", "481989534")
df[i5,"cell.type"] = "AV2i5"
#####
# u #
#####
j1 = c("733005935") # light = c("fru-M-400293")
df[j1,"cell.type"] = "AV2j1"
o1 = "421650994"
df[o1,"cell.type"] = "AV2o1"
############
### AV2w ##
############
#####
# c #
#####
c1 = c("454693209", "5813015004", "5812980824", "455033548", "422971316",
"881620582", "456082779", "5813048297", "5813087655", "518476551",
"947795335", "5813047212", "580547055") # light = c("Gad1-F-400156", "Cha-F-400280")
df[c1,"cell.type"] = "AV2c1"
c2 = "975750913"
df[c2,"cell.type"] = "AV2c2"
#####
# g #
#####
g1 = c("574382779", "759585675") # light = c("Cha-F-500135")
df[g1,"cell.type"] = "AV2g1"
g2 = c("1259218128", "978177557", "5813041458", "881995193", "944423023")
df[g2,"cell.type"] = "AV2g2"
g3 = c("574378463", "667827599", "668497214")
df[g3,"cell.type"] = "AV2g3"
g4 = "1199181443"
df[g4,"cell.type"] = "AV2g4"
g5 = c("944720631")
df[g5,"cell.type"] = "AV2g5"
g6 = "945058110"
df[g6,"cell.type"] = "AV2g6"
#####
# b #
#####
b1 = c("944724233", "5813048319", "1006142645", "1414046770") # light = c("Cha-F-300136", "Cha-F-200034")
df[b1,"cell.type"] = "AV2b1" # keep
b2 = c("821612285", "1037510115", "5813016204", "851961337", "852302504")
# light = c("Gad1-F-300218","Gad1-F-200223", "L2087#2", "L2088#3", "L2088#1",
# "L2088#2", "Cha-F-600183", "fru-F-300169", "fru-F-600103", "fru-M-300456",
# "L2087#1", "L2087#3", "L2087#4", "JJ79")
df[b2,"cell.type"] = "AV2b2"
b3 = c("819895218", "730562993", "852302293") # light = c("5HT1A-F-300031","Gad1-F-600005")
df[b3,"cell.type"] = "AV2b3"
b4 = c("1538181953", "1101984860", "886820993", "1039923193", "947168406") # light = c("Gad1-F-700003", "Gad1-F-700003")
df[b4,"cell.type"] = "AV2b4"
b5 = c("5813056386", "1260582361", "977123707") # slight = c("Gad1-F-300310","Cha-F-100444")
df[b5,"cell.type"] = "AV2b5"
b6 = c("819943010", "919526332", "919845196", "825359499", "850972999","5813093028", "1013296065")
df[b6,"cell.type"] = "AV2b6"
b7 = c("944047683", "850260732", "882003599")
df[b7,"cell.type"] = "AV2b7"
b8 = c("944729222")
df[b8,"cell.type"] = "AV2b8"
b9 = c("881999404", "912667199") # light = c("Gad1-F-600189")
df[b9,"cell.type"] = "AV2b9"
b10 = c("825359499", "850972999", "919526332", "919845196") # light = c("Cha-F-700299")
df[b10,"cell.type"] = "AV2b10"
b11 = c("762961590")
df[b11,"cell.type"] = "AV2b11"
#####
# k #
#####
# l1 = "483708083" # dead
l1 = "1130947782"
df[l1,"cell.type"] = "AV2l1"
m1 = c("5813105722", "696126258")
df[m1,"cell.type"] = "AV2m1"
n1 = "481264051"
df[n1,"cell.type"] = "AV2n1"
d1 = "574377562"
df[d1,"cell.type"] = "AV2d1"
#####
# p #
#####
# p1 = c("912390737", "943420940")
# df[p1,"cell.type"] = "AV2p1"
#
# p2 = c("943420877", "1067546905", "1192007205", "1223045702", "1224078043")
# df[p2,"cell.type"] = "AV2p2"
#
# p3 = c("943412282", "1098249445")
# df[p3,"cell.type"] = "AV2p3"
#
# p4 = c("1099255933", "1013757060", "1067884486", "1066516552")
# df[p4,"cell.type"] = "AV2p4"
########
# save #
########
# Organise cell types
df = process_types(df = df, hemibrain_lhns = hemibrain_lhns)
# Summarise results
state_results(df)
# Write .csv
write.csv(df, file = "data-raw/hemibrain/pnts/csv/AV2_celltyping.csv", row.names = FALSE)
# Process
if(process){
# Make 2D Images
take_pictures(df)
# Update googlesheet
write_lhns(df = df, column = c("class", "pnt", "cell.type", "ItoLee_Hemilineage", "Hartenstein_Hemilineage"))
}
jefferislab/lhns documentation built on Aug. 20, 2020, 10:10 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
#######
# PV5 #
#######
if(!exists("process")){
source("data-raw/hemibrain/startupHemibrain.R")
