View source: R/differentialAbundance.R
differentialAbundance | R Documentation |
Use a Fisher exact test to calculate differential abdunance of each sequence in two samples and reports the log2 transformed fold change, P value and adjusted P value.
differentialAbundance( study_table, repertoire_ids = NULL, abundance = "duplicate_count", type = "junction_aa", q = 1, zero = 1, parallel = FALSE )
study_table |
A tibble consisting of antigen receptor sequences imported by the LymphoSeq function readImmunoSeq. |
repertoire_ids |
A character vector of two repertoire_ids in study_table to be compared. If NULL, the first two repertoire_ids from study_table will be used. |
abundance |
The input value for the Fisher exact test. "duplicate_count" is recommend but "duplicate_count" may also be used. |
type |
A character vector indicating whether "junction_aa" or "junction" sequences should be used. If "junction_aa" is specified, then run productiveSeqs first. |
q |
A numeric value between 0.0 and 1.0 indicating the threshold Holms adjusted P value (also knowns as the false discovery rate or q value) to subset the results with. Any sequences with a q value greater than this value will not be shown. |
zero |
A numeric value to set all zero values to when calculating the log2 transformed fold change between samples 1 and 2. This does not apply to the p and q value calculations. |
parallel |
A boolean indicating wheter parallel processing should be used or not. |
Returns a data frame with columns corresponding to the frequency of the abudance measure in samples 1 and 2, the P value, Q value (Holms adjusted P value, also knowns as the false discovery rate), and log2 transformed fold change.
file_path <- system.file("extdata", "TCRB_sequencing", package = "LymphoSeq2") stable <- readImmunoSeq(path = file_path) atable <- productiveSeq(study_table = stable, aggregate = "junction_aa") differentialAbundance(study_table = atable, repertoire_ids = c("TRB_Unsorted_949", "TRB_Unsorted_1320"), type = "junction_aa", q = 0.01, zero = 0.001)
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