. Author manuscript; available in PMC: 2018 Mar 20.

Published in final edited form as: IEEE Trans Biomed Eng. 2016 Oct 10;64(2):263–273. doi: 10.1109/TBME.2016.2573285

TABLE V.

Selected Tools for -Omic Biomarker Identification

Tool	-Omic Data	-Omic Biomarker	Approach
SNPassoc [89]	Genomic	Significant SNPs associated with traits	Genome- wide association studies
SNPTEST^* [90]		Significant SNPs associated with traits
VAT [91]		Significant SNPs and indels associated with traits
PLINK^* [92]		Significant SNPs, indels, and CNVs associated with traits
CNVRuler [93]		Significant CNVs associated with traits
edgeR^* [94]	Transcriptomic	Differentially expressed genes /transcripts	Differential analysis (model fitting and statistical tests)
DESeq2^* [95]
omniBiomarker [96]
DiffSplice [97]		Differential alternative splicing
MATS [98]		Differential alternative splicing
DBChIP [99]	Epigenomic	Differential binding sites
ChIPDiff [100]		Differential histone modification sites
QDMR [101]		Differentially methylated regions
DetectTLC [102]	Proteomic and metabolomic	Molecular patterns in mass spectrometry images	Similarity scoring
Automics [103]		Differentially abundant metabolites	Supervised and unsupervised learning
MetaboAnalyst^* [104]		Differentially abundant metabolites	Supervised and unsupervised learning

SNPassoc stands for SNP-based whole genome association studies; VAT, variant association tools; PLINK, population-based linkage analyses; edgeR, empirical analysis of digital gene expression data in R; MATS, multivariate analysis of transcript splicing; DBChIP, differential binding with ChIP-seq data; and QDMR, quantitative differentially methylated regions.

Highly impactful tool with more than 50 citations per year.