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:
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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The landscape of molecular chaperones across human tissues reveals a layered architecture of core and variable chaperones.
Netta Shemesh,Juman Jubran,Shiran Dror,Eyal Simonovsky,Omer Basha,Chanan M Argov,Idan Hekselman,Mehtap Abu-Qarn,Ekaterina Vinogradov,Omry Mauer,Tatiana Tiago,Serena Carra,Anat Ben-Zvi,Esti Yeger-Lotem +13 more
TL;DR: In this article, the chaperone system is composed of core elements that are uniformly expressed across tissues, and variable elements that were differentially expressed to fit with tissue-specific requirements.
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Multimodal Meta-Analysis of 1,494 Hepatocellular Carcinoma Samples Reveals Significant Impact of Consensus Driver Genes on Phenotypes.
Kumardeep Chaudhary,Olivier Poirion,Liangqun Lu,Liangqun Lu,Sijia Huang,Sijia Huang,Travers Ching,Travers Ching,Lana X. Garmire,Lana X. Garmire +9 more
TL;DR: A group of consensus drivers in HCC are identified, which collectively show vast impacts on the phenotypes and may warrant as valuable therapeutic targets of HCC.
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Cancer Cells Employ Nuclear Caspase-8 to Overcome the p53-Dependent G2/M Checkpoint through Cleavage of USP28
Ines Müller,Elwira Strozyk,Sebastian Schindler,Stefan Beissert,Htoo Zarni Oo,Htoo Zarni Oo,Thomas Sauter,Philippe Lucarelli,Sebastian Raeth,Angelika Hausser,Nader Al Nakouzi,Nader Al Nakouzi,Ladan Fazli,Ladan Fazli,Martin E. Gleave,Martin E. Gleave,He Liu,Hans-Uwe Simon,Henning Walczak,Douglas R. Green,Jiri Bartek,Mads Daugaard,Mads Daugaard,Dagmar Kulms +23 more
TL;DR: It is shown that tumor cells employ DNA-damage-induced nuclear caspase-8 to override the p53-dependent G2/M cell-cycle checkpoint, switching cell fate from apoptosis toward mitosis.
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Transcriptomic profiling of the myeloma bone-lining niche reveals BMP signalling inhibition to improve bone disease
Sarah Gooding,Sam W. Z. Olechnowicz,Emma V. Morris,Andrew E. Armitage,João Arezes,Joe N. Frost,Emmanouela Repapi,James R. Edwards,Neil Ashley,C Waugh,Nicola Gray,Erik Martinez-Hackert,Pei Jin Lim,Sant-Rayn Pasricha,Helen J Knowles,Adam J. Mead,Karthik Ramasamy,Hal Drakesmith,Claire M. Edwards +18 more
TL;DR: A novel role for the BMP pathway in myeloma-induced bone disease that can be therapeutically targeted is described and a targetable role of bone morphogenetic protein (BMP) signalling is found.
Journal ArticleDOI
Sphingolipids, Transcription Factors, and Conserved Toolkit Genes: Developmental Plasticity in the Ant Cardiocondyla obscurior
TL;DR: It is found that different transcription factors and functionally distinct sets of genes are recruited during larval development to induce the four alternative trajectories of sphingolipid metabolism, a conserved molecular pathway involved in development, obesity, and aging.
References
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Journal ArticleDOI
Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles
Aravind Subramanian,Pablo Tamayo,Vamsi K. Mootha,Sayan Mukherjee,Benjamin L. Ebert,Michael A. Gillette,Amanda G. Paulovich,Scott L. Pomeroy,Todd R. Golub,Eric S. Lander,Jill P. Mesirov +10 more
TL;DR: The Gene Set Enrichment Analysis (GSEA) method as discussed by the authors focuses on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation.
Journal ArticleDOI
edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.
TL;DR: EdgeR as mentioned in this paper is a Bioconductor software package for examining differential expression of replicated count data, which uses an overdispersed Poisson model to account for both biological and technical variability and empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference.
Book
Generalized Linear Models
Peter McCullagh,John A. Nelder +1 more
TL;DR: In this paper, a generalization of the analysis of variance is given for these models using log- likelihoods, illustrated by examples relating to four distributions; the Normal, Binomial (probit analysis, etc.), Poisson (contingency tables), and gamma (variance components).
Journal ArticleDOI
featureCounts: an efficient general-purpose program for assigning sequence reads to genomic features
TL;DR: FeatureCounts as discussed by the authors is a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments, which implements highly efficient chromosome hashing and feature blocking techniques.
Journal ArticleDOI
Differential expression analysis for sequence count data.
Simon Anders,Wolfgang Huber +1 more
TL;DR: A method based on the negative binomial distribution, with variance and mean linked by local regression, is proposed and an implementation, DESeq, as an R/Bioconductor package is presented.