u-brite / snvariome Goto Github PK

• Find geneset enrichment analysis (enrichR) to incorporate into our shiny app
• Use the below genes in those tools to start writing code and functions to be used in our shiny app

BPIFA1
SCGB2A1
MUC5B
PRR4
BPIFB1
ZG16B
ANXA1
IRS1
APOA1
LTF
PIGR
PIP
NTC1
NTC2
PTEN
PIK3R1
PIK3CA

• Determine what data is accessible via API - @MariaJose501
• Determine how API will be used within the shiny app.

We'll integrate:

• GTEx Tissue-Specific Age Group Signatures
• LINCS L1000 Ligand Perturbations (2021)
• LINCS L1000 Chemical Perturbations Consensus Signatures
• SIgnature search by gene, disease

View at https://maayanlab.cloud/sigcom-lincs/#/

• ClinVar API
• Others?

• Use shiny's ui editor
• Discuss with team what layouts would be appropriate
• Look at existing shiny apps to generate ideas

• STRING
  • See https://www.sciencedirect.com/science/article/pii/S2589004220307185?via%3Dihub for methods and datasets integrated.
  • Human Interactome I and II, BioPlex, QUBIC, and CoFrac
• How will we access these (API) and are there challenges?

• Does rShiny now have a way to do develop documentation?
• What documentation should we use (readthedocs, pkgdown)?
• Complete documentation - @swiss-made

We want to see that our method encompasses well-curated and validated disease-causing or pathogenic genes/variants.

• Build method using R
• Incorporate gain of function/loss of function information
• Integrate method with databases/apis

• Jetstream2
• shinyapps.io
• Show locally during the presentation?