I'm currently trying to perform DESEQ2 with my own RNA sequencing results. I performed whole transcriptome RNA sequencing and the subsequent analysis I performed via galaxy. I performed first fastp on the samples, afterwards I performed RNA star (to obtain Star counts similiar to the new TCGA pipeline) and afterwards I used the featurecounts function. The data from the featurecounts function I combined into one excel file (countsm) and I also created a coldata file with the information about the patients (pdataCPall). Subsequently I performed the DESEq2 analysis as described in the pipeline. Since I used the featurecounts function, I followed the "countsmatrix" vignette steps. After I obtained my DEGS, my results however, look confusing if I look at the volcano plots and plotMAs. For volcano plots and for plotMAS the first plot is done before lfcshrinkage and the 2nd is performed after lfcshrinkage. SInce there are barely any DEGS visible, I'm wondering if something during the analysis went wrong. Thank you very much for your help. Attached is my code.
counts=matrix with data after featurecounts pdataCPall: contains clinical data of patients
ddsnew <- DESeqDataSetFromMatrix(countData = countsm, colData= pdataCPall, design= ~ Myo) EnhancedVolcano(resMyonew, lab=rownames(resMyonew), x= 'log2FoldChange', y='pvalue', labSize = 1) reslfcMyonew <- lfcShrink(ddsnew, coef= 'Myo_1_vs_0', type='apeglm') sessionInfo: Version 1.4.1106