all_pairwise | R Documentation |
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.
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",
...
)
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. |
This runs limma_pairwise(), deseq_pairwise(), edger_pairwise(), basic_pairwise() each in turn. It collects the results and does some simple comparisons among them.
A list of limma, deseq, edger results.
[limma_pairwise()] [edger_pairwise()] [deseq_pairwise()] [ebseq_pairwise()] [basic_pairwise()]
## Not run:
lotsodata <- all_pairwise(input = expt, model_batch = "svaseq")
summary(lotsodata)
## limma, edger, deseq, basic results; plots; and summaries.
## End(Not run)
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