abseqReport: Visualize all analysis conducted by abseqPy

In abseqR: Reporting and data analysis functionalities for Rep-Seq datasets of antibody libraries

Description

Plots all samples in the output directory supplied to abseqPy's --outdir or -o argument. Users can optionally specify which samples in directory should be compared. Doing so generates additional plots for clonotype comparison and the usual plots will also conveniently include these samples using additional aesthetics.

Calling this function with a valid directory will always return a named list of objects; these individual objects can be combined using the + operator to form a new comparison, in which the report function accepts as its first parameter.

Usage

abseqReport(directory, report, compare, BPPARAM)

Arguments

directory	string type. directory as specified in -o or --outdir in abseqPy. This tells AbSeq where to look for abseqPy's output.
report	(optional) integer type. The possible values are: 0 - does nothing (returns named list of AbSeqRep objects) 1 - generates plots for csv files 2 - generates a report that collates all plots 3 - generates interactive plots in report (default) each higher value also does what the previous values do. For example, report = 2 will return a named list of AbSeqRep objects, plot csv files, and generate a (non-interactive)HTML report that collates all the plots together.
compare	(optional) vector of strings. From the samples in found in directory directory, they can be selected and compared against each other. For example, to compare "sample1" with "sample2" and "sample3" with "sample4", compare should be c("sample1,sample2", "sample3,sample4"). An error will be thrown if the samples specified in this parameter are not found in directory.
BPPARAM	(optional) BiocParallel backend. Configures the parallel implementation. Refer to BiocParallel for more information. By default, use all available cores.

Value

named list. List of AbSeqRep objects. The names of the list elements are taken directly from the repertoire object itself. This return value is consistent with the return value of report.

See Also

AbSeqRep

report. Analogous function, but takes input from an AbSeqRep or AbSeqCRep object instead.

Examples

# Use example data from abseqR as abseqPy's output, substitute this
# with your own abseqPy output directory
abseqPyOutput <- tempdir()
file.copy(system.file("extdata", "ex", package = "abseqR"), abseqPyOutput, recursive=TRUE)

### 1. The `report` parameter usage example:

# report = 0; don't plot, don't collate a HTML report, don't show anything interactive
samples <- abseqReport(file.path(abseqPyOutput, "ex"), report = 0)
# samples is now a named list of AbSeqRep objects

# report = 1; just plot pngs; don't collate a HTML report; nothing interactive
# samples <- abseqReport(file.path(abseqPyOutput, "ex"), report = 1)
# samples is now a named list of AbSeqRep objects

# report = 2; plot pngs; collate a HTML report; HTML report will NOT be interactive
# samples <- abseqReport(file.path(abseqPyOutput, "ex"), report = 2)
# samples is now a named list of AbSeqRep objects

# report = 3 (default); plot pngs; collate a HTML report; HTML report will be interactive
# samples <- abseqReport(file.path(abseqPyOutput, "ex"), report = 3)
# samples is now a named list of AbSeqRep objects

### 2. Using the return value of abseqReport:

# NOTE, often, this is used to load multiple samples from different directories
# using abseqReport (with report = 0), then the samples are added together
# before calling the report function. This is most useful when the samples
# live in different abseqPy output directory.

# Note that the provided example data has PCR1, PCR2, and PCR3
# samples contained within the directory
stopifnot(names(samples) == c("PCR1", "PCR2", "PCR3"))

# as a hypothetical example, say we found something
# interesting in PCR1 and PCR3, and we want to isolate them:
# we want to explicitly compare PCR1 with PCR3
pcr13 <- samples[["PCR1"]] + samples[["PCR3"]]

# see abseqR::report for more information.
# abseqR::report(pcr13)      # uncomment this line to run

### BPPARAM usage:

# 4 core machine, use all cores -  use whatever value that suits you
nproc <- 4
# samples <- abseqReport(file.path(abseqPyOutput, "ex"),
#                        BPPARAM = BiocParallel::MulticoreParam(nproc))


# run sequentially - no multiprocessing
# samples <- abseqReport(file.path(abseqPyOutput, "ex"),
#                        BPPARAM = BiocParallel::SerialParam())

# see https://bioconductor.org/packages/release/bioc/html/BiocParallel.html
# for more information about how to use BPPARAM and BiocParallel in general.

abseqR documentation built on Nov. 8, 2020, 8:28 p.m.