Package: CheckSumStats 0.0.0.9000

Philip Haycock

CheckSumStats: CheckSumStats

CheckSumStats is an R package for checking the accuracy of meta- and summary-data from genome-wide association studies (GWAS) prior to their use in post-GWAS applications. For example, the package provides tools for checking that the reported effect allele and effect allele frequency columns are correct. It also checks for possible issues in the reported effect sizes that might introduce bias into downstream analyses.

Authors:Philip Haycock [aut, cre]

CheckSumStats_0.0.0.9000.tar.gz
CheckSumStats_0.0.0.9000.zip(r-4.7)CheckSumStats_0.0.0.9000.zip(r-4.6)CheckSumStats_0.0.0.9000.zip(r-4.5)
CheckSumStats_0.0.0.9000.tgz(r-4.6-any)CheckSumStats_0.0.0.9000.tgz(r-4.5-any)
CheckSumStats_0.0.0.9000.tar.gz(r-4.7-any)CheckSumStats_0.0.0.9000.tar.gz(r-4.6-any)
manual.pdf |manual.html✨
card.svg |card.png
CheckSumStats/json (API)

# Install 'CheckSumStats' in R:

install.packages('CheckSumStats', repos = c('https://mrcieu.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mrcieu/checksumstats/issues

Datasets:

ara_test_dat - A example dataset of genetic summary data for arachidonic acid
charge_top_hits - GWAS top hits for arachidonic acid in the CHARGE consortium
charge_top_hits_cleaned - GWAS top hits for arachidonic acid in the CHARGE consortium after post-GWAS cleaning
glioma_test_dat - A example dataset of genetic summary data
refdat_1000G_superpops - A dataset of reference allele frequencies from 1000 genomes superpopulations

On CRAN:

3.11 score 10 stars 26 scripts 21 exports 141 dependencies

Last updated from:ba670767d4. Checks:7 NOTE, 1 OK, 1 FAIL. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	NOTE	152
source / vignettes	OK	273
linux-release-x86_64	NOTE	163
macos-release-arm64	NOTE	114
macos-oldrel-arm64	NOTE	95
windows-devel	NOTE	86
windows-release	NOTE	83
windows-oldrel	NOTE	88
wasm-release	FAIL	158

Exports:combine_plots compare_effect_to_gwascatalog compare_effect_to_gwascatalog2 extract_sig_snps extract_snps find_hits_in_gwas_catalog flag_af_conflicts flag_gc_conflicts flag_gc_conflicts2 format_data get_efo gwas_catalog_hits infer_ancestry make_plot_gwas_catalog make_plot_maf make_plot_pred_effect make_snplist predict_beta_sd predict_lnor_sh transform_betas zz_plot

Dependencies:abind AnnotationDbi askpass assertthat backports Biobase BiocFileCache BiocGenerics biomaRt Biostrings bit bit64 blob boot brio broom cachem callr car carData cli colorspace corrplot cowplot cpp11 crayon curl DBI dbplyr Deriv desc diffobj doBy dplyr evaluate farver fastmap filelock forecast Formula fracdiff fs generics ggplot2 ggpubr ggrepel ggsci ggsignif glue gridExtra gtable gwasrapidd highr hms httr httr2 ieugwasr IRanges isoband jsonlite KEGGREST knitr labeling lattice lifecycle lme4 lmtest lubridate magrittr MASS Matrix MatrixModels memoise mgcv microbenchmark mime minqa modelr nlme nloptr nnet numDeriv openssl pbkrtest pillar pingr pkgbuild pkgconfig pkgload plyr png polynom praise prettyunits processx progress ps purrr quantreg R6 rappdirs rbibutils RColorBrewer Rcpp RcppArmadillo RcppEigen Rdpack reformulas rlang rprojroot RSQLite rstatix S4Vectors S7 scales Seqinfo SparseM stringi stringr survival sys testthat tibble tidyr tidyselect timechange timeDate triebeard urca urltools utf8 vctrs viridisLite waldo withr writexl xfun xml2 XVector yaml zoo

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
A example dataset of genetic summary data for arachidonic acid	ara_test_dat
GWAS top hits for arachidonic acid in the CHARGE consortium	charge_top_hits
GWAS top hits for arachidonic acid in the CHARGE consortium after post-GWAS cleaning	charge_top_hits_cleaned
Make cow plot	combine_plots
Compare the genetic effect sizes in the test dataset to the GWAS catalog	compare_effect_to_gwascatalog
Compare the genetic effect sizes in the test dataset to the GWAS catalog	compare_effect_to_gwascatalog2
Extract SNPs with P value below a specified threshold (e.g. significant SNPs)	extract_sig_snps
Extract SNPs	extract_snps
Are hits in the GWAS catalog?	find_hits_in_gwas_catalog
Flag allele frequency conflicts	flag_af_conflicts
Flag conflicts with the GWAS catalog	flag_gc_conflicts
Flag conflicts with the GWAS catalog	flag_gc_conflicts2
format data	format_data
get efo	get_efo
A example dataset of genetic summary data	glioma_test_dat
GWAS top hits	gwas_catalog_hits
Infer ancestry	infer_ancestry
Plot comparing the test study to the GWAS catalog	make_plot_gwas_catalog
MAF plot	make_plot_maf
Predicted versus reported effect sizes	make_plot_pred_effect
make a SNP list	make_snplist
Predicted standardised beta	predict_beta_sd
Predicted log odds ratio	predict_lnor_sh
A dataset of reference allele frequencies from 1000 genomes superpopulations	refdat_1000G_superpops
Transform betas	transform_betas
ZZ plot	zz_plot