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LSTrAP-Cloud: A User-Friendly Cloud Computing Pipeline to Infer Coexpression Networks
As genomes become more and more available, gene function prediction presents itself as one of the major hurdles in our quest to extract meaningful information on the biological processes genes participate in. In order to facilitate gene function prediction, we show how our user-friendly pipeline, th...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7230309/ https://www.ncbi.nlm.nih.gov/pubmed/32316247 http://dx.doi.org/10.3390/genes11040428 |
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author | Tan, Qiao Wen Goh, William Mutwil, Marek |
author_facet | Tan, Qiao Wen Goh, William Mutwil, Marek |
author_sort | Tan, Qiao Wen |
collection | PubMed |
description | As genomes become more and more available, gene function prediction presents itself as one of the major hurdles in our quest to extract meaningful information on the biological processes genes participate in. In order to facilitate gene function prediction, we show how our user-friendly pipeline, the Large-Scale Transcriptomic Analysis Pipeline in Cloud (LSTrAP-Cloud), can be useful in helping biologists make a shortlist of genes involved in a biological process that they might be interested in, by using a single gene of interest as bait. The LSTrAP-Cloud is based on Google Colaboratory, and provides user-friendly tools that process quality-control RNA sequencing data streamed from the European Nucleotide Archive. The LSTRAP-Cloud outputs a gene coexpression network that can be used to identify functionally related genes for any organism with a sequenced genome and publicly available RNA sequencing data. Here, we used the biosynthesis pathway of Nicotiana tabacum as a case study to demonstrate how enzymes, transporters, and transcription factors involved in the synthesis, transport, and regulation of nicotine can be identified using our pipeline. |
format | Online Article Text |
id | pubmed-7230309 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-72303092020-05-22 LSTrAP-Cloud: A User-Friendly Cloud Computing Pipeline to Infer Coexpression Networks Tan, Qiao Wen Goh, William Mutwil, Marek Genes (Basel) Article As genomes become more and more available, gene function prediction presents itself as one of the major hurdles in our quest to extract meaningful information on the biological processes genes participate in. In order to facilitate gene function prediction, we show how our user-friendly pipeline, the Large-Scale Transcriptomic Analysis Pipeline in Cloud (LSTrAP-Cloud), can be useful in helping biologists make a shortlist of genes involved in a biological process that they might be interested in, by using a single gene of interest as bait. The LSTrAP-Cloud is based on Google Colaboratory, and provides user-friendly tools that process quality-control RNA sequencing data streamed from the European Nucleotide Archive. The LSTRAP-Cloud outputs a gene coexpression network that can be used to identify functionally related genes for any organism with a sequenced genome and publicly available RNA sequencing data. Here, we used the biosynthesis pathway of Nicotiana tabacum as a case study to demonstrate how enzymes, transporters, and transcription factors involved in the synthesis, transport, and regulation of nicotine can be identified using our pipeline. MDPI 2020-04-16 /pmc/articles/PMC7230309/ /pubmed/32316247 http://dx.doi.org/10.3390/genes11040428 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Tan, Qiao Wen Goh, William Mutwil, Marek LSTrAP-Cloud: A User-Friendly Cloud Computing Pipeline to Infer Coexpression Networks |
title | LSTrAP-Cloud: A User-Friendly Cloud Computing Pipeline to Infer Coexpression Networks |
title_full | LSTrAP-Cloud: A User-Friendly Cloud Computing Pipeline to Infer Coexpression Networks |
title_fullStr | LSTrAP-Cloud: A User-Friendly Cloud Computing Pipeline to Infer Coexpression Networks |
title_full_unstemmed | LSTrAP-Cloud: A User-Friendly Cloud Computing Pipeline to Infer Coexpression Networks |
title_short | LSTrAP-Cloud: A User-Friendly Cloud Computing Pipeline to Infer Coexpression Networks |
title_sort | lstrap-cloud: a user-friendly cloud computing pipeline to infer coexpression networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7230309/ https://www.ncbi.nlm.nih.gov/pubmed/32316247 http://dx.doi.org/10.3390/genes11040428 |
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