LSTrAP-Cloud: A User-friendly Cloud Computing Pipeline to Infer Co-functional and Regulatory Networks
| Autor: | William Goh, Marek Mutwil, Qiao Wen Tan |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
chemistry.chemical_classification
Computer science Process (engineering) business.industry RNA food and beverages Cloud computing Computational biology Genome Pipeline (software) Transcriptome chemistry.chemical_compound Enzyme Biosynthesis chemistry business Gene Transcription factor Organism Function (biology) |
| DOI: | 10.1101/2020.03.11.986794 |
| Popis: | 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, Large-Scale Transcriptomic Analysis Pipeline in Cloud (LSTrAP-Cloud), can be useful in helping biologists make a shortlist of genes that they might be interested in. LSTrAP-Cloud is based on Google Colaboratory and provides user-friendly tools that process and quality-control RNA sequencing data streamed from the European Sequencing Archive. LSTRAP-Cloud outputs a gene co-expression 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. |
| Databáze: | OpenAIRE |
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