Some little R helpers to work with data, and bio-data in particular.
To use them just source them when needed.
Use the issue tracker to suggest changes or to report problems. Feel welcome to suggest changes to or send pull requests.
The R bits are split up into tools for
- general data handling, see
core_commons.R - plotting using ggplot2, see
ggplot_commons.R - bioinformatics using various bioconductor packages, see
bioinfo_commons.R
and some more.
devtools::source_url("https://raw.githubusercontent.com/holgerbrandl/datautils/master/R/core_commons.R")
devtools::source_url("https://raw.githubusercontent.com/holgerbrandl/datautils/master/R/ggplot_commons.R")
devtools::source_url("https://raw.githubusercontent.com/holgerbrandl/datautils/master/R/bio/bioinfo_commons.R")
To install as package run
install.packages("remotes")
remotes::install_github("holgerbrandl/datautils")
or from local working copy with
devtools::install_local("/path/to/workingcopy")
# devtools::install_local("d:/projects/misc/datautils")
To allow for reproducible research, we prefer version tags over cran deployment. You can use these tags to write our workflows. Eg. you could use the stable v1.45 tag
devtools::source_url("https://raw.githubusercontent.com/holgerbrandl/datautils/v1.45/R/core_commons.R")
Instead to use the latest master-branch version (which is subject of constant change) use
devtools::source_url("https://raw.githubusercontent.com/holgerbrandl/datautils/master/R/datatable_commons.R")
Launch local file server in directory where files are located
python -m http.server &
Use the local server to source the files
devtools::source_url("http://localhost:8000/core_commons.R")
devtools::install(".")