all_pairwise: Perform limma, DESeq2, EdgeR pairwise analyses.

View source: R/de_shared.R

all_pairwiseR Documentation

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 May 9, 2024, 5:02 a.m.