playbase

The `playbase´ package contains the core back-end functionality for the OmicsPlayground. This package allows you to run, develop, and test any essential functions used in the OmicsPlayground directly in the R console without needing to worry about the R Shiny front-end code.

Installation

You can install the development version of playbase from GitHub with:

# install.packages("devtools")
devtools::install_github("bigomics/playbase")

Data upload

The first step in any OmicsPlayground analysis is to upload data which can be used to create a pgx object. The pgx object is basically the core data structure in the OmicsPlayground upon which most analysis and plotting functions operate.

library(playbase)

# Here we check that your input files do not have problems

playbase::PGX_CHECKS # These are the possible errors you can encounter

# individual file checks

SAMPLES = playbase::pgx.checkINPUT(playbase::SAMPLES, type = "SAMPLES")
COUNTS = playbase::pgx.checkINPUT(playbase::COUNTS, type = "COUNTS")
CONTRASTS = playbase::pgx.checkINPUT(playbase::SAMPLES, type = "CONTRASTS")

# Checks across input files

INPUTS_CHECKED <- pgx.crosscheckINPUT(SAMPLES, COUNTS, CONTRASTS)

SAMPLES = INPUTS_CHECKED$SAMPLES
COUNTS = INPUTS_CHECKED$COUNTS
CONTRASTS = INPUTS_CHECKED$CONTRASTS

If no errors are reported (and PASS is TRUE), these new checked files SAMPLES, COUNTS and CONTRASTS can be used safely in the next step.

# Here we create a pgx object that can be used in Omics Playground.

# Step 1. create a pgx object

pgx <- playbase::pgx.createPGX(
 samples = playbase::SAMPLES,
 counts = playbase::COUNTS,
 contrasts = playbase::CONTRASTS
)

# Step 2. Populate pgx object with results

pgx <- playbase::pgx.computePGX(
  pgx = pgx
)

The pgx object

The core object in playbase is the pgx object. This object holds the raw data and any analysis results returned from playbase modules / boards. The pgx object is simply an R list. It contains minimally the following list items:

• counts
• samples
• contrasts

A pgx object is created from these three list items via the following function:

my_pgx <- pgx.createPGX(counts, samples, contrasts)

Once a pgx object is created from these three items, the various playbase modules can operate on the pgx object to generate the analysis results relevant to that specific module.

Playbase modules

As mentioned above, the core object in playbase is the pgx object. This holds all of the analysis and results derived from the raw data, as well as the raw data itself. There are various modules in playbase that take a pgx object as input, perform some analysis on the raw data in the pgx object, and then append these results to the pgx object. These modules are more-or-less independent of one another and can therefore be parallelized or run in any arbitrary order.

The core playbase modules operate on either genes or genesets.

The gene modules are as follows:

• ttest
• ttest.welch
• ttest.rank
• voom.limma
• trend.limma
• notrend.limma
• edger.qlf
• edger.lrt
• deseq2.wald
• deseq2.lrt

The geneset methods are as follows:

• fisher
• gsva
• ssgsea
• spearman
• camera
• fry
• fgsea

And extra modules are as follows:

• meta.go
• deconv
• infer
• drugs
• graph
• connectivity
• wordcloud