process = TRUE
}
# First read all LHNs in the related cell body fibres
### Use plot3d(), nlscan() and find.neuron() to choose IDs.
# Groups
x = c( "573346324",
"574710121", "604735525", "578151363",
"484377189", "578841489", "517117602", "452331917", "483038957",
"513357277", "423684795", "485736803", "422644053",
"483354202", "422666053", "517458316")
y = c("699212545", "733005935", "5813012462", "606492411", "5813069285",
"5813040903", "606479285", "360595711", "5812980329", "486073599",
"855043038", "5813039931", "424384254", "485723857", "391276906",
"390586997", "455728985", "5813106089", "667841133", "516762858",
"5813039980", "580546081", "5813013792", "5813013530", "640220321",
"516771668", "576774002", "609168709", "485732870", "547115923",
"948135822", "612285653", "486444499", "674001478", "391945237",
"329206270", "359560118", "360237353", "5812980039", "452327439",
"454377810", "514406435", "636792984", "640915837", "549521047",
"5813013203", "574723544", "5813061564", "577801333", "575042709",
"668152044", "5813057923", "638476210", "5813013183", "638148213",
"883030091", "638826442", "886066221", "575418068", "607109790",
"574352231", "606431658", "542665187", "761239957", "543770627",
"607130326", "574128034", "850636610", "450933288", "450951445",
"450933392", "481989534", "574378565", "5813011770", "419880359",
"511970945", "603007915", "546123239", "638196102", "668552668")
z = c("455033548", "5812980824", "5813047212", "5813048297", "5813087655",
"422971316", "975750913", "454693209", "456082779", "881620582",
"947795335", "518476551", "580547055", "5813015004", "882003599",
"574378463", "759585675", "574382779", "5813041458", "944720631",
"945058110", "1259218128", "944423023", "881995193", "978177557",
"886820993", "947168406", "1039923193", "1101984860", "1538181953",
"1414046770", "1006142645", "944724233", "944729222", "5813048319",
"1260582361", "5813016204", "821612285", "851961337", "730562993",
"852302293", "852302504", "1037510115", "881999404", "819943010",
"825359499", "5813093028", "850972999", "919526332", "850260732",
"944047683", "762961590", "912667199", "1013296065", "819895218",
"919845196", "5813056386", "977123707", "1199181443", "668497214",
"667827599", "421650994", "1130947782")
w = c("574377562")
v = c("5813105722", "696126258","481264051")
av2 = c(x,y,z,w,v)
### Get FAFB assigned hemilineage information
# x.match = unique(hemibrain_lhns[x,"FAFB.match"])
# x.match = x.match[!is.na(x.match)]
# x.match = read.neurons.catmaid.meta(x.match)
# z.match = unique(hemibrain_lhns[z,"FAFB.match"])
# z.match = z.match[!is.na(z.match)]
# z.match = read.neurons.catmaid.meta(z.match)
# y.match = unique(hemibrain_lhns[y,"FAFB.match"])
# y.match = y.match[!is.na(y.match)]
# y.match = read.neurons.catmaid.meta(y.match)
#
# ### Meta info
# mx = neuprint_get_meta(x)
# my = neuprint_get_meta(y)
# mz = neuprint_get_meta(z)
# table(mx$cellBodyFiber)
# table(my$cellBodyFiber)
# table(mz$cellBodyFiber)
# ### CBFs:
# ### ADL22^LBDL3 ADL04^LBDL7 AVL07^LEA1
# ADL22 = neuprint_read_neurons("ADL22")
# ADL22 = ADL22[names(ADL22)%in%hemibrain.lhn.bodyids]
# ADL04 = neuprint_read_neurons("ADL04")
# ADL04 = ADL04[names(ADL04)%in%hemibrain.lhn.bodyids]
# AVL07 = neuprint_read_neurons("AVL07")
# AVL07 = AVL07[names(AVL07)%in%hemibrain.lhn.bodyids]
# av2.hemi = c(ADL22,ADL04,AVL07)
#
# ### Re-define some of these CBFs
# sd = setdiff(av2, names(av2.hemi))
# ds = setdiff(names(av2.hemi),av2)
# av2 = unique(av2, names(av2.hemi))
### Set-up data.frame
df = subset(namelist, bodyid %in% av2)
df$cbf.change = FALSE
df$class = "LHN"
df$cell.type = NA
rownames(df) = df$bodyid
### Hemilineages:
df[x,"ItoLee_Hemilineage"] = "SLPav3"
df[x,"Hartenstein_Hemilineage"] = "BLVa2a"
df[z,"ItoLee_Hemilineage"] = "SLPal1"
df[z,"Hartenstein_Hemilineage"] = "VLPl2_dorsal"
df[y,"ItoLee_Hemilineage"] = "LHa2"
df[y,"Hartenstein_Hemilineage"] = "BLVa1"
df[w,"ItoLee_Hemilineage"] = "primary"
df[w,"Hartenstein_Hemilineage"] = "primary"
df[v,"ItoLee_Hemilineage"] = "LHl3"
df[v,"Hartenstein_Hemilineage"] = "BLD6"
##############################
# Make and review cell types #
##############################
# hemibrain_type_plot(bodyids = a, meta = lh.meta, someneuronlist = db);plot3d(most.lhns.hemibrain[light],col="black")
### Plot your candidate type alongside the equivalent Ito groupings
# hemibrain_milti3d(a1, a2)
### Easily plot several of your candidate types at once
############
### av2x ###
############
#####
# a #
#####
f1 = c("422666053", "483038957","452331917", "423684795", "517458316", "485736803", "517117602", "422644053", "483354202") #light = c("L876#6", "L876#3", "JJ83")
df[f1,"cell.type"] = "AV2f1"
f2 = c("604735525", "573346324", "574710121") # light = c("L876#2", "L876#1","L876#5")
df[f2,"cell.type"] = "AV2f2"
f3 = c("484377189", "578841489","513357277")
df[f3,"cell.type"] = "AV2f3"
f4 = c("578151363")
df[f4,"cell.type"] = "AV2f4"
#####
# h #
#####
# h1 = "674009814" # dead
p1 = "668552668"
df[p1,"cell.type"] = "AV2p1"
############
### AV2y ###
############
#####
# a #
#####
k1 = c("5813012462", "5813040903", "5813069285") # light = "Gad1-F-600244"
df[k1,"cell.type"] = "AV2k1"
k2 = c("549521047", "5813061564", "574723544", "5813013203")
df[k2,"cell.type"] = "AV2k2"
k3 = c("360595711", "5813039980") # light = c("fru-F-200126", "Gad1-F-000298", "Cha-F-800106","L907#1","VGlut-F-500323")
df[k3,"cell.type"] = "AV2k3"
k4 = c("329206270", "360237353", "359560118", "391945237", "5812980039", "452327439", "454377810", "5812980329")
