update Apr13

.Rbuildignore

@@ -16,3 +16,4 @@
 ^\.pixi
 ^cran-comments\.md$
 ^LICENSE\.md$
+^README\.md$

.github/environment/pixi.toml

@@ -10,7 +10,8 @@ libc = { family="glibc", version="2.17" }
 devtools_document = "R -e 'devtools::document()'"
 devtools_test = "R -e 'devtools::test()'"
 codecov = "R -e 'covr::codecov(quiet = FALSE)'"
-rcmdcheck = "R -e 'rcmdcheck::rcmdcheck()'"
+build = "R -e 'devtools::build()'"
+rcmdcheck = "R -e 'pkg <- list.files(\"..\", pattern = \".tar.gz\", full.names = TRUE); rcmdcheck::rcmdcheck(path = pkg[1], args = c(\"--as-cran\", \"--no-manual\"))'"
 use_major_version = "R -e 'usethis::Use_version(which = \"major\", push = FALSE)'"
 use_minor_version = "R -e 'usethis::use_version(which = \"minor\", push = FALSE)'"
 use_patch_version = "R -e 'usethis::use_version(which = \"patch\", push = FALSE)'"
@@ -26,7 +27,9 @@ r43 = {features = ["r43"]}
 r44 = {features = ["r44"]}
 
 [dependencies]
+"r-ashr" = "*"
+"r-covr" = "*"
 "r-devtools" = "*"
+"r-mass" = "*"
 "r-rcmdcheck" = "*"
-"r-covr" = "*"
 "r-tidyverse" = "*"

.github/workflows/ci.yml

@@ -33,11 +33,16 @@ jobs:
       - name: Run unit tests
         run: pixi run --environment ${{ matrix.environment }} devtools_test
 
-      # - name: Check unit test code coverage
-      #   run: pixi run --environment ${{ matrix.environment }} codecov
+      - name: Run R CMD CHECK
+        run: |
+          pixi install --environment ${{ matrix.environment }}
+          ln -sf $(pwd)/.pixi/envs/default/lib/libhwasan.so.0 $(pwd)/.pixi/envs/default/lib/libhwasan.so
+          ln -sf $(pwd)/.pixi/envs/${{ matrix.environment }}/lib/libhwasan.so.0 $(pwd)/.pixi/envs/${{ matrix.environment }}/lib/libhwasan.so
+          pixi run --environment ${{ matrix.environment }} build
+          pixi run --environment ${{ matrix.environment }} rcmdcheck
 
-      #- name: Run R CMD CHECK
-        #run: pixi run rcmdcheck
+      - name: Check unit test code coverage
+        run: pixi run --environment ${{ matrix.environment }} codecov
 
   ci_osx-64:
     name: osx-64 CI
@@ -62,8 +67,10 @@ jobs:
       - name: Run unit tests
         run: pixi run --environment ${{ matrix.environment }} devtools_test
 
-      #- name: Run R CMD CHECK
-        #run: pixi run rcmdcheck
+      - name: Run R CMD CHECK
+        run: |
+          pixi run --environment ${{ matrix.environment }} build
+          pixi run --environment ${{ matrix.environment }} rcmdcheck
 
   ci_osx-arm64:
     name: osx-arm64 CI
@@ -88,5 +95,7 @@ jobs:
       - name: Run unit tests
         run: pixi run --environment ${{ matrix.environment }} devtools_test
 
-      #- name: Run R CMD CHECK
-        #run: pixi run rcmdcheck
+      - name: Run R CMD CHECK
+        run: |
+          pixi run --environment ${{ matrix.environment }} build
+          pixi run --environment ${{ matrix.environment }} rcmdcheck

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: colocboost
 Type: Package
-Date: 2024-09-01
+Date: 2025-04-13
 Title: Multi-Context Colocalization Analysis Tool for Molecular QTL and GWAS Studies
 Version: 0.1.0
 Authors@R: c(
@@ -28,8 +28,8 @@ Suggests:
     testthat (>= 3.0.0),
     knitr,
     rmarkdown,
-    susieR,
-    ashr
+    ashr,
+    MASS
 VignetteBuilder: knitr
 Roxygen: list(markdown = TRUE)
 Config/testthat/edition: 3

