differentialAbundance {LymphoSeq} | 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(sample1, sample2, list, abundance = "estimatedNumberGenomes", type = "aminoAcid", q = 1, zero = 0.001, parallel = FALSE)
sample1 |
A character vector indicating the name of the first sample in the list to be compared. |
sample2 |
A character vector indicating the name of the second sample in the list to be compared. |
list |
A list of data frames consisting of antigen receptor sequences imported by the LymphoSeq function readImmunoSeq. |
abundance |
The input value for the Fisher exact test. "estimatedNumberGenomes" is recommend but "count" may also be used. |
type |
A character vector indicating whether "aminoAcid" or "nucleotide" sequences should be used. If "aminoAcid" 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 = "LymphoSeq") file.list <- readImmunoSeq(path = file.path) productive.aa <- productiveSeq(file.list = file.list, aggregate = "aminoAcid") differentialAbundance(list = productive.aa, sample1 = "TRB_Unsorted_949", sample2 = "TRB_Unsorted_1320", type = "aminoAcid", q = 0.01, zero = 0.001)