README.md
In christystarr/ambiguoustaxa:
Please contact cstarrmeredith@gmail.com for any additional information about running the ambiguous taxa program
The readme file is best viewed by at https://raw.githubusercontent.com/christystarr/ambiguoustaxa/master/README.md as the information below has errors.
#######################Part 1
Instructions: set working directory and put 2 input files in there. "Invertsinput.csv","lookup.csv". Example files are in the "data" folder on github. Column headings must match.
any taxonomic level that does not have a name associated with it must be "NA"
all of the taxa in the invertsinput.csv must be in the lookup table
set method to "widespread" or "numerous; set method_divide to "nodivide or "divide";
The final file is ambiguous_APTC_results.csv in the "all" folder, which has the original taxa (InvName), the new taxa when
ambiguous taxa are assigned at the site level (sitetaxa) and the new taxa when ambiguous taxa are assigned at the dataset level (newtaxa) according to the APTC_SG method
to produce final datasets for other common methods in Meredith et al., run extracode, part 2 (below)
Instructions for APTC_SG Method
setwd("C:/christy/examples") # set working directory where input files are located; columns must be the same as in example)
method="numerous" #options are "numerous" or "widespread" (see Meredith et al. 2019)
method_divide="divide" #options are "divide" or "nodivide" (see Meredith et al. 2019)
library(doBy)
library(plyr)
library(devtools)
install_github("christystarr/ambiguoustaxa")
library(ambiguoustaxa)
inverts=read.table("invertsinput.csv",sep=",",header=TRUE) # place example files from github in your working directory or create your own invertsinput.csv and lookup.csv
lookup=read.table("lookup.csv",sep=",",header=TRUE)
setup(lookup)
missinglevels(lookupsetup)
siteresolve(inverts,lookupready,"nodivide") #methods are "divide" or "nodivide" referring to whether the parent taxa will be divided among children at the site, or assigned to the most numerous at the site
allresolve(lookupready,invertssite_obs,invertsnew,"widespread") # methods are "numerous" or "widespread" refering to whether ambiguous taxa will be assigned to the child taxa that is most abundance,#or the child taxa found at the most sites
######################## Part 2
after running part 1, simply select the entire code below; final files after ambiguous taxa are resolved will be put into the working directory
creates datasets in which ambiguous taxa are resolve in different ways: APTC_S,APTC_SG,APTC_SG1,APTC_SG2,RPCK_S; puts these in working directory
also estimates variables describing number of singletons and doubleton and number uniques and duplicates; these will be in the global environment
setwd("all")
methods.b=read.table("ambiguous_APTC_results.csv",sep=",",header=TRUE)
if(method_divide=="divide") {
methods.b=methods.b[,c(1,3,4,5,7,2)]
}
if (method_divide != "divide"){
methods.b=methods.b[,c(1,3,4,5,7,2)]
}
calculate number of singletons and doubletons in original dataset
setwd("C://christy/examples")
