ArticleBioinformatics (Oxford, England)2017
PatternMarkers & GWCoGAPS for novel data-driven biomarkers via whole transcriptome NMF.
Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed.
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- Spatial profiling of human pancreatic ductal adenocarcinoma reveals molecular alterations associated with venous invasion.Science translational medicine · 2025Article
- Allelic bias contributes to heterogeneous phenotypes of NK cell deficiency.Cell reports · 2025Article
- Spatial proteomics and transcriptomics reveal early immune cell organization in pancreatic intraepithelial neoplasia.JCI insight · 2025Article
- Early developmental origins of cortical disorders modeled in human neural stem cells.Nature communications · 2025Article
- Transcriptional signatures of hippocampal tau pathology in primary age-related tauopathy and Alzheimer's disease.Cell reports · 2025Article
- Individual variation in the emergence of anterior-to-posterior neural fates from human pluripotent stem cells.Stem cell reports · 2024Article
- PanIN and CAF transitions in pancreatic carcinogenesis revealed with spatial data integration.Cell systems · 2024Article
- Integration of Clinical Trial Spatial Multiomics Analysis and Virtual Clinical Trials Enables Immunotherapy Response Prediction and Biomarker Discovery.Cancer research · 2024Article
- Gene expression signatures in blood from a West African sepsis cohort define host response phenotypes.Nature communications · 2024Article
- Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Inflammation in Cancer Cells in Pancreatic Ductal Adenocarcinoma.Cancer research · 2024Article
- Systems immunology spanning tumors, lymph nodes, and periphery.Cell reports methods · 2023Review
- Inferring cellular and molecular processes in single-cell data with non-negative matrix factorization using Python, R and GenePattern Notebook implementations of CoGAPS.Nature protocols · 2023Review
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- Informing virtual clinical trials of hepatocellular carcinoma with spatial multi-omics analysis of a human neoadjuvant immunotherapy clinical trial.bioRxiv : the preprint server for biology · 2023Article
- easyMF: A Web Platform for Matrix Factorization-Based Gene Discovery from Large-scale Transcriptome Data.Interdisciplinary sciences, computational life sciences · 2022Article
- Triple-negative breast cancer metastasis involves complex epithelial-mesenchymal transition dynamics and requires vimentin.Science translational medicine · 2022Article
Corrections and comments
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Authors and funding
16 authors.
Funding
Abstract
summaryNon-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. CONTACT: gsteinobrien@jhmi.edu or ccolantu@jhmi.edu or ejfertig@jhmi.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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