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GeneExpression

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Ben Busby edited this page Apr 5, 2020 · 68 revisions

Main Objective

We want to perform RNAseq-based analyses on published datasets in order to better understand the interaction between human host and virus.

Skills needed

Bioinformatics in general, NGS analysis (bulk, viral, sRNA, scRNA), Biostatistics, Biology, Virology, everyone is welcome!

Deliverables

Biological: Perform a global RNA-Seq analysis with SARS-CoV-2 infected datasets to search for new candidate genes for testing experimentally

Methodological: Create a packaged reproducible pipeline in Dockers to help scientists to easily treat their RNA-Seq data and for us if any new dataset comes out

Workflow

1. Viral infection global analyses:

  • RNAseq analysis to select differentially expressed genes
  • Isoform differential expression
  • Map RNAseq to virus genomes
  • Functional and enrichment analyses
  • Search for global regulators

2. Human-virus interaction analyses:

  • Which human proteins interact or are regulating the virus and vice-versa?
  • Are there human RNA-binding proteins potentially regulating the viral genome?
  • Include these in subsequent analyses

3. Increased risk factors analyses:

  • Select datasets from co-morbidities related to severeness of Covid-19 For instance, diseases such as diabetes myelitus and hypertension; other factors like smoking, which might make the person more vulnerable to the virus;
  • Select other human tissues to check the expression of proteins interacting with the virus (selected in previous step)
  • Search for SNPs, splicing variants, regulatory regions for all genes selected in previous steps
  • Analysis of HLA types that predispose individuals and populations to COVID-19 infection and mortality (starting at http://hlacovid19.org/

4. Towards the control of gene expression:

  • Are there any known drugs or other factors that might regulate the expression of these selected genes? In this section we can also communicate with #htvs (Virtual Screening) as they “will use target binding of the crystal structure of the viral protease with potential inhibitors”, so maybe there is room for collaborating their pipeline on human proteins as well?

Initial work: https://amp.pharm.mssm.edu/covid19/

5. Reporting findings to electronic medical records:

  • How do we get RNAseq findings into the hands of clinicians in both the immediate and longer (chronic disease) term?

Initial work: https://github.com/NCBI-Codeathons/omopomics -- working with OHDSI

Communication channel

Resources that might be helpful:

(Please add more here!)

https://github.com/NCBI-Codeathons/ViraVate

Perhaps future collab with these folks: https://www.hackseq.com/rna

Participants

(Feel free to add your name)

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