Hydra: A mixture modeling framework for subtyping pediatric cancer cohorts using multimodal gene expression signatures
暂无分享,去创建一个
David Haussler | Holly C Beale | Lauren M Sanders | Jacob Pfeil | Sofie R Salama | Olena Morozova Vaske | Ioannis Anastopoulos | A Geoffrey Lyle | Alana S Weinstein | Yuanqing Xue | Andrew Blair | Alex Lee | Stanley G Leung | Phuong T Dinh | Avanthi Tayi Shah | Marcus R Breese | W Patrick Devine | Isabel Bjork | E Alejandro Sweet-Cordero | Marcus R. Breese | Holly C. Beale | Lauren M. Sanders | D. Haussler | S. Salama | Jacob Pfeil | M. Breese | E. A. Sweet-Cordero | Ioannis N. Anastopoulos | A. Weinstein | Stanley G. Leung | Olena M. Vaske | Alex G. Lee | P. Dinh | O. Vaske | W. Devine | Alex Lee | A. Shah | Isabel Bjork | A. G. Lyle | A. Blair | Yuanqing Xue | W. | Stanley G. Leung | Jacob | PfeilID | Ioannis | AnastopoulosID | A. Geoffrey | LyleID | S. Alana | WeinsteinID | Yuanqing | XueID | C. Holly | BealeID | T. Phuong | DinhID | Patrick | DevineID | R. Sofie | SalamaID | -. E.AlejandroSweet | CorderoID | Olena Morozova | VaskeID | Ioannis Anastopoulos | Alana S. Weinstein | Yuanqing Xue | Phuong T Dinh | W. Patrick Devine | E. Sweet-Cordero
[1] Mathieu Bastian,et al. Gephi: An Open Source Software for Exploring and Manipulating Networks , 2009, ICWSM.
[2] David B. Dunson,et al. Bayesian data analysis, third edition , 2013 .
[3] A. Butte,et al. xCell: digitally portraying the tissue cellular heterogeneity landscape , 2017, Genome Biology.
[4] W. Huber,et al. which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. MAnorm: a robust model for quantitative comparison of ChIP-Seq data sets , 2011 .
[5] Deshka S. Foster,et al. The evolving relationship of wound healing and tumor stroma. , 2018, JCI insight.
[6] Ash A. Alizadeh,et al. Robust enumeration of cell subsets from tissue expression profiles , 2015, Nature Methods.
[7] Erik B. Sudderth,et al. Memoized Online Variational Inference for Dirichlet Process Mixture Models , 2013, NIPS.
[8] Peter W. Laird,et al. Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer , 2018, Cell.
[9] Paul G. Thomas,et al. Pediatric patients with acute lymphoblastic leukemia generate abundant and functional neoantigen-specific CD8+ T cell responses , 2019, Science Translational Medicine.
[10] Debashis Ghosh,et al. Mixture models for assessing differential expression in complex tissues using microarray data , 2004, Bioinform..
[11] Joshua M. Stuart,et al. The Cancer Genome Atlas Pan-Cancer analysis project , 2013, Nature Genetics.
[12] Peter F Thall,et al. Bayesian nonparametric statistics: A new toolkit for discovery in cancer research , 2017, Pharmaceutical statistics.
[13] Peter J Houghton,et al. Initial testing of the aurora kinase a inhibitor MLN8237 by the Pediatric Preclinical Testing Program (PPTP) , 2010, Pediatric blood & cancer.
[14] Maksim Terpilowski,et al. scikit-posthocs: Pairwise multiple comparison tests in Python , 2019, J. Open Source Softw..
[15] Steven J. M. Jones,et al. Integrated Genomic Characterization of Pancreatic Ductal Adenocarcinoma. , 2017, Cancer cell.
[16] Gary D Bader,et al. Enrichment Map: A Network-Based Method for Gene-Set Enrichment Visualization and Interpretation , 2010, PloS one.