colnames(methods.b)=c("obs","newtaxa","InvEventFK","InvName","InvCount","sitetaxa")
invertsorig=read.table("invertsinput.csv",sep=",",header=TRUE)
origsum=summaryBy(InvCount~InvName,FUN=c(sum),data=invertsorig)
origsing=subset(origsum,origsum$InvCount.sum==1)
origdoub=subset(origsum,origsum$InvCount.sum==2)
singledoub=rbind(origsing,origdoub)
length(origsing[,1])
length(origdoub[,1])
calculate number of uniques and duplicates in original dataset
origcount=summaryBy(InvCount~InvName+InvEventFK,FUN=c(sum),data=invertsorig)
origcount$InvCount.sum=ifelse(origcount$InvCount.sum>0,1,0)
origcount2=summaryBy(InvCount.sum~InvName,FUN=sum,data=origcount)
uniqueorig=subset(origcount2,origcount2$InvCount.sum.sum==1)
duporig=subset(origcount2,origcount2$InvCount.sum.sum==2)
uniqdup=rbind(uniqueorig,duporig)
length(uniqueorig[,1])
length(duporig[,1])
prepare to summarize
amb_sing2=merge(methods.b,singledoub,by.x=c("newtaxa"),by.y=c("InvName"),all.x=TRUE,all.y=FALSE)
amb_sing3=merge(amb_sing2,uniqdup,by.x=c("newtaxa"),by.y=c("InvName"),all.x=TRUE,all.y=FALSE)
amb_sing3=amb_sing3[,c(2,3,5,4,6,1,7,8)]
colnames(amb_sing3)=c("obs","InvEventFK","InvCount","InvName","sitetaxa","newtaxa","sing_doub","uniq_dup")
amb_sing3$sing_doub[is.na(amb_sing3$sing_doub)] <- 0
amb_sing3$uniq_dup[is.na(amb_sing3$uniq_dup)] <- 0
if(method=="numerous"){
create APTC_SG dataset
APTC_SG=summaryBy(InvCount~InvEventFK+newtaxa,data=amb_sing3,FUN=sum)
amb_sing3$newtaxa=as.character(amb_sing3$newtaxa)
amb_sing3$InvName=as.character(amb_sing3$InvName)
SG_singdoub=summaryBy(InvCount.sum~newtaxa,FUN=sum,data=APTC_SG)
singSG=subset(SG_singdoub,SG_singdoub$InvCount.sum.sum==1)
lsingSG=length(singSG[,1])
doubSG=subset(SG_singdoub,SG_singdoub$InvCount.sum.sum>1 & SG_singdoub$InvCount.sum.sum<=2 )
ldoubSG=length(doubSG[,1])
write.table(APTC_SG,"APTC_SG.csv",sep=",",row.names=FALSE)
create APTC_SG1 dataset
amb_sing3.SG1=amb_sing3[!(amb_sing3$sing_doub!=0 & amb_sing3$InvName!=amb_sing3$newtaxa),]
APTC_SG1=summaryBy(InvCount~InvEventFK+newtaxa,data=amb_sing3.SG1,FUN=sum)
test=unique(APTC_SG1$newtaxa)
APTC_SG1singdoub=summaryBy(InvCount.sum~newtaxa,FUN=sum,data=APTC_SG1)
singSG1=subset(APTC_SG1singdoub,APTC_SG1singdoub$InvCount.sum.sum==1)
lsingSG1=length(singSG1[,1])
doubSG1=subset(APTC_SG1singdoub,APTC_SG1singdoub$InvCount.sum.sum>1 & APTC_SG1singdoub$InvCount.sum.sum<=2 )
ldoubSG1=length(doubSG1[,1])
write.table(APTC_SG1,"APTC_SG1.csv",sep=",",row.names=FALSE)
create APTC_SG2 dataset
amb_sing3.SG2=amb_sing3[!(amb_sing3$sing_doub!=0 & amb_sing3$newtaxa==amb_sing3$sitetaxa & amb_sing3$InvName!=amb_sing3$newtaxa),]
APTC_SG2=summaryBy(InvCount~InvEventFK+newtaxa,data=amb_sing3.SG2,FUN=sum)
test=unique(APTC_SG2$newtaxa)
APTC_SG2singdoub=summaryBy(InvCount.sum~newtaxa,FUN=sum,data=APTC_SG2)
singSG2=subset(APTC_SG2singdoub,APTC_SG2singdoub$InvCount.sum.sum==1)
lsingSG2=length(singSG2[,1])
doubSG2=subset(APTC_SG2singdoub,APTC_SG1singdoub$InvCount.sum.sum>1 & APTC_SG2singdoub$InvCount.sum.sum<=2 )
ldoubSG2=length(doubSG2[,1])
write.table(APTC_SG2,"APTC_SG2.csv",sep=",",row.names=FALSE)
create APTC_S dataset
APTC_S=summaryBy(InvCount~InvEventFK + sitetaxa,FUN=sum,data=amb_sing3)
