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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-04-01
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| Series: | Genes |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4425/11/4/428 |
| _version_ | 1797570450587385856 |
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| author | Qiao Wen Tan William Goh Marek Mutwil |
| author_facet | Qiao Wen Tan William Goh Marek Mutwil |
| author_sort | Qiao Wen Tan |
| collection | DOAJ |
| 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 <i>Nicotiana tabacum</i> 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. |
| first_indexed | 2024-03-10T20:25:45Z |
| format | Article |
| id | doaj.art-02ae239cf3bb4cc49889a3716f5c498e |
| institution | Directory Open Access Journal |
| issn | 2073-4425 |
| language | English |
| last_indexed | 2024-03-10T20:25:45Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Genes |
| spelling | doaj.art-02ae239cf3bb4cc49889a3716f5c498e2023-11-19T21:48:41ZengMDPI AGGenes2073-44252020-04-0111442810.3390/genes11040428LSTrAP-Cloud: A User-Friendly Cloud Computing Pipeline to Infer Coexpression NetworksQiao Wen Tan0William Goh1Marek Mutwil2School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore 637551, SingaporeSchool of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore 637551, SingaporeSchool of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore 637551, SingaporeAs 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 <i>Nicotiana tabacum</i> 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.https://www.mdpi.com/2073-4425/11/4/428cloudRNAsequencingcoexpressionmetabolism |
| spellingShingle | Qiao Wen Tan William Goh Marek Mutwil LSTrAP-Cloud: A User-Friendly Cloud Computing Pipeline to Infer Coexpression Networks Genes cloud RNA sequencing coexpression metabolism |
| 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 | cloud RNA sequencing coexpression metabolism |
| url | https://www.mdpi.com/2073-4425/11/4/428 |
| work_keys_str_mv | AT qiaowentan lstrapcloudauserfriendlycloudcomputingpipelinetoinfercoexpressionnetworks AT williamgoh lstrapcloudauserfriendlycloudcomputingpipelinetoinfercoexpressionnetworks AT marekmutwil lstrapcloudauserfriendlycloudcomputingpipelinetoinfercoexpressionnetworks |