Computational deconvolution: extracting cell type-specific information from heterogeneous samples.
Shai S. Shen-Orr,Renaud Gaujoux +1 more
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TLDR
The present state of available deconvolution techniques, their advantages and limitations, are reviewed, with a focus on blood expression data and immunological studies in general.About:
This article is published in Current Opinion in Immunology.The article was published on 2013-10-01 and is currently open access. It has received 244 citations till now. The article focuses on the topics: Deconvolution.read more
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Brain Cell Type Specific Gene Expression and Co-expression Network Architectures
Andrew M. McKenzie,Minghui Wang,Mads E. Hauberg,John F. Fullard,Alexey Kozlenkov,Alexandra B Keenan,Yasmin L. Hurd,Stella Dracheva,Patrizia Casaccia,Panos Roussos,Bin Zhang +10 more
TL;DR: A set of novel brain cell consensus signatures and robust networks from the integration of multiple datasets are identified and therefore transcend limitations related to technical issues characteristic of each individual study.
Journal ArticleDOI
Quantifying tumor-infiltrating immune cells from transcriptomics data
TL;DR: In this paper, state-of-the-art computational methods for the quantification of immune cells from transcriptomics data and discuss the open challenges that must be addressed to accurately quantify immune infiltrates from RNA sequencing data of human bulk tumors.
Journal ArticleDOI
Systems Analysis of Immunity to Influenza Vaccination across Multiple Years and in Diverse Populations Reveals Shared Molecular Signatures
Helder I. Nakaya,Thomas Hagan,Sai Duraisingham,Eva K. Lee,Marcin Kwissa,Nadine Rouphael,Daniela Frasca,Merril Gersten,Aneesh K. Mehta,Renaud Gaujoux,Gui Mei Li,Shakti Gupta,Rafi Ahmed,Rafi Ahmed,Mark J. Mulligan,Shai S. Shen-Orr,Bonnie B. Blomberg,Shankar Subramaniam,Bali Pulendran,Bali Pulendran +19 more
TL;DR: These results identify shared vaccine-induced signatures across multiple seasons and in diverse populations and might help guide the development of next-generation vaccines that provide persistent immunity against influenza.
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Computational genomics tools for dissecting tumour–immune cell interactions
TL;DR: This work reviews computational genomics tools for cancer immunology and provides information on the requirements and functionality in order to assist in the selection of tools and assembly of analytical pipelines.
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Reference-free deconvolution of DNA methylation data and mediation by cell composition effects
E. Andres Houseman,Molly L. Kile,David C. Christiani,Tan A. Ince,Karl T. Kelsey,Carmen J. Marsit +5 more
TL;DR: This work proposes a simple method for reference-free deconvolution that provides both proportions of putative cell types defined by their underlying methylomes, the number of these constituent cell types, as well as a method for evaluating the extent to which the underlyingmethylomes reflect specific types of cells.
References
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Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments
TL;DR: The hierarchical model of Lonnstedt and Speed (2002) is developed into a practical approach for general microarray experiments with arbitrary numbers of treatments and RNA samples and the moderated t-statistic is shown to follow a t-distribution with augmented degrees of freedom.
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Integrated Genomic Analysis Identifies Clinically Relevant Subtypes of Glioblastoma Characterized by Abnormalities in PDGFRA, IDH1, EGFR, and NF1
Roel G.W. Verhaak,Katherine A. Hoadley,Elizabeth Purdom,Victoria Wang,Yuan-yuan Qi,Matthew D. Wilkerson,C. Ryan Miller,Li Ding,Todd R. Golub,Jill P. Mesirov,Gabriele Alexe,Michael S. Lawrence,Michael O'Kelly,Pablo Tamayo,Barbara A. Weir,Stacey Gabriel,Wendy Winckler,Supriya Gupta,Lakshmi Jakkula,Heidi S. Feiler,J. Graeme Hodgson,C. David James,Jann N. Sarkaria,Cameron Brennan,Ari B. Kahn,Paul T. Spellman,Richard K. Wilson,Terence P. Speed,Terence P. Speed,Joe W. Gray,Matthew Meyerson,Gad Getz,Charles M. Perou,Charles M. Perou,D. Neil Hayes +34 more
TL;DR: A robust gene expression-based molecular classification of GBM into Proneural, Neural, Classical, and Mesenchymal subtypes is described and multidimensional genomic data is integrated to establish patterns of somatic mutations and DNA copy number.
Integrated Genomic Analysis Identifies Clinically Relevant Subtypes of Glioblastoma Characterized by Abnormalities in PDGFRA, IDH1, EGFR, and NF1
Roel G.W. Verhaak,Katherine A. Hoadley,Elizabeth Purdom,Victoria Wang,Yuan-yuan Qi,Matthew D. Wilkerson,C. Ryan Miller,Li Ding,Todd R. Golub,Jill P. Mesirov,Gabriele Alexe,Michael S. Lawrence,Michael O'Kelly,Pablo Tamayo,Barbara A. Weir,Stacey Gabriel,Wendy Winckler,Supriya Gupta,Lakshmi Jakkula,Heidi S. Feiler,J. Graeme Hodgson,C. David James,Jann N. Sarkaria,Cameron Brennan,Ari B. Kahn,Paul T. Spellman,Richard K. Wilson,Terence P. Speed,Terence P. Speed,Joe W. Gray,Matthew Meyerson,Gad Getz,Charles M. Perou,Charles M. Perou,D. Neil Hayes +34 more
TL;DR: The Cancer Genome Atlas Network recently cataloged recurrent genomic abnormalities in glioblastoma multiforme (GBM) and proposed a robust gene expression-based molecular classification of GBM into Proneural, Neural, Classical, and Mesenchymal subtypes as discussed by the authors.
Journal ArticleDOI
Molecular signatures database (MSigDB) 3.0
Arthur Liberzon,Aravind Subramanian,Reid M. Pinchback,Helga Thorvaldsdottir,Pablo Tamayo,Jill P. Mesirov +5 more
TL;DR: A new version of the database, MSigDB 3.0, is reported, with over 6700 gene sets, a complete revision of the collection of canonical pathways and experimental signatures from publications, enhanced annotations and upgrades to the web site.
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Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1
David A. Barbie,Pablo Tamayo,Jesse S. Boehm,So Young Kim,Susan Moody,Ian F. Dunn,Anna C. Schinzel,Peter Sandy,Etienne Meylan,Claudia Scholl,Stefan Fröhling,Edmond M. Chan,Martin L. Sos,Kathrin Michel,Craig H. Mermel,Serena J. Silver,Barbara A. Weir,Jan H. Reiling,Qing Sheng,Piyush Gupta,Raymond C. Wadlow,Raymond C. Wadlow,Hanh Le,Sebastian Hoersch,Ben S. Wittner,Ben S. Wittner,Sridhar Ramaswamy,Sridhar Ramaswamy,David M. Livingston,David M. Sabatini,Matthew Meyerson,Matthew Meyerson,Roman K. Thomas,Eric S. Lander,Jill P. Mesirov,David E. Root,D. Gary Gilliland,Tyler Jacks,William C. Hahn +38 more
TL;DR: Observations indicate that TBK1 and NF-κB signalling are essential in KRAS mutant tumours, and establish a general approach for the rational identification of co-dependent pathways in cancer.