df[k4,"cell.type"] = "AV2k4"
k5 = c("516762858", "485723857", "486073599") #
df[k5,"cell.type"] = "AV2k5"
k6 = "546123239"
df[k6,"cell.type"] = "AV2k6"
k7 = c("391276906", "606479285") # light = c("Gad1-F-000203", "Gad1-F-000006")
df[k7,"cell.type"] = "AV2k7"
k8 = "638196102"
df[k8,"cell.type"] = "AV2k8"
k9 = c("5813039931", "424384254", "855043038")
df[k9,"cell.type"] = "AV2k9"
k10 = c("5813106089", "390586997", "455728985") #light = c("Cak-F-200387")
df[k10,"cell.type"] = "AV2k10"
k11 = c("514406435", "547115923", "640915837") # light = c("Gad1-F-000096", "JJ140")
df[k11,"cell.type"] = "AV2k11"
k12 = c("606492411", "667841133", "699212545") #light = c("Gad1-F-800100","JJ82")
df[k12,"cell.type"] = "AV2k12"
k13 = "636792984"
df[k13,"cell.type"] = "AV2k13"
#####
# d #
#####
a1 = c("883030091", "638826442", "886066221") # light = c("L629#2", "L629#6", "L629#1","L629#5", "L1385#20","L1385#17","L1385#5")
df[a1,"cell.type"] = "AV2a1"
a2 = c("612285653", "486444499", "674001478", "948135822") #light = c("Gak1-F-000240")
df[a2,"cell.type"] = "AV2a2"
a3 = c("5813013530", "640220321", "580546081", "5813013792") # light = c("L629#2", "Gak1-F-800214")
df[a3,"cell.type"] = "AV2a3" # keep
a4 = c("575418068", "638476210", "668152044") # light = c("Gad1-F-600244")
df[a4,"cell.type"] = "AV2a4"
a5 = c("5813057923", "5813013183", "607109790", "638148213") # light = c("L1385#2")
df[a5,"cell.type"] = "AV2a5"
#####
# e #
#####
e3 = c("516771668", "577801333")
df[e3,"cell.type"] = "AV2e3"
e4 = c("485732870", "576774002")
df[e4,"cell.type"] = "AV2e4"
e2 = "609168709"
df[e2,"cell.type"] = "AV2e2"
e1 = c("575042709") # light = c("Gad1-F-600244")
df[e1,"cell.type"] = "AV2e1"
#####
# f #
#####
h1 = c("542665187", "574378565", "606431658", "574352231", "761239957")
df[h1,"cell.type"] = "AV2h1"
#####
# i #
#####
i1 = c("511970945", "603007915","5813011770")
df[i1,"cell.type"] = "AV2i1"
i2 = c("543770627", "574128034", "850636610")
df[i2,"cell.type"] = "AV2i2"
i3 = "607130326"
df[i3,"cell.type"] = "AV2i3"
i4 = c("450933288", "419880359", "450933392")
df[i4,"cell.type"] = "AV2i4"
i5 = c("450951445", "481989534")
df[i5,"cell.type"] = "AV2i5"
#####
# u #
#####
j1 = c("733005935") # light = c("fru-M-400293")
df[j1,"cell.type"] = "AV2j1"
o1 = "421650994"
df[o1,"cell.type"] = "AV2o1"
############
### AV2w ##
############
#####
# c #
#####
c1 = c("454693209", "5813015004", "5812980824", "455033548", "422971316",
"881620582", "456082779", "5813048297", "5813087655", "518476551",
"947795335", "5813047212", "580547055") # light = c("Gad1-F-400156", "Cha-F-400280")
df[c1,"cell.type"] = "AV2c1"
c2 = "975750913"
df[c2,"cell.type"] = "AV2c2"
#####
# g #
#####
g1 = c("574382779", "759585675") # light = c("Cha-F-500135")
df[g1,"cell.type"] = "AV2g1"
