Table 1 mitch can import profiling data generated by a wide range of upstream tools
From: mitch: multi-contrast pathway enrichment for multi-omics and single-cell profiling data
Target application | Tool | Reference | Function | Ranking metric |
|---|---|---|---|---|
RNA-seq (and other applications of count based quantification) | edgeR | [20] | topTable() | “logFC” and “PValue” |
DESeq2 | [21] | results() | “stat” | |
ABSSeq | [22] | results() | “foldChange” and “pvalue” | |
topConfects | [23] | edger_confects() limma_confects() | “confect” | |
fishpond/Swish | [24] | swish() | “stat” | |
NOIseq | [25] | noiseq() | “ranking” | |
Ballgown | [26] | stattest() | “fc” and “pval” | |
TCC | [27] | getResult() | “m.value” and “p.value” | |
Sleuth | [28] | sleuth_results() | “b” and “pval” | |
Cufflinks | [29] | cuffdiff | “test_stat” | |
Expression microarray | limma | [8] | topTable() | “t” |
DEDS | [30] | topgenes() | “t” | |
scRNA-seq (and other applications of barcoded cell based count quantification) | Seurat | [31] | FindMarkers() | “avg_logFC” and “p_val” |
Muscat | [32] | pbDS() | “logFC” and “p_val” | |
scde | [33] | scde.expression.difference() | “Z” | |
MAST | [34] | zlm() | “Coef” and “Pr(>Chisq)” | |
DEsingle | [35] | DEtype() | “foldchange” and “pvalue” | |
Methylation array | missMethyl | [36] | topTable() | “t” |
DMRcate | [37] | extractRanges() | “meanbetafc” and “Stouffer” | |
Differential proteomics | DEP | [38] | get_results() | “ratio” and “p.val” |
msmsTests | [39] | msms.glm.pois(), msms.glm.qlll() or msms.edgeR() | “LogFC” and “p.value” | |
plgem | [40] | plgem.deg() | “PLGEM.STN” and “p.value” | |
SDAMS | [41] | SDA() | “beta” and “pv_2part” | |
DEqMS | [42] | DEqMS | “t” | |
Differential binding | DiffBind | [43] | dba.report() | “Fold” and “p.value” |