ImMquant: A user-friendly tool for inferring immune cell-type composition from gene-expression data

Amit Frishberg; Avital Brodt; Yael Steuerman; Irit Gat-Viks

doi:10.1093/bioinformatics/btw535

ImMquant: A user-friendly tool for inferring immune cell-type composition from gene-expression data

Amit Frishberg, Avital Brodt, Yael Steuerman, Irit Gat-Viks^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

The composition of immune-cell subsets is key to the understanding of major diseases and pathologies. Computational deconvolution methods enable researchers to investigate immune cell quantities in complex tissues based on transcriptome data. Here we present ImmQuant, a software tool allowing immunologists to upload transcription profiles of multiple tissue samples, apply deconvolution methodology to predict differences in cell-type quantities between the samples, and then inspect the inferred cell-type alterations using convenient visualization tools. ImmQuant builds on the DCQ deconvolution algorithm and allows a user-friendly utilization of this method by non-bioinformatician researchers. Specifically, it enables investigation of hundreds of immune cell subsets in mouse tissues, as well as a few dozen cell types in human samples.

Original language	English
Pages (from-to)	3842-3843
Number of pages	2
Journal	Bioinformatics
Volume	32
Issue number	24
DOIs	https://doi.org/10.1093/bioinformatics/btw535
State	Published - 15 Dec 2016

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10.1093/bioinformatics/btw535

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ImMquant: A user-friendly tool for inferring immune cell-type composition from gene-expression data

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