g2 = c("1259218128", "978177557", "5813041458", "881995193", "944423023")
df[g2,"cell.type"] = "AV2g2"
g3 = c("574378463", "667827599", "668497214")
df[g3,"cell.type"] = "AV2g3"
g4 = "1199181443"
df[g4,"cell.type"] = "AV2g4"
g5 = c("944720631")
df[g5,"cell.type"] = "AV2g5"
g6 = "945058110"
df[g6,"cell.type"] = "AV2g6"
#####
# b #
#####
b1 = c("944724233", "5813048319", "1006142645", "1414046770") # light = c("Cha-F-300136", "Cha-F-200034")
df[b1,"cell.type"] = "AV2b1" # keep
b2 = c("821612285", "1037510115", "5813016204", "851961337", "852302504")
# light = c("Gad1-F-300218","Gad1-F-200223", "L2087#2", "L2088#3", "L2088#1",
# "L2088#2", "Cha-F-600183", "fru-F-300169", "fru-F-600103", "fru-M-300456",
# "L2087#1", "L2087#3", "L2087#4", "JJ79")
df[b2,"cell.type"] = "AV2b2"
b3 = c("819895218", "730562993", "852302293") # light = c("5HT1A-F-300031","Gad1-F-600005")
df[b3,"cell.type"] = "AV2b3"
b4 = c("1538181953", "1101984860", "886820993", "1039923193", "947168406") # light = c("Gad1-F-700003", "Gad1-F-700003")
df[b4,"cell.type"] = "AV2b4"
b5 = c("5813056386", "1260582361", "977123707") # slight = c("Gad1-F-300310","Cha-F-100444")
df[b5,"cell.type"] = "AV2b5"
b6 = c("819943010", "919526332", "919845196", "825359499", "850972999","5813093028", "1013296065")
df[b6,"cell.type"] = "AV2b6"
b7 = c("944047683", "850260732", "882003599")
df[b7,"cell.type"] = "AV2b7"
b8 = c("944729222")
df[b8,"cell.type"] = "AV2b8"
b9 = c("881999404", "912667199") # light = c("Gad1-F-600189")
df[b9,"cell.type"] = "AV2b9"
b10 = c("825359499", "850972999", "919526332", "919845196") # light = c("Cha-F-700299")
df[b10,"cell.type"] = "AV2b10"
b11 = c("762961590")
df[b11,"cell.type"] = "AV2b11"
#####
# k #
#####
# l1 = "483708083" # dead
l1 = "1130947782"
df[l1,"cell.type"] = "AV2l1"
m1 = c("5813105722", "696126258")
df[m1,"cell.type"] = "AV2m1"
n1 = "481264051"
df[n1,"cell.type"] = "AV2n1"
d1 = "574377562"
df[d1,"cell.type"] = "AV2d1"
#####
# p #
#####
# p1 = c("912390737", "943420940")
# df[p1,"cell.type"] = "AV2p1"
#
# p2 = c("943420877", "1067546905", "1192007205", "1223045702", "1224078043")
# df[p2,"cell.type"] = "AV2p2"
#
# p3 = c("943412282", "1098249445")
# df[p3,"cell.type"] = "AV2p3"
#
# p4 = c("1099255933", "1013757060", "1067884486", "1066516552")
# df[p4,"cell.type"] = "AV2p4"
########
# save #
########
# Organise cell types
df = process_types(df = df, hemibrain_lhns = hemibrain_lhns)
# Summarise results
state_results(df)
# Write .csv
write.csv(df, file = "data-raw/hemibrain/pnts/csv/AV2_celltyping.csv", row.names = FALSE)
# Process
if(process){
# Make 2D Images
take_pictures(df)
# Update googlesheet
write_lhns(df = df, column = c("class", "pnt", "cell.type", "ItoLee_Hemilineage", "Hartenstein_Hemilineage"))
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.