[17] Ezekiel Adebiyi,et al. Clustering Algorithms: Their Application to Gene Expression Data , 2016, Bioinformatics and biology insights.
[18] Eric Jones,et al. SciPy: Open Source Scientific Tools for Python , 2001 .
[19] D. Fearon,et al. T cell exclusion, immune privilege, and the tumor microenvironment , 2015, Science.
[20] Roberto Romero,et al. A Comparison of Gene Set Analysis Methods in Terms of Sensitivity, Prioritization and Specificity , 2013, PloS one.
[21] David Tritchler,et al. Filtering Genes for Cluster and Network Analysis , 2009, BMC Bioinformatics.
[22] Mithat Gönen,et al. An efficient basket trial design , 2017, Statistics in medicine.
[23] Davis J. McCarthy,et al. Count-based differential expression analysis of RNA sequencing data using R and Bioconductor , 2013, Nature Protocols.
[24] Li Wang,et al. Corrigendum: The Serum Profile of Hypercytokinemia Factors Identified in H7N9-Infected Patients can Predict Fatal Outcomes , 2016, Scientific reports.
[25] Fernando A. Quintana,et al. Bayesian Nonparametric Data Analysis , 2015 .
[26] Mary Goldman,et al. Toil enables reproducible, open source, big biomedical data analyses , 2017, Nature Biotechnology.
[27] Matthew D. Wilkerson,et al. ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking , 2010, Bioinform..
[28] Guangchuang Yu,et al. clusterProfiler: an R package for comparing biological themes among gene clusters. , 2012, Omics : a journal of integrative biology.
[29] James C. Hu,et al. The Gene Ontology Resource: 20 years and still GOing strong , 2019 .
[30] Joel Nothman,et al. SciPy 1.0-Fundamental Algorithms for Scientific Computing in Python , 2019, ArXiv.
[31] Steven J. M. Jones,et al. The genetic landscape of high-risk neuroblastoma , 2013, Nature Genetics.
[32] D. B. Dahl. Bayesian Inference for Gene Expression and Proteomics: Model-Based Clustering for Expression Data via a Dirichlet Process Mixture Model , 2006 .
[33] R. Gentleman,et al. Independent filtering increases detection power for high-throughput experiments , 2010, Proceedings of the National Academy of Sciences.
[34] Marina Vannucci,et al. Variable selection in clustering via Dirichlet process mixture models , 2006 .
[35] T. Cai,et al. A Constrained ℓ1 Minimization Approach to Sparse Precision Matrix Estimation , 2011, 1102.2233.
[36] Mary Goldman,et al. The UCSC Xena Platform for cancer genomics data visualization and interpretation , 2018 .
[37] C. Antoniak. Mixtures of Dirichlet Processes with Applications to Bayesian Nonparametric Problems , 1974 .
[38] Fernando A. Quintana,et al. Nonparametric Bayesian data analysis , 2004 .
[39] Eswar G. Phadia. Prior Processes and Their Applications , 2013 .
[40] Justin Guinney,et al. GSVA: gene set variation analysis for microarray and RNA-Seq data , 2013, BMC Bioinformatics.
[41] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..
[42] Oliver Gautschi,et al. Aurora Kinases as Anticancer Drug Targets , 2008, Clinical Cancer Research.
[43] George Coukos,et al. Cancer immunotherapy comes of age , 2011, Nature.
[44] Gaurav Pandey,et al. Analysis of Transcriptional Variability in a Large Human iPSC Library Reveals Genetic and Non-genetic Determinants of Heterogeneity. , 2017, Cell stem cell.
[45] Gudrun Schleiermacher,et al. The challenge of defining “ultra‐high‐risk” neuroblastoma , 2018, Pediatric blood & cancer.
[46] Alex H. Wagner,et al. DGIdb 3.0: a redesign and expansion of the drug–gene interaction database , 2017, bioRxiv.