APTC_singdoub=summaryBy(InvCount~sitetaxa,FUN=sum,data=amb_sing3)
singAPTC_s=subset(APTC_singdoub,APTC_singdoub$InvCount.sum==1)
doubAPTC_s=subset(APTC_singdoub,APTC_singdoub$InvCount.sum==2)
l_singAPTC_s=length(singAPTC_s[,1])
l_doubAPTC_s=length(doubAPTC_s[,1])
write.table(APTC_S,"APTC_S.csv",sep=",",row.names=FALSE)
create RPKC_s datast
amb_sing3$diff=ifelse(amb_sing3$sitetaxa!=amb_sing3$InvName,1,0)
RPKC_s.a=subset(amb_sing3,amb_sing3$diff==0)
RPKC_s=summaryBy(InvCount~InvEventFK + sitetaxa,FUN=sum,data=RPKC_s.a)
RPKC_s_singdoub=summaryBy(InvCount.sum~sitetaxa,FUN=sum,data=RPKC_s)
sing_RPKC_s=subset(RPKC_s_singdoub,RPKC_s_singdoub$InvCount.sum==1)
doub_RPKC_s=subset(RPKC_s_singdoub,RPKC_s_singdoub$InvCount.sum==2)
lsing_RPKCS=length(sing_RPKC_s[,1])
ldoub_RPKCS=length(doub_RPKC_s[,1])
write.table(RPKC_s,"RPKC_s.csv",sep=",",row.names=FALSE)
}
if method = widespread instead of numerous
create APTC_SG dataset
if (method != "numerous") {
SGcount=summaryBy(InvCount~newtaxa+InvEventFK,FUN=c(sum),data=amb_sing3)
APTC_SG=SGcount
SGcount$InvCount.sum=ifelse(SGcount$InvCount.sum>0,1,0)
SGcount2=summaryBy(InvCount.sum~newtaxa,FUN=sum,data=SGcount)
uniqueSG=subset(SGcount2,SGcount2$InvCount.sum.sum==1)
lSG.uniques=length(uniqueSG[,1])
dupSG=subset(SGcount2,SGcount2$InvCount.sum.sum>1 & SGcount2$InvCount.sum.sum<=2)
lSG.dups=length(dupSG[,1])
write.table(APTC_SG,"APTC_SG.csv",sep=",")
write.table(dupSG,"origdup.csv",sep=",")
create APTC_SG1 dataste
amb_sing3$InvName=as.character(amb_sing3$InvName)
amb_sing3$newtaxa=as.character(amb_sing3$newtaxa)
amb_sing3.SG1.uniq=amb_sing3[!(amb_sing3$uniq_dup!=0 & amb_sing3$InvName!=amb_sing3$newtaxa),]
APTC_SG1=amb_sing3.SG1.uniq
APTC_SG1.uniq=summaryBy(InvCount~InvEventFK+newtaxa,data=amb_sing3.SG1.uniq,FUN=sum)
test=unique(APTC_SG1$newtaxa)
APTC_SG1.uniq$InvCount.sum=ifelse(APTC_SG1.uniq$InvCount.sum>0,1,0)
APTC_SG1.uniqdup=summaryBy(InvCount.sum~newtaxa,FUN=sum,data=APTC_SG1.uniq)
SG1.uniques=subset(APTC_SG1.uniqdup,APTC_SG1.uniqdup$InvCount.sum.sum==1)
SG1.dups=subset(APTC_SG1.uniqdup,APTC_SG1.uniqdup$InvCount.sum.sum>1 & APTC_SG1.uniqdup$InvCount.sum.sum<=2)
lSG1.uniques=length(SG1.uniques[,1])
lSG1.dups=length(SG1.dups[,1])
write.table(APTC_SG1,"APTC_SG1.csv",sep=",")
hmmmm
create APTC_SG2 dataset
amb_sing3.SG2=amb_sing3[!(amb_sing3$uniq_dup!=0 & amb_sing3$newtaxa!=amb_sing3$sitetaxa),]
APTC_SG2=amb_sing3.SG2
APTC_SG2=summaryBy(InvCount~InvEventFK+newtaxa,data=amb_sing3.SG2,FUN=sum)
APTC_SG2.uniq=summaryBy(InvCount~InvEventFK+newtaxa,data=amb_sing3.SG2,FUN=sum)
APTC_SG2.uniq$InvCount.sum=ifelse(APTC_SG2.uniq$InvCount.sum>0,1,0)
APTC_SG2.uniqdup=summaryBy(InvCount.sum~newtaxa,FUN=sum,data=APTC_SG2.uniq)
SG2.uniques=subset(APTC_SG2.uniqdup,APTC_SG2.uniqdup$InvCount.sum.sum==1)
SG2.dups=subset(APTC_SG2.uniqdup,APTC_SG2.uniqdup$InvCount.sum.sum>1 & APTC_SG2.uniqdup$InvCount.sum.sum<=2)
lSG2.uniques=length(SG2.uniques[,1])
lSG2.dups=length(SG2.dups[,1])
write.table(APTC_SG2,"APTC_SG2.csv",sep=",")
}
christystarr/ambiguoustaxa documentation built on May 28, 2019, 5:42 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.
