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CReSCENT: CanceR Single Cell ExpressioN Toolkit
CReSCENT: CanceR Single Cell ExpressioN Toolkit (https://crescent.cloud), is an intuitive and scalable web portal incorporating a containerized pipeline execution engine for standardized analysis of single-cell RNA sequencing (scRNA-seq) data. While scRNA-seq data for tumour specimens are readily ge...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7319570/ https://www.ncbi.nlm.nih.gov/pubmed/32479601 http://dx.doi.org/10.1093/nar/gkaa437 |
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author | Mohanraj, Suluxan Díaz-Mejía, J Javier Pham, Martin D Elrick, Hillary Husić, Mia Rashid, Shaikh Luo, Ping Bal, Prabnur Lu, Kevin Patel, Samarth Mahalanabis, Alaina Naidas, Alaine Christensen, Erik Croucher, Danielle Richards, Laura M Shooshtari, Parisa Brudno, Michael Ramani, Arun K Pugh, Trevor J |
author_facet | Mohanraj, Suluxan Díaz-Mejía, J Javier Pham, Martin D Elrick, Hillary Husić, Mia Rashid, Shaikh Luo, Ping Bal, Prabnur Lu, Kevin Patel, Samarth Mahalanabis, Alaina Naidas, Alaine Christensen, Erik Croucher, Danielle Richards, Laura M Shooshtari, Parisa Brudno, Michael Ramani, Arun K Pugh, Trevor J |
author_sort | Mohanraj, Suluxan |
collection | PubMed |
description | CReSCENT: CanceR Single Cell ExpressioN Toolkit (https://crescent.cloud), is an intuitive and scalable web portal incorporating a containerized pipeline execution engine for standardized analysis of single-cell RNA sequencing (scRNA-seq) data. While scRNA-seq data for tumour specimens are readily generated, subsequent analysis requires high-performance computing infrastructure and user expertise to build analysis pipelines and tailor interpretation for cancer biology. CReSCENT uses public data sets and preconfigured pipelines that are accessible to computational biology non-experts and are user-editable to allow optimization, comparison, and reanalysis for specific experiments. Users can also upload their own scRNA-seq data for analysis and results can be kept private or shared with other users. |
format | Online Article Text |
id | pubmed-7319570 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-73195702020-07-01 CReSCENT: CanceR Single Cell ExpressioN Toolkit Mohanraj, Suluxan Díaz-Mejía, J Javier Pham, Martin D Elrick, Hillary Husić, Mia Rashid, Shaikh Luo, Ping Bal, Prabnur Lu, Kevin Patel, Samarth Mahalanabis, Alaina Naidas, Alaine Christensen, Erik Croucher, Danielle Richards, Laura M Shooshtari, Parisa Brudno, Michael Ramani, Arun K Pugh, Trevor J Nucleic Acids Res Web Server Issue CReSCENT: CanceR Single Cell ExpressioN Toolkit (https://crescent.cloud), is an intuitive and scalable web portal incorporating a containerized pipeline execution engine for standardized analysis of single-cell RNA sequencing (scRNA-seq) data. While scRNA-seq data for tumour specimens are readily generated, subsequent analysis requires high-performance computing infrastructure and user expertise to build analysis pipelines and tailor interpretation for cancer biology. CReSCENT uses public data sets and preconfigured pipelines that are accessible to computational biology non-experts and are user-editable to allow optimization, comparison, and reanalysis for specific experiments. Users can also upload their own scRNA-seq data for analysis and results can be kept private or shared with other users. Oxford University Press 2020-07-02 2020-06-01 /pmc/articles/PMC7319570/ /pubmed/32479601 http://dx.doi.org/10.1093/nar/gkaa437 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. 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 | Web Server Issue Mohanraj, Suluxan Díaz-Mejía, J Javier Pham, Martin D Elrick, Hillary Husić, Mia Rashid, Shaikh Luo, Ping Bal, Prabnur Lu, Kevin Patel, Samarth Mahalanabis, Alaina Naidas, Alaine Christensen, Erik Croucher, Danielle Richards, Laura M Shooshtari, Parisa Brudno, Michael Ramani, Arun K Pugh, Trevor J CReSCENT: CanceR Single Cell ExpressioN Toolkit |
title | CReSCENT: CanceR Single Cell ExpressioN Toolkit |
title_full | CReSCENT: CanceR Single Cell ExpressioN Toolkit |
title_fullStr | CReSCENT: CanceR Single Cell ExpressioN Toolkit |
title_full_unstemmed | CReSCENT: CanceR Single Cell ExpressioN Toolkit |
title_short | CReSCENT: CanceR Single Cell ExpressioN Toolkit |
title_sort | crescent: cancer single cell expression toolkit |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7319570/ https://www.ncbi.nlm.nih.gov/pubmed/32479601 http://dx.doi.org/10.1093/nar/gkaa437 |
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