Once ingredients have been procured, they are shelved in the pantry ready for use.

Bioinformatics datasets are provided by a wide range of groups, in a wide range formats, and are rapidly changing. This is an opinionated guide to collect and curate data sets. It sets up a local database of datasets that can be used for an integrated analysis.

to install:

  1. Install a postgres database (http://www.postgresql.org/)

1a. Create the json file ~/.pantry_login that will be passed to dplyr::src_postgres to login ot the database. For example:

{
  "staging_directory" : "$HOME/pantry_sets",
  "login" : {
    "dbname" : "<database name",
    "host" : "<host>",
    "user" : "<user>",
    "password" : "<password>",
    "port" : <port>
  }
}
  1. Install the package in R
install.packages("devtools")
devtools::install_github("maomlab/BioChemPantry")

usage:

  1. Install datasets

  1. Load datasets by following the vignettes in vignettes/sets/

  2. Use datasets

library(plyr)
library(dplyr)
library(BioChemPantry)
pantry <- get_pantry(schema=<dataset>)

tbl <- pantry %>% schema_tbl("<tbl>")