CReSCENT: CanceR Single Cell ExpressioN Toolkit
Author(s) -
Suluxan Mohanraj,
J. Javier Díaz-Mejía,
Martin D. Pham,
Hillary Elrick,
Mia Husić,
Shaikh Rashid,
Ping Luo,
Prabnur Bal,
Kevin GuoKai Lu,
Samarth Patel,
Alaina Mahalanabis,
Alaine Naidas,
Erik Christensen,
Danielle Croucher,
Laura M. Richards,
Parisa Shooshtari,
Michael Brudno,
Arun Ramani,
Trevor J. Pugh
Publication year - 2020
Publication title -
nucleic acids research
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gkaa437
Subject(s) - biology , computational biology , cancer , expression (computer science) , genetics , evolutionary biology , programming language , computer science
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.
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