Please contact cstarrmeredith@gmail.com for any additional information about running the ambiguous taxa program The readme file is best viewed by at https://raw.githubusercontent.com/christystarr/ambiguoustaxa/master/README.md as the information below has errors.
#######################Part 1
Instructions: set working directory and put 2 input files in there. "Invertsinput.csv","lookup.csv". Example files are in the "data" folder on github. Column headings must match.
any taxonomic level that does not have a name associated with it must be "NA"
all of the taxa in the invertsinput.csv must be in the lookup table
set method to "widespread" or "numerous; set method_divide to "nodivide or "divide";
The final file is ambiguous_APTC_results.csv in the "all" folder, which has the original taxa (InvName), the new taxa when
ambiguous taxa are assigned at the site level (sitetaxa) and the new taxa when ambiguous taxa are assigned at the dataset level (newtaxa) according to the APTC_SG method
to produce final datasets for other common methods in Meredith et al., run extracode, part 2 (below)
Instructions for APTC_SG Method
setwd("C:/christy/examples") # set working directory where input files are located; columns must be the same as in example) method="numerous" #options are "numerous" or "widespread" (see Meredith et al. 2019) method_divide="divide" #options are "divide" or "nodivide" (see Meredith et al. 2019)
library(doBy) library(plyr) library(devtools)
install_github("christystarr/ambiguoustaxa") library(ambiguoustaxa)
inverts=read.table("invertsinput.csv",sep=",",header=TRUE) # place example files from github in your working directory or create your own invertsinput.csv and lookup.csv lookup=read.table("lookup.csv",sep=",",header=TRUE)
setup(lookup) missinglevels(lookupsetup) siteresolve(inverts,lookupready,"nodivide") #methods are "divide" or "nodivide" referring to whether the parent taxa will be divided among children at the site, or assigned to the most numerous at the site allresolve(lookupready,invertssite_obs,invertsnew,"widespread") # methods are "numerous" or "widespread" refering to whether ambiguous taxa will be assigned to the child taxa that is most abundance,#or the child taxa found at the most sites
######################## Part 2
after running part 1, simply select the entire code below; final files after ambiguous taxa are resolved will be put into the working directory
creates datasets in which ambiguous taxa are resolve in different ways: APTC_S,APTC_SG,APTC_SG1,APTC_SG2,RPCK_S; puts these in working directory
also estimates variables describing number of singletons and doubleton and number uniques and duplicates; these will be in the global environment
setwd("all") methods.b=read.table("ambiguous_APTC_results.csv",sep=",",header=TRUE)
if(method_divide=="divide") { methods.b=methods.b[,c(1,3,4,5,7,2)] }
if (method_divide != "divide"){ methods.b=methods.b[,c(1,3,4,5,7,2)] }
calculate number of singletons and doubletons in original dataset
