Name
Title | ||
|---|---|---|
PatternMarkers & GWCoGAPS for novel data-driven biomarkers via whole transcriptome NMF. |
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1093/bioinformatics/btx058 | BIOINFORMATICS |
Field | DocType | Volume |
Data mining,Data-driven,Computer science,Transcriptome,Artificial intelligence,Non-negative matrix factorization,Bioinformatics,Machine learning | Journal | 33 |
Issue | ISSN | Citations |
12 | 1367-4803 | 0 |
PageRank | References | Authors |
0.34 | 3 | 16 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Genevieve L. Stein-O'Brien | 1 | 0 | 0.68 |
| Jacob L. Carey | 2 | 0 | 0.34 |
| Waishing Lee | 3 | 0 | 0.68 |
| Michael Considine | 4 | 2 | 1.47 |
| Alexander Favorov | 5 | 56 | 8.02 |
| Emily Flam | 6 | 0 | 0.68 |
| Theresa Guo | 7 | 0 | 0.68 |
| Sijia Li | 8 | 0 | 0.34 |
| Luigi Marchionni | 9 | 28 | 1.92 |
| Thomas Sherman | 10 | 0 | 0.34 |
| Shawn Sivy | 11 | 0 | 0.34 |
| Daria A. Gaykalova | 12 | 0 | 1.01 |
| Ronald D McKay | 13 | 4 | 1.49 |
| Michael F. Ochs | 14 | 0 | 0.68 |
| Carlo Colantuoni | 15 | 24 | 4.33 |
| Elana J. Fertig | 16 | 19 | 4.78 |