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Evaluation of Simultaneous Inference Methods for the Human Genome.

Home Page: http://chrisbcole.me/coRge/

License: Apache License 2.0

Shell 3.23% R 74.13% Makefile 3.03% C++ 19.61%
genetics high-performance-computing multiple-testing-correction simulation

corge's Introduction

Hi there, I'm Chris.

I am currently a lead scientist at Deep Genomics in Toronto. My work involves using machine learning and AI to identify causal drug targets from human genetics data. I previously completed my DPhil working with Gerton Lunter and Thomas Milne at the University of Oxford. Check out my website for a breakdown of previous projects and repositories of interest.

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corge's Issues

Issues Remaining

January 12 Meeting

  • The clusters aren't obviously separable, so maybe add as a third dimension a density peak to see if the groups really are different in the following:

  • Incorporate true positive gradient instead of absolute number of TPs
  • Sweep over concentrations for cluster enrichment
  • UK10K Data access

Sub Script function

  • Create cluster submission script within inst/bash
  • Create wrapped function for sub so don't have to leave R, ie
if(!require(pacman)) install.packages("pacman", repos = uT)
p_load(foreach, SnowMC)

install_github("Chris1221", "coRge")

uT = cran repo
foreach(i = 1:10) %:% foreach(j = 1:10) %do% sub(i,j) #from within interactive session

Add in gene "mode"

Mode arguement must be changed in analyze.R along with correct.R and stratify.R.

Another option would be to harmonize the entire function, but I don't think I have the time right now.

Circumvent need for coRge::gen2r()

This is way too long, maybe create a vector with three entries for each es and simply multiply the matrices. This has to be faster. Have to make sure that 0*x = 0 and that the 0s don't contribute to rowsums. they shouldn't but just make sure.

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