[47] Je-Keun Rhee,et al. Impact of Tumor Purity on Immune Gene Expression and Clustering Analyses across Multiple Cancer Types , 2017, Cancer Immunology Research.
[48] Pablo Tamayo,et al. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.
[49] M. Ashburner,et al. Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.
[50] T. Ferguson. A Bayesian Analysis of Some Nonparametric Problems , 1973 .
[51] Michael C. Hughes,et al. bnpy : Reliable and scalable variational inference for Bayesian nonparametric models , 2014 .
[52] Yee Whye Teh,et al. Dirichlet Process , 2017, Encyclopedia of Machine Learning and Data Mining.
[53] The Gene Ontology Consortium,et al. The Gene Ontology Resource: 20 years and still GOing strong , 2018, Nucleic Acids Res..
[54] P. Müller,et al. Bayesian inference for gene expression and proteomics , 2006 .
[55] I. Mellman,et al. Elements of cancer immunity and the cancer–immune set point , 2017, Nature.
[56] David Haussler,et al. Comparative Tumor RNA Sequencing Analysis for Difficult-to-Treat Pediatric and Young Adult Patients With Cancer , 2019, JAMA network open.
[57] C. Mackall,et al. Harnessing the Immunotherapy Revolution for the Treatment of Childhood Cancers. , 2017, Cancer cell.
[58] Olivier Delattre,et al. Chromosome instability accounts for reverse metastatic outcomes of pediatric and adult synovial sarcomas. , 2013, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[59] Carl E. Rasmussen,et al. Dirichlet Process Gaussian Mixture Models: Choice of the Base Distribution , 2010, Journal of Computer Science and Technology.
[60] Ben S. Wittner,et al. Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1 , 2009, Nature.
[61] G. Getz,et al. Inferring tumour purity and stromal and immune cell admixture from expression data , 2013, Nature Communications.
[62] David B. Dunson,et al. Bayesian Data Analysis , 2010 .
[63] David Watson,et al. M3C: A Monte Carlo reference-based consensus clustering algorithm , 2018, bioRxiv.
[64] L. Ries,et al. Cancer incidence and survival among children and adolescents: United States SEER Program 1975-1995. , 1999 .
[65] Robert Tibshirani,et al. Estimating the number of clusters in a data set via the gap statistic , 2000 .
[66] Harald Binder,et al. Transforming RNA-Seq Data to Improve the Performance of Prognostic Gene Signatures , 2014, PloS one.
[67] J. Mesirov,et al. The limitations of simple gene set enrichment analysis assuming gene independence , 2011, J. Biomed. Informatics.
[68] J. Wolchok,et al. Immune modulation in cancer with antibodies. , 2014, Annual review of medicine.
[69] Gennady Korotkevich,et al. Fast gene set enrichment analysis , 2021 .
[70] David Haussler,et al. TumorMap: Exploring the Molecular Similarities of Cancer Samples in an Interactive Portal. , 2017, Cancer research.
[71] Charlotte Soneson,et al. A comparison of methods for differential expression analysis of RNA-seq data , 2013, BMC Bioinformatics.
[72] J. Markert,et al. Checkpoint Proteins in Pediatric Brain and Extracranial Solid Tumors: Opportunities for Immunotherapy , 2016, Clinical Cancer Research.
[73] M. Daly,et al. PGC-1α-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes , 2003, Nature Genetics.
[74] W. Dik,et al. The JAK1/JAK2‐ inhibitor ruxolitinib inhibits mast cell degranulation and cytokine release , 2018, Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology.
[75] Andreas Schuppert,et al. Principal components analysis and the reported low intrinsic dimensionality of gene expression microarray data , 2016, Scientific Reports.
[76] Helga Thorvaldsdóttir,et al. Molecular signatures database (MSigDB) 3.0 , 2011, Bioinform..
[77] Edward James,et al. Antigen processing and immune regulation in the response to tumours , 2017, Immunology.