This is likely a newbie\'s question but I think I did my homework and yet have not found the answer (I hope to find) so I am posting it here to seek some assistance.
Here is another way to explore the functionality of any package. Although it is not as comprehensive a solution as Dirk's, it is still useful. When I want to know all the functionality of a package, I quickly list all of its functions. Then if I'm curious about any function, I an quickly pull up the help file ?function_name
and see what it does. For that reason, I keep this function in my .rprofile
so it automatically loads every time I run R
.
lsp <- function (package, all.names = FALSE, pattern) {
package <- deparse(substitute(package))
ls(pos = paste("package", package, sep = ":"), all.names = all.names,
pattern = pattern)
}
This is especially helpful when I know the partial name of a function and what package it belongs to but quickly need to find it.
e.g.
> lsp(ggplot2, pattern = "geom")
[1] "geom_abline" "geom_area"
[3] "geom_bar" "geom_bin2d"
[5] "geom_blank" "geom_boxplot"
[7] "geom_contour" "geom_crossbar"
[9] "geom_density" "geom_density2d"
[11] "geom_dotplot" "geom_errorbar"
[13] "geom_errorbarh" "geom_freqpoly"
[15] "geom_hex" "geom_histogram"
[17] "geom_hline" "geom_jitter"
[19] "geom_line" "geom_linerange"
[21] "geom_map" "geom_path"
[23] "geom_point" "geom_pointrange"
[25] "geom_polygon" "geom_quantile"
[27] "geom_raster" "geom_rect"
[29] "geom_ribbon" "geom_rug"
[31] "geom_segment" "geom_smooth"
[33] "geom_step" "geom_text"
[35] "geom_tile" "geom_violin"
[37] "geom_vline" "update_geom_defaults"
If you want to see all the system files for a particular package, then try something like
list.files(system.file(package = 'TCGAGBM'), recursive = T, full.names = T)
How useful this will be will depend on your OS, as the way packages are installed is OS dependent
see the appropriate section in R Installation and Administration manual for more details.
@DirkEddelbuettel's suggestion of inspecting the source is a far better approach.
My preferred approach by far is to simply look at the source code of a package in question.
In fact, I actually do that pretty often as running CRANberries creates a local CRAN mirror as a side effect. But even if you don't, CRAN packages really are only a quick download away and will come with comments in the source which the parsed code excludes.
Edit: I just found what Ben found too: Sean Davis' page at http://watson.nci.nih.gov/~sdavis/tutorials/TCGA_data_integration/ -- looks like it uses some BioC packages too. I would still study the source which often has more comments, annotations, extras, ... than the installed package. But maybe that's just my preference. YMMV as they say.