Hello

I'm analyzing some data from tcga (tumor x normal) with deseq2, but some genes are returning with really big log2 fc and p values. Like this:

                                    baseMean | log2FoldChange   |   lfcSE |stat |  pvalue |   padj

ENSG00000121691.4   278.024.793.462.181 **-147192720471788**    0.170612654907734   -862.730.379.240.558    6,28E-04    2,62E-02

ENSG00000250722.4   438.211.180.060.727 **-103006615299621**    0.160160306303726   -643.146.967.415.759    1,26E+04    **2,05E+05**

Is this ok or did I do something wrong? I used HTSEQ-counts data.

Example of how I performed the analysis:

Data was constructed like this:

Data counts= row (gene ids), columns (sample names)

Metadata= row (same sample names, same order), column (condition - target and control; subject - 1/1, 2/2 - paired by patient).

dds <-DESeqDataSetFromMatrix(countData = rawCountTable, colData = sampleInfo, design = ~ subject + condition)  

dds <- dds[ rowSums(counts(dds)) >1,]
dds$condition <- relevel(dds$condition, ref="Control")
dds <- estimateSizeFactors(dds)
dds <- estimateDispersions(dds)
dds <- DESeq(dds)
res <- results(dds, contrast=c("condition","Target","Control"), alpha=0.05)
res