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FastProject: a tool for low-dimensional analysis of single-cell RNA-Seq data
BACKGROUND: A key challenge in the emerging field of single-cell RNA-Seq is to characterize phenotypic diversity between cells and visualize this information in an informative manner. A common technique when dealing with high-dimensional data is to project the data to 2 or 3 dimensions for visualiza...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4995760/ https://www.ncbi.nlm.nih.gov/pubmed/27553427 http://dx.doi.org/10.1186/s12859-016-1176-5 |
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author | DeTomaso, David Yosef, Nir |
author_facet | DeTomaso, David Yosef, Nir |
author_sort | DeTomaso, David |
collection | PubMed |
description | BACKGROUND: A key challenge in the emerging field of single-cell RNA-Seq is to characterize phenotypic diversity between cells and visualize this information in an informative manner. A common technique when dealing with high-dimensional data is to project the data to 2 or 3 dimensions for visualization. However, there are a variety of methods to achieve this result and once projected, it can be difficult to ascribe biological significance to the observed features. Additionally, when analyzing single-cell data, the relationship between cells can be obscured by technical confounders such as variable gene capture rates. RESULTS: To aid in the analysis and interpretation of single-cell RNA-Seq data, we have developed FastProject, a software tool which analyzes a gene expression matrix and produces a dynamic output report in which two-dimensional projections of the data can be explored. Annotated gene sets (referred to as gene ‘signatures’) are incorporated so that features in the projections can be understood in relation to the biological processes they might represent. FastProject provides a novel method of scoring each cell against a gene signature so as to minimize the effect of missed transcripts as well as a method to rank signature-projection pairings so that meaningful associations can be quickly identified. Additionally, FastProject is written with a modular architecture and designed to serve as a platform for incorporating and comparing new projection methods and gene selection algorithms. CONCLUSIONS: Here we present FastProject, a software package for two-dimensional visualization of single cell data, which utilizes a plethora of projection methods and provides a way to systematically investigate the biological relevance of these low dimensional representations by incorporating domain knowledge. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1176-5) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4995760 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-49957602016-09-06 FastProject: a tool for low-dimensional analysis of single-cell RNA-Seq data DeTomaso, David Yosef, Nir BMC Bioinformatics Software BACKGROUND: A key challenge in the emerging field of single-cell RNA-Seq is to characterize phenotypic diversity between cells and visualize this information in an informative manner. A common technique when dealing with high-dimensional data is to project the data to 2 or 3 dimensions for visualization. However, there are a variety of methods to achieve this result and once projected, it can be difficult to ascribe biological significance to the observed features. Additionally, when analyzing single-cell data, the relationship between cells can be obscured by technical confounders such as variable gene capture rates. RESULTS: To aid in the analysis and interpretation of single-cell RNA-Seq data, we have developed FastProject, a software tool which analyzes a gene expression matrix and produces a dynamic output report in which two-dimensional projections of the data can be explored. Annotated gene sets (referred to as gene ‘signatures’) are incorporated so that features in the projections can be understood in relation to the biological processes they might represent. FastProject provides a novel method of scoring each cell against a gene signature so as to minimize the effect of missed transcripts as well as a method to rank signature-projection pairings so that meaningful associations can be quickly identified. Additionally, FastProject is written with a modular architecture and designed to serve as a platform for incorporating and comparing new projection methods and gene selection algorithms. CONCLUSIONS: Here we present FastProject, a software package for two-dimensional visualization of single cell data, which utilizes a plethora of projection methods and provides a way to systematically investigate the biological relevance of these low dimensional representations by incorporating domain knowledge. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1176-5) contains supplementary material, which is available to authorized users. BioMed Central 2016-08-23 /pmc/articles/PMC4995760/ /pubmed/27553427 http://dx.doi.org/10.1186/s12859-016-1176-5 Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Software DeTomaso, David Yosef, Nir FastProject: a tool for low-dimensional analysis of single-cell RNA-Seq data |
title | FastProject: a tool for low-dimensional analysis of single-cell RNA-Seq data |
title_full | FastProject: a tool for low-dimensional analysis of single-cell RNA-Seq data |
title_fullStr | FastProject: a tool for low-dimensional analysis of single-cell RNA-Seq data |
title_full_unstemmed | FastProject: a tool for low-dimensional analysis of single-cell RNA-Seq data |
title_short | FastProject: a tool for low-dimensional analysis of single-cell RNA-Seq data |
title_sort | fastproject: a tool for low-dimensional analysis of single-cell rna-seq data |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4995760/ https://www.ncbi.nlm.nih.gov/pubmed/27553427 http://dx.doi.org/10.1186/s12859-016-1176-5 |
work_keys_str_mv | AT detomasodavid fastprojectatoolforlowdimensionalanalysisofsinglecellrnaseqdata AT yosefnir fastprojectatoolforlowdimensionalanalysisofsinglecellrnaseqdata |