泡泡_ef50

背景 眾所周知宽菜，excel生成的文件后綴是xls或者xlsx谣膳，早期讀取這樣的文件，要么就另存為csv格式铅乡，要么就用readxls或者xlsx這樣的R包继谚，可能會遇到Rjava報...

泡泡_ef50 ·

文章寫得不錯，但是有個問題

res = results(dds2, contrast=c("condition", "control", "treat")) 這個地方應該是存在問題的

下面是help文件中result中contrast參數(shù)的描述

this argument specifies what comparison to extract from the object to build a results table. one of either:

a character vector with exactly three elements: the name of a factor in the design formula, the name of the numerator level for the fold change, and the name of the denominator level for the fold change (simplest case)

a list of 2 character vectors: the names of the fold changes for the numerator, and the names of the fold changes for the denominator. these names should be elements of resultsNames(object). if the list is length 1, a second element is added which is the empty character vector, character(). (more general case, can be to combine interaction terms and main effects)

a numeric contrast vector with one element for each element in resultsNames(object) (most general case)

If specified, the name argument is ignored.

可見阵幸，當contrast參數(shù)有三個元素時依次代表 數(shù)據(jù)中作為treat/control標簽的列的名稱, fold change的分子花履， 以及fold change的分母。
fold change 一般算的時treat/control挚赊，作者也在他的描述中說他算的是treat versus control诡壁，所以這里正常應該是
res = results(dds, contrast=c("condition", "treat", "control"))
在作者后面分析部分
> diff_gene_deseq2 <-subset(res, padj < 0.05 & abs(log2FoldChange) > 1)
> head(diff_gene_deseq2)
log2 fold change (MLE): condition control vs treat
也展示了他這里算的log2 fold change是control vs treat

ET君不愛玩DLC 評論自RNA-seq(7): DEseq2篩選差異表達基因并注釋(bioMart)