Computational deconvolution: extracting cell type-specific information from heterogeneous samples.
Shai S. Shen-Orr,Renaud Gaujoux +1 more
Reads0
Chats0
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
Citations
More filters
Journal ArticleDOI
Post‐modified non‐negative matrix factorization for deconvoluting the gene expression profiles of specific cell types from heterogeneous clinical samples based on RNA‐sequencing data
TL;DR: Post‐modified non‐negative matrix factorization (NMF), the unsupervised algorithm, is capable of estimating the gene expression profiles and contents of the major cell types in cancer samples without any prior reference knowledge and can efficiently extract the genes of specific cell types from heterogeneous samples for subsequent analysis and prediction.
Journal ArticleDOI
DNA methylation signatures of childhood trauma predict psychiatric disorders and other adverse outcomes 17 years after exposure
Charlie L. J. D. van den Oord,William E. Copeland,Min Zhao,Lingling Xie,Karolina A. Aberg,Edwin Cgj van den Oord +5 more
TL;DR: In this article , a prospective longitudinal study was conducted to predict psychiatric disorders and other adverse outcomes from trauma-related methylation changes 16.9 years after trauma exposure in childhood using a sequencing-based approach that provides near-complete coverage of all 28 million sites in the blood methylome.
Journal ArticleDOI
Quantitative analysis of the blood transcriptome of young healthy pigs and its relationship with subsequent disease resilience.
Kyu-Sang Lim,Jian Cheng,Austin M. Putz,Qian Dong,Qian Dong,Xuechun Bai,Hamid Beiki,Christopher K. Tuggle,Michael K. Dyck,Pig Gen Canada,Frederic Fortin,John C. S. Harding,Graham Plastow,Jack C. M. Dekkers +13 more
TL;DR: In this paper, the authors investigate population-level gene expression profiles in the blood of 912 healthy F1 barrows at ~ 27 days of age for associations with performance and health before and after their exposure to a natural polymicrobial disease challenge.
Journal ArticleDOI
Modeling population heterogeneity from microbial communities to immune response in cells
TL;DR: This review presents a broad overview of the experimental developments that allowed observing heterogeneity at the single cell level, and highlights how this “data revolution” requires the parallel advancement of algorithms and computing infrastructure for data processing and analysis.
Journal ArticleDOI
Vec2image: an explainable artificial intelligence model for the feature representation and classification of high-dimensional biological data by vector-to-image conversion
TL;DR: Vec2image is an explainable convolutional neural network framework for characterizing the feature engineering, feature selection and classifier training that is mainly based on the collaboration of principal component coordinate conversion, deep residual neural networks and embedded k-nearest neighbor representation on pseudo images of high-dimensional biological data.
References
More filters
Journal ArticleDOI
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.
Journal ArticleDOI
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.
Journal ArticleDOI
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.