R/colocboost.R

@@ -13,7 +13,6 @@
 #' (default is 0.8) but within the same locus. This step addresses potential instabilities in linkage disequilibrium (LD) estimation
 #' that may arise from small sample sizes or discrepancies in minor allele frequencies (MAF) across different confidence sets.
 #'
-#' @section Input Data:
 #' @param X A list of genotype matrices for different outcomes, or a single matrix if all outcomes share the same genotypes.
 #'          Each matrix should have column names, if sample sizes and variables possibly differing across matrices.
 #' @param Y A list of vectors of outcomes or an N by L matrix if it is considered for the same X and multiple outcomes.
@@ -40,7 +39,6 @@
 #' @param effect_se Matrix of standard errors associated with the beta values
 #' @param effect_n A scalar or a vector of sample sizes for estimating regression coefficients. Highly recommended!
 #' 
-#' @section Model Parameters
 #' @param M The maximum number of gradient boosting rounds. If the number of outcomes are large, it will be automatically increased to a larger number.
 #' @param stop_thresh The stop criterion for overall profile loglikelihood function.
 #' @param tau The smooth parameter for proximity adaptive smoothing weights for the best update jk-star.
@@ -64,7 +62,6 @@
 #' @param p.adjust.methods The adjusted pvalue method in stats:p.adj  when \code{func_multi_test = "fdr"}
 #' @param residual_correlation The residual correlation based on the sample overlap, it is diagonal if it is NULL.
 #' 
-#' @section Post Inference Parameters
 #' @param coverage A number between 0 and 1 specifying the \dQuote{coverage} of the estimated colocalization confidence sets (CoS) (default is 0.95).
 #' @param min_cluster_corr The small correlation for the weights distributions across different iterations to be decided having only one cluster.
 #' @param dedup If \code{dedup = TRUE}, the duplicate confidence sets will be removed in the post-processing.

R/colocboost_init.R

@@ -571,5 +571,3 @@ get_multiple_correction <- function(z, miss_idx = NULL, func_multi_test = "lfdr"
     }
 
 }
-
-

README.md

@@ -1,14 +1,77 @@
-# ColocBoost for multi-context colocalization in molecular QTL and GWAS studies
+# ColocBoost for multi-trait colocalization in molecular QTL and GWAS studies
 [![Codecov test coverage](https://codecov.io/gh/StatFunGen/colocboost/branch/master/graph/badge.svg)](https://codecov.io/gh/StatFunGen/colocboost?branch=master)
+[![CRAN Version](https://www.r-pkg.org/badges/version/colocboost)](https://cran.r-project.org/package=colocboost)
 
 This R package implements ColocBoost --- motivated and designed for colocalization analysis ([first formulated here](https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1004383)) of multiple genetic association studies --- as 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.
 
-Temporary usage before our cran or conda release
-- clone the repo to your local folder, then
+## Installation
+
+### Conda
+Install major releases from conda (recommended)
+
 ```bash
-cd colocboost
-R --slave -e "devtools::install()"
+conda install -c dnachun r-colocboost
+```
+
+### CRAN
+Install released versions from cran
+
+```r
+install.packages("colocboost")
+```
+
+### GitHub
+Install the development version from GitHub
+
+```r
+devtools::install_github("StatFunGen/colocboost")
+```
+
+## Usage
+
+### Single-trait Fine-mapping (FineBoost)
+Run FineBoost for single-trait fine-mapping (similar interface to SuSiE)
+```r
+result <- colocboost(X=X, Y=y)
+```
+
+### Multi-trait Colocalization
+```r
+# Basic multi-trait analysis
+result <- colocboost(X=list(X), Y=list(y1, y2, y3))
+
+# Using summary statistics
+result <- colocboost(sumstat=list(sumstat1, sumstat2), LD=LD_matrix)
+
+# View colocalization summary
+summary <- get_cos_summary(result)
+
+# Visualize results
+colocboost_plot(result)
+
+# Filter for stronger colocalization evidence
+filtered <- get_strong_colocalization(result, cos_npc_cutoff = 0.5)
 ```
-- To run FineBoost, you need `colocboost(X=X, Y=y)`, where X and y are the same as `susie(X,y)`
-- To run ColocBoost we suggest using [this pipeline wrapper](https://github.com/StatFunGen/pecotmr/blob/main/R/colocboost_pipeline.R) to manage multiple data-sets mixing individual level and summary statistics data. The `pecotmr` package can be installed either from source or from our conda package at https://anaconda.org/dnachun/r-pecotmr
 
+For more complex analyses involving multiple datasets mixing individual level and summary statistics data, we recommend using [this pipeline wrapper](https://github.com/StatFunGen/pecotmr/blob/main/R/colocboost_pipeline.R) from the `pecotmr` package. The `pecotmr` package can be installed either from source or from our conda package at https://anaconda.org/dnachun/r-pecotmr.
+
+## Citation
+
+If you use ColocBoost in your research, please cite:
+
+Cao X, Sun H, Feng R, Mazumder R, Najar CFB, Li YI, de Jager PL, Bennett D, The Alzheimer's Disease Functional Genomics Consortium, Dey KK, Wang G. (2025+). Integrative multi-omics QTL colocalization maps regulatory architecture in aging human brain. bioRxiv. [https://doi.org/](https://doi.org/)
+
+## Documentation
+
+For detailed documentation, use the R help system:
+
+```r
+?colocboost
+?colocboost_plot
+?get_cos_summary
+?get_strong_colocalization
+```
+
+## License
+
+This package is released under the MIT License.