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Summary Non-negative Matrix Factorization (NMF) algorithms associate gene expression with biological processes (e.g. time-course dynamics or disease subtypes). Compared with univariate associations, the relative weights of NMF solutions can obscure biomarkers. Therefore, we developed a novel patternMarkers statistic to extract genes for biological validation and enhanced visualization of NMF results. Finding novel and unbiased gene markers with patternMarkers requires whole-genome data. Therefore, we also developed Genome-Wide CoGAPS Analysis in Parallel Sets (GWCoGAPS), the first robust whole genome Bayesian NMF using the sparse, MCMC algorithm, CoGAPS. Additionally, a manual version of the GWCoGAPS algorithm contains analytic and visualization tools including patternMatcher, a Shiny web application. The decomposition in the manual pipeline can be replaced with any NMF algorithm, for further generalization of the software. Using these tools, we find granular brain-region and cell-type specific signatures with corresponding biomarkers in GTEx data, illustrating GWCoGAPS and patternMarkers ascertainment of data-driven biomarkers from whole-genome data. Availability and Implementation PatternMarkers & GWCoGAPS are in the CoGAPS Bioconductor package (3.5) under the GPL license. Supplementary information Supplementary data are available at Bioinformatics online.

Summary: SNOMAD is a collection of algorithms for the normalization and standardization of gene expression datasets derived from diverse biological and technological sources. In addition to conventional transformations and visualization tools, SNOMAD includes two non-linear transformations which correct for bias and variance which are non-uniformly distributed across the range of microarray element signal intensities: (1) Local mean normalization; and (2) Local variance correction (Z-score generation using a locally calculated standard deviation). Availability: The SNOMAD tools were developed in the R statistical language http://www.r-project.org/. SNOMAD is an interactive, user-friendly web-application which can be accessed freely via the internet with any standard HTML browser: http://pevsnerlab.kennedykrieger.org/snomad.htm. Contact: ccolantu@jhmi.edu or pevsner@jhmi.edu * To whom correspondence should be addressed. † Present address: Wadham College, Oxford University, UK.