voom: precision weights unlock linear model analysis tools for RNA-seq read counts
Charity W. Law,Charity W. Law,Yunshun Chen,Yunshun Chen,Wei Shi,Wei Shi,Gordon K. Smyth,Gordon K. Smyth +7 more
TLDR
New normal linear modeling strategies are presented for analyzing read counts from RNA-seq experiments, and the voom method estimates the mean-variance relationship of the log-counts, generates a precision weight for each observation and enters these into the limma empirical Bayes analysis pipeline.Abstract:Â
New normal linear modeling strategies are presented for analyzing read counts from RNA-seq experiments. The voom method estimates the mean-variance relationship of the log-counts, generates a precision weight for each observation and enters these into the limma empirical Bayes analysis pipeline. This opens access for RNA-seq analysts to a large body of methodology developed for microarrays. Simulation studies show that voom performs as well or better than count-based RNA-seq methods even when the data are generated according to the assumptions of the earlier methods. Two case studies illustrate the use of linear modeling and gene set testing methods.read more
Citations
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RNAontheBENCH: computational and empirical resources for benchmarking RNAseq quantification and differential expression methods
Pierre-Luc Germain,Alessandro Vitriolo,Antonio Adamo,Pasquale Laise,Vivek Das,Giuseppe Testa,Giuseppe Testa +6 more
TL;DR: It is shown that methods providing the best absolute quantification do not necessarily provide goodrelative quantification across samples, that count-based methods are superior for gene-level relative quantification, and that the new generation of pseudo-alignment-based software performs as well as established methods, at a fraction of the computing time.
Journal ArticleDOI
Genomics pipelines and data integration: challenges and opportunities in the research setting
Jeremy Davis-Turak,Sean M. Courtney,E. Starr Hazard,W. Bailey Glen,Willian A. da Silveira,Timothy Wesselman,Larry P. Harbin,Bethany J. Wolf,Dongjun Chung,Gary Hardiman +9 more
TL;DR: The authors review the challenges associated with implementing bioinformatics best practices in a large-scale setting, and highlight the opportunity for establishing bioInformatics pipelines that incorporate data tracking and auditing, enabling greater consistency and reproducibility for basic research, translational or clinical settings.
Journal ArticleDOI
Multi-omics analysis identifies therapeutic vulnerabilities in triple-negative breast cancer subtypes.
Brian D. Lehmann,Antonio Colaprico,Tiago C. Silva,Jianjiao Chen,Hanbing An,Yuguang Ban,Hanchen Huang,Lily Wang,Jamaal L. James,Justin M. Balko,Paula I. Gonzalez-Ericsson,Melinda E. Sanders,Bing Zhang,Jennifer A. Pietenpol,Jennifer A. Pietenpol,X. Steven Chen +15 more
TL;DR: In this paper, a comprehensive analysis of mutation, copy number, transcriptomic, epigenetic, proteomic, and phospho-proteomic patterns of triple negative breast cancer (TNBC) subtypes is presented.
Journal ArticleDOI
Repression of Igf1 expression by Ezh2 prevents basal cell differentiation in the developing lung
Laura A. Galvis,Aliaksei Holik,Kieran M. Short,Julie Pasquet,Aaron T. L. Lun,Marnie E. Blewitt,Ian M. Smyth,Matthew E. Ritchie,Marie Liesse Asselin-Labat,Marie Liesse Asselin-Labat +9 more
TL;DR: It is found that loss of Ezh2 de-represses insulin-like growth factor 1 (Igf1) expression and that modulation of IGF1 signaling ex vivo in wild-type lungs could induce basal cell differentiation.
Journal ArticleDOI
Attenuation of TCR-induced transcription by Bach2 controls regulatory T cell differentiation and homeostasis.
Tom Sidwell,Tom Sidwell,Yang Liao,Yang Liao,Alexandra L. Garnham,Alexandra L. Garnham,Ajithkumar Vasanthakumar,Ajithkumar Vasanthakumar,Renee Gloury,Renee Gloury,Jonas Blume,Jonas Blume,Peggy P Teh,David Chisanga,David Chisanga,Christoph Thelemann,Fabian de Labastida Rivera,Christian R. Engwerda,Lynn M. Corcoran,Lynn M. Corcoran,Kohei Kometani,Tomohiro Kurosaki,Gordon K. Smyth,Gordon K. Smyth,Wei Shi,Wei Shi,Axel Kallies,Axel Kallies +27 more
TL;DR: The authors use a Treg-specific mouse model to show that Bach2 controls homeostasis and function of Treg cells by limiting DNA accessibility and activity of IRF4 in response to TCR signaling.
References
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