So I am running data analysis on count data using DESeq2. I have three biological replicates for each condition. My results show significant p values but no padj values other than 1, even with very low pval. How can I troubleshoot? Truncated data set attached.
setwd("C:/Users/Melissa Randel/Desktop")
library( "DESeq" )
theta = 0.3
Fname_pos = "trunc_DESeq_out"
CountTable3L_pos = read.table("counts_table.txt")
Design3L_pos = data.frame( row.names = colnames( CountTable3L_pos ), condition = c( "untreated", "untreated", "untreated", "treated", "treated", "treated" ), libType = c( "single-end", "single-end", "single-end", "single-end", "single-end","single-end" ) )
singleSamples_pos = Design3L_pos$libType == "single-end"
countTable_pos = CountTable3L_pos[ , singleSamples_pos]
condition_pos = Design3L_pos$condition[ singleSamples_pos ]
full_cds_pos = newCountDataSet( countTable_pos, condition_pos )
rs_pos = rowSums ( counts ( full_cds_pos ))
use = (rs_pos > quantile(rs_pos, probs=theta))
table(use)
cds_pos = full_cds_pos[use,]
cds_pos = estimateSizeFactors( cds_pos )
cds_pos = estimateDispersions( cds_pos )
res_pos = nbinomTest( cds_pos, "untreated", "treated" )
write.table(res_pos, file = Fname_pos, append = FALSE, quote = FALSE, sep = "\t", eol = "\n", na = "NA", dec = ".", row.names = TRUE, col.names = TRUE, qmethod = c("escape", "double"), fileEncoding = "")
min(res_pos$padj)
setwd("C:/Users/Melissa Randel/Desktop")
library( "DESeq" )
theta = 0.3
Fname_pos = "trunc_DESeq_out"
CountTable3L_pos = read.table("counts_table.txt")
Design3L_pos = data.frame( row.names = colnames( CountTable3L_pos ), condition = c( "untreated", "untreated", "untreated", "treated", "treated", "treated" ), libType = c( "single-end", "single-end", "single-end", "single-end", "single-end","single-end" ) )
singleSamples_pos = Design3L_pos$libType == "single-end"
countTable_pos = CountTable3L_pos[ , singleSamples_pos]
condition_pos = Design3L_pos$condition[ singleSamples_pos ]
full_cds_pos = newCountDataSet( countTable_pos, condition_pos )
rs_pos = rowSums ( counts ( full_cds_pos ))
use = (rs_pos > quantile(rs_pos, probs=theta))
table(use)
cds_pos = full_cds_pos[use,]
cds_pos = estimateSizeFactors( cds_pos )
cds_pos = estimateDispersions( cds_pos )
res_pos = nbinomTest( cds_pos, "untreated", "treated" )
write.table(res_pos, file = Fname_pos, append = FALSE, quote = FALSE, sep = "\t", eol = "\n", na = "NA", dec = ".", row.names = TRUE, col.names = TRUE, qmethod = c("escape", "double"), fileEncoding = "")
min(res_pos$padj)
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