Cargando…
ImmQuant: a user-friendly tool for inferring immune cell-type composition from gene-expression data
Summary: 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 allowi...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5167062/ https://www.ncbi.nlm.nih.gov/pubmed/27531105 http://dx.doi.org/10.1093/bioinformatics/btw535 |
_version_ | 1782483129324273664 |
---|---|
author | Frishberg, Amit Brodt, Avital Steuerman, Yael Gat-Viks, Irit |
author_facet | Frishberg, Amit Brodt, Avital Steuerman, Yael Gat-Viks, Irit |
author_sort | Frishberg, Amit |
collection | PubMed |
description | Summary: 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. Availability and implementation: ImmQuant is available for download at http://csgi.tau.ac.il/ImmQuant/. Contact: iritgv@post.tau.ac.il Supplementary information: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-5167062 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-51670622016-12-20 ImmQuant: a user-friendly tool for inferring immune cell-type composition from gene-expression data Frishberg, Amit Brodt, Avital Steuerman, Yael Gat-Viks, Irit Bioinformatics Applications Notes Summary: 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. Availability and implementation: ImmQuant is available for download at http://csgi.tau.ac.il/ImmQuant/. Contact: iritgv@post.tau.ac.il Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2016-12-15 2016-08-16 /pmc/articles/PMC5167062/ /pubmed/27531105 http://dx.doi.org/10.1093/bioinformatics/btw535 Text en © The Author 2016. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Frishberg, Amit Brodt, Avital Steuerman, Yael Gat-Viks, Irit ImmQuant: a user-friendly tool for inferring immune cell-type composition from gene-expression data |
title | ImmQuant: a user-friendly tool for inferring immune cell-type composition from gene-expression data |
title_full | ImmQuant: a user-friendly tool for inferring immune cell-type composition from gene-expression data |
title_fullStr | ImmQuant: a user-friendly tool for inferring immune cell-type composition from gene-expression data |
title_full_unstemmed | ImmQuant: a user-friendly tool for inferring immune cell-type composition from gene-expression data |
title_short | ImmQuant: a user-friendly tool for inferring immune cell-type composition from gene-expression data |
title_sort | immquant: a user-friendly tool for inferring immune cell-type composition from gene-expression data |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5167062/ https://www.ncbi.nlm.nih.gov/pubmed/27531105 http://dx.doi.org/10.1093/bioinformatics/btw535 |
work_keys_str_mv | AT frishbergamit immquantauserfriendlytoolforinferringimmunecelltypecompositionfromgeneexpressiondata AT brodtavital immquantauserfriendlytoolforinferringimmunecelltypecompositionfromgeneexpressiondata AT steuermanyael immquantauserfriendlytoolforinferringimmunecelltypecompositionfromgeneexpressiondata AT gatviksirit immquantauserfriendlytoolforinferringimmunecelltypecompositionfromgeneexpressiondata |