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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”