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Computational deconvolution: extracting cell type-specific information from heterogeneous samples.

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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.
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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.

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Methods and systems for determining proportions of distinct cell subsets

TL;DR: In this paper, a regression between a feature profile of a first plurality of distinct components and a reference matrix of feature signatures for a second plurality of different components is used to deconvolution.
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Polled Digital Cell Sorter (p-DCS): Automatic identification of hematological cell types from single cell RNA-sequencing clusters

TL;DR: A computational tool for processing single cell RNA-seq data that uses a voting algorithm to identify cells based on approval votes received by known molecular markers and automatically assigns a cell type to clusters without an expert curator is presented.
Journal ArticleDOI

Unraveling patterns of disrupted gene expression across a complex tissue

TL;DR: In this paper , the effects of different cellular composition on whole tissue expression profiles were investigated, and it was shown that differences in cellular composition between tissues can modify expression profiles, potentially altering inferred gene ontological processes and insights into gene network evolution.
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Epigenetic changes with age primes mammary luminal epithelia for cancer initiation

TL;DR: In this paper, the authors found that the epigenomic and DNA methylation changes were robust indicators of aging luminal cells, and were either directly correlated with expression changes or served as priming events for subsequent dysregulation, such as demethylation of ESR1-binding regions in DNAm-regulatory CXXC5.
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Whole-Tissue Deconvolution and scRNAseq Analysis Identify Altered Endometrial Cellular Compositions and Functionality Associated With Endometriosis

TL;DR: In this paper , the authors comprehensively characterized immune and non-immune cell types in the endometrium of women with or without disease and their dynamic changes across the menstrual cycle through integrating whole-tissue deconvolution and single-cell RNAseq.
References
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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

Molecular signatures database (MSigDB) 3.0

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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