Hello, i'am a bit new to deseq2 and wanted to understand

I wanted to test for two factors (meiosis stage and température) separately:

code

samples <- read.table(file="samples_WheatOmics.txt", header=TRUE)

model <- ~ stade

design=paste0(model[2])

rownames(samples) <- samples$run

files <- file.path("WheatOmics-salmon/salmon", samples$run, "quant.sf")

names(files) <- samples$run

txi <- tximport(files, type="salmon", txOut=TRUE, ignoreAfterBar = TRUE)

ddsTxi <- DESeqDataSetFromTximport(txi, colData = samples, design = model )

dds <- DESeq(ddsTxi)

res_dds_padj <- results(dds, alpha=0.05)

res_dds_padj <- res_dds_padj[order(res_dds_padj$padj),]

res_dds_padj <- na.omit(res_dds_padj)

summary(res_dds_padj)

Summary (Meiosis Stage factor)

out of 124677 with nonzero total read count
adjusted p-value < 0.05
LFC > 0 (up)       : 16853, 14%
LFC < 0 (down)     : 9652, 7.7%
outliers [1]       : 0, 0%
low counts [2]     : 0, 0%
(mean count < 1)
[1] see 'cooksCutoff' argument of ?results
[2] see 'independentFiltering' argument of ?results

Summary (température factor)

out of 91748 with nonzero total read count
adjusted p-value < 0.05
LFC > 0 (up)       : 779, 0.85%
LFC < 0 (down)     : 1036, 1.1%
outliers [1]       : 0, 0%
low counts [2]     : 0, 0%
(mean count < 8)
[1] see 'cooksCutoff' argument of ?results
[2] see 'independentFiltering' argument of ?results

Can you explain why is there 124677 vs 91748, thanks in advance

You removed a different set of genes with the na.omit call, see vignette on the meaning of NA in results.

Thank you so much, have a great day.