setwd("C://christy/examples") colnames(methods.b)=c("obs","newtaxa","InvEventFK","InvName","InvCount","sitetaxa") invertsorig=read.table("invertsinput.csv",sep=",",header=TRUE) origsum=summaryBy(InvCount~InvName,FUN=c(sum),data=invertsorig) origsing=subset(origsum,origsum$InvCount.sum==1) origdoub=subset(origsum,origsum$InvCount.sum==2) singledoub=rbind(origsing,origdoub) length(origsing[,1]) length(origdoub[,1])
calculate number of uniques and duplicates in original dataset
origcount=summaryBy(InvCount~InvName+InvEventFK,FUN=c(sum),data=invertsorig) origcount$InvCount.sum=ifelse(origcount$InvCount.sum>0,1,0) origcount2=summaryBy(InvCount.sum~InvName,FUN=sum,data=origcount) uniqueorig=subset(origcount2,origcount2$InvCount.sum.sum==1) duporig=subset(origcount2,origcount2$InvCount.sum.sum==2) uniqdup=rbind(uniqueorig,duporig) length(uniqueorig[,1]) length(duporig[,1])
prepare to summarize
amb_sing2=merge(methods.b,singledoub,by.x=c("newtaxa"),by.y=c("InvName"),all.x=TRUE,all.y=FALSE) amb_sing3=merge(amb_sing2,uniqdup,by.x=c("newtaxa"),by.y=c("InvName"),all.x=TRUE,all.y=FALSE) amb_sing3=amb_sing3[,c(2,3,5,4,6,1,7,8)] colnames(amb_sing3)=c("obs","InvEventFK","InvCount","InvName","sitetaxa","newtaxa","sing_doub","uniq_dup") amb_sing3$sing_doub[is.na(amb_sing3$sing_doub)] <- 0 amb_sing3$uniq_dup[is.na(amb_sing3$uniq_dup)] <- 0
if(method=="numerous"){
create APTC_SG dataset
APTC_SG=summaryBy(InvCount~InvEventFK+newtaxa,data=amb_sing3,FUN=sum) amb_sing3$newtaxa=as.character(amb_sing3$newtaxa) amb_sing3$InvName=as.character(amb_sing3$InvName) SG_singdoub=summaryBy(InvCount.sum~newtaxa,FUN=sum,data=APTC_SG) singSG=subset(SG_singdoub,SG_singdoub$InvCount.sum.sum==1) lsingSG=length(singSG[,1]) doubSG=subset(SG_singdoub,SG_singdoub$InvCount.sum.sum>1 & SG_singdoub$InvCount.sum.sum<=2 ) ldoubSG=length(doubSG[,1]) write.table(APTC_SG,"APTC_SG.csv",sep=",",row.names=FALSE)
create APTC_SG1 dataset
amb_sing3.SG1=amb_sing3[!(amb_sing3$sing_doub!=0 & amb_sing3$InvName!=amb_sing3$newtaxa),] APTC_SG1=summaryBy(InvCount~InvEventFK+newtaxa,data=amb_sing3.SG1,FUN=sum) test=unique(APTC_SG1$newtaxa)
APTC_SG1singdoub=summaryBy(InvCount.sum~newtaxa,FUN=sum,data=APTC_SG1)
singSG1=subset(APTC_SG1singdoub,APTC_SG1singdoub$InvCount.sum.sum==1) lsingSG1=length(singSG1[,1]) doubSG1=subset(APTC_SG1singdoub,APTC_SG1singdoub$InvCount.sum.sum>1 & APTC_SG1singdoub$InvCount.sum.sum<=2 ) ldoubSG1=length(doubSG1[,1]) write.table(APTC_SG1,"APTC_SG1.csv",sep=",",row.names=FALSE)
create APTC_SG2 dataset
amb_sing3.SG2=amb_sing3[!(amb_sing3$sing_doub!=0 & amb_sing3$newtaxa==amb_sing3$sitetaxa & amb_sing3$InvName!=amb_sing3$newtaxa),] APTC_SG2=summaryBy(InvCount~InvEventFK+newtaxa,data=amb_sing3.SG2,FUN=sum) test=unique(APTC_SG2$newtaxa)
APTC_SG2singdoub=summaryBy(InvCount.sum~newtaxa,FUN=sum,data=APTC_SG2)
singSG2=subset(APTC_SG2singdoub,APTC_SG2singdoub$InvCount.sum.sum==1) lsingSG2=length(singSG2[,1]) doubSG2=subset(APTC_SG2singdoub,APTC_SG1singdoub$InvCount.sum.sum>1 & APTC_SG2singdoub$InvCount.sum.sum<=2 ) ldoubSG2=length(doubSG2[,1]) write.table(APTC_SG2,"APTC_SG2.csv",sep=",",row.names=FALSE)
create APTC_S dataset
