all_pairwise: Perform limma, DESeq2, EdgeR pairwise analyses.

In elsayed-lab/hpgltools: A pile of (hopefully) useful R functions

Perform limma, DESeq2, EdgeR pairwise analyses.

Description

This takes an expt object, collects the set of all possible pairwise comparisons, sets up experimental models appropriate for the differential expression analyses, and performs them.

Usage

all_pairwise(
  input = NULL,
  conditions = NULL,
  batches = NULL,
  model_cond = TRUE,
  modify_p = FALSE,
  model_batch = TRUE,
  filter = NULL,
  model_intercept = FALSE,
  extra_contrasts = NULL,
  alt_model = NULL,
  libsize = NULL,
  test_pca = TRUE,
  annot_df = NULL,
  parallel = TRUE,
  do_basic = TRUE,
  do_deseq = TRUE,
  do_ebseq = NULL,
  do_edger = TRUE,
  do_limma = TRUE,
  do_noiseq = TRUE,
  do_dream = FALSE,
  keepers = NULL,
  convert = "cpm",
  norm = "quant",
  verbose = TRUE,
  surrogates = "be",
  ...
)

Arguments

input	Dataframe/vector or expt class containing count tables, normalization state, etc.
conditions	Factor of conditions in the experiment.
batches	Factor of batches in the experiment.
model_cond	Include condition in the model? This is likely always true.
modify_p	Depending on how it is used, sva may require a modification of the p-values.
model_batch	Include batch in the model? This may be true/false/"sva" or other methods supported by all_adjusters().
filter	Added because I am tired of needing to filter the data before invoking all_pairwise().
model_intercept	Use an intercept model instead of cell means?
extra_contrasts	Optional extra contrasts beyone the pairwise comparisons. This can be pretty neat, lets say one has conditions A,B,C,D,E and wants to do (C/B)/A and (E/D)/A or (E/D)/(C/B) then use this with a string like: "c_vs_b_ctrla = (C-B)-A, e_vs_d_ctrla = (E-D)-A, de_vs_cb = (E-D)-(C-B)".
alt_model	Alternate model to use rather than just condition/batch.
libsize	Library size of the original data to help voom().
test_pca	Perform some tests of the data before/after applying a given batch effect.
annot_df	Annotations to add to the result tables.
parallel	Use dopar to run limma, deseq, edger, and basic simultaneously.
do_basic	Perform a basic analysis?
do_deseq	Perform DESeq2 pairwise?
do_ebseq	Perform EBSeq (caveat, this is NULL as opposed to TRUE/FALSE so it can choose).
do_edger	Perform EdgeR?
do_limma	Perform limma?
do_noiseq	Perform noiseq?
do_dream	Perform dream?
keepers	Limit the pairwise search to a set of specific contrasts.
convert	Modify the data with a 'conversion' method for PCA?
norm	Modify the data with a 'normalization' method for PCA?
verbose	Print extra information while running?
surrogates	Either a number of surrogates or method to estimate it.
...	Picks up extra arguments into arglist.

Details

This runs limma_pairwise(), deseq_pairwise(), edger_pairwise(), basic_pairwise() each in turn. It collects the results and does some simple comparisons among them.

Value

A list of limma, deseq, edger results.

See Also

[limma_pairwise()] [edger_pairwise()] [deseq_pairwise()] [ebseq_pairwise()] [basic_pairwise()]

Examples

## Not run: 
 lotsodata <- all_pairwise(input = expt, model_batch = "svaseq")
 summary(lotsodata)
 ## limma, edger, deseq, basic results; plots; and summaries.

## End(Not run)

elsayed-lab/hpgltools documentation built on April 8, 2024, 1:30 a.m.