Name Mode Size
..
GCT-class.Rd 100644 1 kb
GCT.Rd 100644 2 kb
align_matrices.Rd 100644 1 kb
annotate_gct.Rd 100644 2 kb
append_dim.Rd 100644 1 kb
cdesc_char.Rd 100644 1 kb
check_colnames.Rd 100644 1 kb
check_dups.Rd 100644 1 kb
distil.Rd 100644 1 kb
ds.Rd 100644 0 kb
extract_gct.Rd 100644 2 kb
fix_datatypes.Rd 100644 1 kb
gene_set.Rd 100644 0 kb
ids.Rd 100644 1 kb
is.wholenumber.Rd 100644 0 kb
kd_gct.Rd 100644 0 kb
lxb2mat.Rd 100644 1 kb
mat.Rd 100644 1 kb
melt_gct.Rd 100644 2 kb
merge_gct.Rd 100644 1 kb
merge_with_precedence.Rd 100644 1 kb
meta.Rd 100644 1 kb
na_pad_matrix.Rd 100644 1 kb
parse_gctx.Rd 100644 2 kb
parse_gmt.Rd 100644 1 kb
parse_gmx.Rd 100644 1 kb
parse_grp.Rd 100644 1 kb
process_ids.Rd 100644 1 kb
rank_gct.Rd 100644 1 kb
read_gctx_ids.Rd 100644 1 kb
read_gctx_meta.Rd 100644 1 kb
robust_zscore.Rd 100644 1 kb
subset_gct.Rd 100644 1 kb
subset_to_ids.Rd 100644 0 kb
threshold.Rd 100644 0 kb
transpose_gct.Rd 100644 1 kb
update_gctx.Rd 100644 1 kb
write_gct.Rd 100644 2 kb
write_gctx.Rd 100644 1 kb
write_gctx_meta.Rd 100644 1 kb
write_gmt.Rd 100644 1 kb
write_grp.Rd 100644 1 kb
write_tbl.Rd 100644 1 kb
README.md
# cmapR (CMap R code) Parsing and utility functions for analyzing CMap data. To learn more about the CMap project at the Broad Institute, please visit [clue.io](https://clue.io). ## NOTICE - Updates for Bioconductor cmapR has been accepted in [Bioconductor](https://www.bioconductor.org/packages/release/bioc/html/cmapR.html). In accordance with Bioconductor standards, we have changed some of the function naming conventions. Function names that used to contain `.` have been replaced with `_`. Hence, `parse.gctx` is now `parse_gctx` and so on. The older function names will still work with a warning. There is additional info and examples in the vignettes/tutorial.Rmd. ### Install instructions **Installing from Bioconductor** In R version 4.0 or newer: ``` if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("cmapR") ``` Dependencies are listed in `DESCRIPTION` **Docker** A docker container with a slightly earlier version of cmapR can be obtained here: https://hub.docker.com/r/cmap/cmapr. This may be preferable for those who would like to use the package without installing on their system. **Installing from Github source** Perhaps the simplest way to install directly from github is using `devtools::install_github("cmap/cmapR")`. Note that this requires having previously installed the `devtools` package. The script `install_cmapR.R` takes care of installing all the dependencies and then running `devtools::install_github("cmap/cmapR")`, so you can simply source this script after cloning this repository. Alternatively, you can point your R's `install.packages` function at a tarball of the `cmapR` archive. You can generate this archive by cloning this repository and doing the following: # make a gzip tar ball of the repo R CMD build cmapR # makes cmapR_1.0.tar.gz # check that the package is ok R CMD check cmapR_1.0.tar.gz Once you have created the tarball, open an R terminal and execute the following: install.packages("cmapR_1.0.tar.gz", type="source", repos=NULL) library("cmapR") You can also source individual files as needed instead of installing the entire package. # For example, just load the IO methods source("cmapR/R/io.R") ### Citation information If you use GCTx and/or cmapR in your work, please cite [Enache et al.](https://www.biorxiv.org/content/early/2017/11/30/227041)