APTC_S=summaryBy(InvCount~InvEventFK + sitetaxa,FUN=sum,data=amb_sing3) APTC_singdoub=summaryBy(InvCount~sitetaxa,FUN=sum,data=amb_sing3) singAPTC_s=subset(APTC_singdoub,APTC_singdoub$InvCount.sum==1) doubAPTC_s=subset(APTC_singdoub,APTC_singdoub$InvCount.sum==2) l_singAPTC_s=length(singAPTC_s[,1]) l_doubAPTC_s=length(doubAPTC_s[,1]) write.table(APTC_S,"APTC_S.csv",sep=",",row.names=FALSE)
create RPKC_s datast
amb_sing3$diff=ifelse(amb_sing3$sitetaxa!=amb_sing3$InvName,1,0) RPKC_s.a=subset(amb_sing3,amb_sing3$diff==0) RPKC_s=summaryBy(InvCount~InvEventFK + sitetaxa,FUN=sum,data=RPKC_s.a) RPKC_s_singdoub=summaryBy(InvCount.sum~sitetaxa,FUN=sum,data=RPKC_s) sing_RPKC_s=subset(RPKC_s_singdoub,RPKC_s_singdoub$InvCount.sum==1) doub_RPKC_s=subset(RPKC_s_singdoub,RPKC_s_singdoub$InvCount.sum==2) lsing_RPKCS=length(sing_RPKC_s[,1]) ldoub_RPKCS=length(doub_RPKC_s[,1]) write.table(RPKC_s,"RPKC_s.csv",sep=",",row.names=FALSE)
}
if method = widespread instead of numerous
create APTC_SG dataset
if (method != "numerous") { SGcount=summaryBy(InvCount~newtaxa+InvEventFK,FUN=c(sum),data=amb_sing3) APTC_SG=SGcount SGcount$InvCount.sum=ifelse(SGcount$InvCount.sum>0,1,0) SGcount2=summaryBy(InvCount.sum~newtaxa,FUN=sum,data=SGcount) uniqueSG=subset(SGcount2,SGcount2$InvCount.sum.sum==1) lSG.uniques=length(uniqueSG[,1]) dupSG=subset(SGcount2,SGcount2$InvCount.sum.sum>1 & SGcount2$InvCount.sum.sum<=2) lSG.dups=length(dupSG[,1])
write.table(APTC_SG,"APTC_SG.csv",sep=",")
write.table(dupSG,"origdup.csv",sep=",")
create APTC_SG1 dataste
amb_sing3$InvName=as.character(amb_sing3$InvName) amb_sing3$newtaxa=as.character(amb_sing3$newtaxa) amb_sing3.SG1.uniq=amb_sing3[!(amb_sing3$uniq_dup!=0 & amb_sing3$InvName!=amb_sing3$newtaxa),] APTC_SG1=amb_sing3.SG1.uniq APTC_SG1.uniq=summaryBy(InvCount~InvEventFK+newtaxa,data=amb_sing3.SG1.uniq,FUN=sum)
test=unique(APTC_SG1$newtaxa)
APTC_SG1.uniq$InvCount.sum=ifelse(APTC_SG1.uniq$InvCount.sum>0,1,0) APTC_SG1.uniqdup=summaryBy(InvCount.sum~newtaxa,FUN=sum,data=APTC_SG1.uniq) SG1.uniques=subset(APTC_SG1.uniqdup,APTC_SG1.uniqdup$InvCount.sum.sum==1) SG1.dups=subset(APTC_SG1.uniqdup,APTC_SG1.uniqdup$InvCount.sum.sum>1 & APTC_SG1.uniqdup$InvCount.sum.sum<=2) lSG1.uniques=length(SG1.uniques[,1]) lSG1.dups=length(SG1.dups[,1]) write.table(APTC_SG1,"APTC_SG1.csv",sep=",")
hmmmm
create APTC_SG2 dataset
amb_sing3.SG2=amb_sing3[!(amb_sing3$uniq_dup!=0 & amb_sing3$newtaxa!=amb_sing3$sitetaxa),] APTC_SG2=amb_sing3.SG2 APTC_SG2=summaryBy(InvCount~InvEventFK+newtaxa,data=amb_sing3.SG2,FUN=sum) APTC_SG2.uniq=summaryBy(InvCount~InvEventFK+newtaxa,data=amb_sing3.SG2,FUN=sum) APTC_SG2.uniq$InvCount.sum=ifelse(APTC_SG2.uniq$InvCount.sum>0,1,0) APTC_SG2.uniqdup=summaryBy(InvCount.sum~newtaxa,FUN=sum,data=APTC_SG2.uniq) SG2.uniques=subset(APTC_SG2.uniqdup,APTC_SG2.uniqdup$InvCount.sum.sum==1) SG2.dups=subset(APTC_SG2.uniqdup,APTC_SG2.uniqdup$InvCount.sum.sum>1 & APTC_SG2.uniqdup$InvCount.sum.sum<=2) lSG2.uniques=length(SG2.uniques[,1]) lSG2.dups=length(SG2.dups[,1])
write.table(APTC_SG2,"APTC_SG2.csv",sep=",")
}
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