Mercurial > repos > davidecangelosi > pipe_t
changeset 7:3e099c082954 draft
planemo upload for repository https://github.com/igg-molecular-biology-lab/pipe-t.git commit 5c55ecdfd6ed19c7eb7558f278884511620df5dd
| author | davidecangelosi |
|---|---|
| date | Tue, 07 May 2019 06:03:18 -0400 |
| parents | d1cabb2bc795 |
| children | e5953805ad7a |
| files | pipe-t.R |
| diffstat | 1 files changed, 15 insertions(+), 6 deletions(-) [+] |
line wrap: on
line diff
--- a/pipe-t.R Mon May 06 06:39:28 2019 -0400 +++ b/pipe-t.R Tue May 07 06:03:18 2019 -0400 @@ -177,7 +177,7 @@ if (length(n.header)==0) n.header <- 0 # Read data, skip the required lines - out <- read.delim(file=readfile, header=TRUE, colClasses="character", nrows=nspots*n.data[i], skip=n.header-1, strip.white=TRUE, ...) + out <- read.delim(file=readfile, header=FALSE, colClasses="character", nrows=nspots*n.data[i], skip=n.header, strip.white=TRUE, ...) # Return out } # .readCtSDS @@ -257,8 +257,8 @@ if (missing(column.info)) { column.info <- switch(format, EDS = list(flag="EXPFAIL", feature="Target.Name", position="Well.Position", Ct="CT"), plain = list(flag = 4, feature = 6, type = 7, position = 3, Ct = 8), - #SDS = list(flag = 4,feature = 6, type = 7, position = 3, Ct = 8), - SDS = list(flag = "Omit",feature = "Detector", type = "Task", position = "Wells", Ct = "Ct"), + SDS = list(flag = 4,feature = 6, type = 7, position = 3, Ct = 8), + #SDS = list(flag = "Omit",feature = "Detector", type = "Task", position = "Pos", Ct = "Avg.Ct"), LightCycler = list(feature = "Name", position = "Pos", Ct = "Cp"), CFX = list(feature = "Content", position = "Well", Ct = "Cq.Mean"), OpenArray = list(flag = "ThroughHole.Outlier", @@ -289,8 +289,15 @@ n.data = n.data, i = i, nspots = nspots, ...), OpenArray = .readCtOpenArray(readfile = readfile, n.data = n.data, i = i, nspots = nspots, ...), BioMark = .readCtBioMark(readfile = readfile, n.data = n.data, i = i, nspots = nspots, ...)) - - data <- matrix(sample[, column.info[["Ct"]]], ncol = n.data[i]) + #if (format == "SDS") { + # if("Avg Ct" %in% colnames(n.data)){ + # data <- matrix(sample[, column.info[["Avg.Ct"]]], ncol = n.data[i]) + # } elseif { + # cat("\n Unsupported SDS format! ") + # } + #}else{ + data <- matrix(sample[, column.info[["Ct"]]], ncol = n.data[i]) + # } undeter <- apply(data, 2, function(x) x %in% c("Undetermined", "No Ct")) X.cat[, cols][undeter] <- "Undetermined" @@ -394,7 +401,7 @@ }, "SDS"={ #columns<- list(feature=3, Ct=6, flag=11) - columns <-list(flag = "Omit",feature = "Detector", type = "Task", position = "Wells", Ct = "Ct") + columns <-list(flag = "Omit",feature = "Detector", type = "Task", position = "Wells", Ct = "Avg.Ct") metadata <- data.frame(labelDescription = c("sampleName", "Treatment"), row.names = c("sampleName", "Treatment")) phenoData <- new("AnnotatedDataFrame", data = files, varMetadata = metadata) rownames(phenoData)=as.vector(files$sampleName) @@ -631,7 +638,9 @@ #user_number=5 #genorm <- selectHKs(t(delete.na(as.matrix(exprs(xGlico)),0)), method = "geNorm", Symbols = rownames(as.matrix(delete.na(exprs(xGlico),0))), minNrHK = as.numeric(user_number), log = TRUE) +#genorm #normfinder <- selectHKs(as.matrix(t(delete.na(exprs(xGlico),0))), group= files$Treatment , method = "NormFinder", Symbols =rownames(as.matrix(delete.na(exprs(xGlico),0))), minNrHK = as.numeric(user_number), log = TRUE) +#normfinder #intersection= intersect(normfinder$ranking, genorm$ranking[1:as.numeric(user_number)]) #cat("\n GeNorm and NormFinder transcripts selected as housekeeping for normalization! \n")