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Aerospace Medicine Technical Reports
Friday, June 06, 2025FAA Office of Aerospace Medicine
Civil Aerospace Medical Institute
Report No:DOT/FAA/AM-23/02
Title and Subtitle: RNA-Seq Alignment and Differential Expression Software Comparison
Report Date: January, 2023
Authors: Munster SK, Nicholson SJ, Uyhelji HA
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.
Key Words: RNA-Seq, alignment, differential expression
No. of Pages:41
Aerospace Medicine Technical Reports
Friday, June 06, 2025FAA Office of Aerospace Medicine
Civil Aerospace Medical Institute
Report No:DOT/FAA/AM-23/01
Title and Subtitle: An Evaluation of the Downstream Effects of Purification Methods on RNA-Seq Differential Expression
Report Date: January 2023
Authors: Munster SK, Uyhelji HA, Nicholson SJ
Abstract: Ribonucleic acid sequencing (RNA-Seq) is a valuable and commonly used technique to quantify the number of individual RNA transcripts within a sample. RNA-Seq typically requires a small amount of pure and concentrated RNA, which can necessitate additional concentration or purification of previously isolated RNA samples. Magnetic beads and silica-based columns are often used to concentrate and/or purify RNA samples, but little is known about how these techniques influence downstream analyses. In this study, we collected blood from volunteer human subjects and pooled those samples during RNA extraction to minimize variance due to input material. We then purified aliquots of that sample pool to evaluate how sample purification and concentration influenced gene expression observations. Extracted RNA was sequenced, and the resulting RNA-Seq files were evaluated to determine the degree of differential expression between methods. Differential expression was detected in roughly half of the comparisons made and appeared attributable at least partly to differences in sample concentration and purification techniques.
Key Words: RNA-Seq, sample purification, differential expression
No. of Pages: 27