Package: colocboost
Type: Package
Date: 2026-06-07
Title: Multi-Context Colocalization Analysis for QTL and GWAS Studies
Version: 1.0.9
Authors@R: c(
  person(given = "Xuewei", family = "Cao", email = "xc2270@cumc.columbia.edu", role = c("cre", "aut", "cph")),
  person(given = "Haochen", family = "Sun", email = "hs3393@cumc.columbia.edu", role = c("aut", "cph")),
  person(given = "Ru", family = "Feng", email = "rf2872@cumc.columbia.edu", role = c("aut", "cph")),
  person(given = "Daniel", family = "Nachun", role = c("aut", "cph")),
  person(given = "Kushal", family = "Dey", email = "deyk@mskcc.org", role = c("aut", "cph")),
  person(given = "Gao", family = "Wang", email = "wang.gao@columbia.edu", role = c("aut", "cph"))
  )
Maintainer: Xuewei Cao <xc2270@cumc.columbia.edu>
Description: A multi-task learning approach to variable selection regression with highly correlated predictors and sparse effects, 
  based on frequentist statistical inference. It provides statistical evidence to identify which subsets of predictors have non-zero 
  effects on which subsets of response variables, motivated and designed for colocalization analysis across genome-wide association studies (GWAS)
  and quantitative trait loci (QTL) studies.
  The ColocBoost model is described in Cao et. al. (2025) <doi:10.1101/2025.04.17.25326042>.
Encoding: UTF-8
LazyDataCompression: xz
LazyData: true
RoxygenNote: 7.3.3
URL: https://github.com/StatFunGen/colocboost
BugReports: https://github.com/StatFunGen/colocboost/issues
Depends: R (>= 4.0.0)
Imports: Rfast, matrixStats
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, ashr, MASS, susieR
VignetteBuilder: knitr
Config/testthat/edition: 3
License: MIT + file LICENSE
NeedsCompilation: no
Packaged: 2026-06-07 14:30:03 UTC; xueweic
Author: Xuewei Cao [cre, aut, cph],
  Haochen Sun [aut, cph],
  Ru Feng [aut, cph],
  Daniel Nachun [aut, cph],
  Kushal Dey [aut, cph],
  Gao Wang [aut, cph]
Repository: CRAN
Date/Publication: 2026-06-08 06:40:02 UTC
Built: R 4.5.3; ; 2026-06-17 03:00:33 UTC; windows
