Hello I'm doing an rna seq differential expression analysis using DESeq2 I did the read counting using FeatureCount but didn't normalize the read counts after. I just wanted to confirm if I have interpreted the DESeq2 manual statement correctly ? Is it saying I don't need to write a command for DESeq2 to do the read count normalization in my script because DESeq2 already does it automatically by default ? DESEQ2 manual states: "Why un-normalized counts? As input, the DESeq2 package expects count data as obtained, e.g., from RNA-seq or another high-throughput sequencing experiment, in the form of a matrix of integer values. The value in the i-th row and the j-th column of the matrix tells how many reads can be assigned to gene i in sample j. Analogously, for other types of assays, the rows of the matrix might correspond e.g. to binding regions (with ChIP-Seq) or peptide sequences (with quantitative mass spectrometry). We will list method for obtaining count matrices in sections below.The values in the matrix should be un-normalized counts or estimated counts of sequencing reads (for single-end RNA-seq) or fragments (for paired-end RNA-seq). The RNA-seq workflow describes multiple techniques for preparing such count matrices. It is important to provide count matrices as input for DESeq2’s statistical model (Love, Huber, and Anders 2014) to hold, as only the count values allow assessing the measurement precision correctly. The DESeq2 model internally corrects for library size, so transformed or normalized values such as counts scaled by library size should not be used as input."
Also, If DESeq2 does it automatically what technique does it use to do the read count normalization ?