Critical Assessment of RNA-Seq Differential Expression
Contributors
Supervisor:
Description
Warden and Wu Preprint: v1
In general, this primarily focuses on the following types of comparisons:
- Cell line experiments with over-expression or knock-down to define a known causal gene, with processing starting with public reads.
- Processed TCGA (The Cancer Genome Atlas) data for breast cancer (BRCA) to compare gene expression by immunohistochemistry status (ER/ESR1, PR/PGR, or HER2/ERBB2).
Differential expression methods include the following:
- edgeR (GLM)
- edgeR-robust (GLM)
- edgeR (QL)
- edgeR-robust (QL)
- DESeq1
- DESeq2
- limma-voom
- limma-trend (CPM)
- limma-trend (FPKM/RPKM)
- ANOVA (log2 FRPKM/RPKM)
The most common preprocessing strategies include STAR, TopHat2, and Salmon. However, a limited amount of additional processing with HISAT2, kallisto, Bowtie2 (+eXpress), and Bowtie1 (+RSEM) is also provided.
Most STAR and TopHat2 alignments use htseq-count for quantification, as well as running cuffdiff (for single variable 2-group comparisons). However, a limited amount of additional processing with featureCounts is also provided.
Most STAR and TopHat2 alignments start with the public forward reads, even if paired-end data was available.
Notes
Notes
Files
bioRxiv-Downstream_Code.zip
Files
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