differentialAbundance: Differential abundance analysis
In LymphoSeq: Analyze high-throughput sequencing of T and B cell receptors

Description Usage Arguments Value Examples

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.

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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)