United States Department of Transportation
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RNA-Seq Alignment and Differential Expression Software Comparison
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2023-01-01
[PDF-2.67 MB]
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Alternative Title:Assessment of RNA-seq Sample Preparation Methodology [Project Name]
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Abstract:The twofold goals for this study were to determine an optimum choice for ribonucleic acid sequencing (RNA-Seq) alignment software and to determine which differential expression software packages produced consistent and accurate results. RNA was extracted from blood and pooled to produce homogenous sample material to ensure that any differential expression between samples was attributable to characteristics of downstream processing or software choice. Also, simulated sequence data were produced with a known rate of differential expression. After RNA-Seq, all datasets had alignments (or pseudoalignments) performed by Bowtie2, HISAT2, kallisto, RSEM, Rsubread, Salmon, and STAR. Feature counts were tabulated and analyzed for differential expression using ALDEx2, baySeq, DEGseq, DESeq2, edgeR, limma, NOISeq, PoissonSeq, and SAMseq (samr), and results were compared. Findings indicated that kallisto, Salmon, and STAR provided superior mapping performance, were quickest, and had the smallest output file size compared to the others tested. The differential expression software DESeq2, edgeR, and limma had the most accurate true positive rate with simulated data and consistently performed as expected with real datasets.
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