我最近投了一篇转录组的文章，编辑说我数据分析有问题。编辑的原话如下： the manuscript contains a major technical error in the analysis of the RNA-seq data and I agree with him on this point. The methods section indicates that raw reads were transformed into FPKM values prior to the identification of differentially expressed genes using DESeq2. However, DESeq2 should be used with raw counts (discrete data) and not with FPKM-transfomed values (continuous data).
下面是我在文章中的原文写法。 2.5Identification of DEGs
FeatureCounts v1.5.0-p3 was employed to count the numbers of reads mapped to each gene (Liao et al., 2014). Then, the fragments per kilo base of transcript per million reads (FPKM) method was used to normalize all data (Mortazavi et al., 2008). Differential expression analysis was carried out using the DESeq2 R package (1.16.1). The P-values were adjusted using the Benjamini and Hochberg’s approach to control false discovery rate (FDR) (Kim and van de Wiel, 2008). Genes with an adjusted P-value < 0.05 (Padj< 0.05) and the absolute value of Foldchange ≥ 1 obtained from DESeq2 were designated as DGEs.
有懂得的大神可以帮忙看看是哪里有问题吗，不甚感激

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