Computes the intersection of forward and reverse strand haplotypes and generates some report files.
ConsHaplotypes(trimfiles, pm.res, thr = 0.2, min.seq.len = 150, max.difs = 250)
Vector including the paths of demultiplexed files by specific primer, with fna extension.
The list returned by
Threshold to filter haplotypes at minimum abundance before multiple alignment.
Threshold to filter haplotypes at minimum length before intersection.
Maximum number of mismatches allowed in resulting consensus haplotypes with respect to the dominant one.
This function is designed to be used after the execution of
from the same package. After the generation of FASTA files containing forward and reverse strand reads
for the evaluated samples,
ConsHaplotypes executes multiple alignment with
returns the consensus haplotypes using
IntersectStrandHpls, that will be saved using
the helper function
The function returns a
data.frame object containing the intersection results
for each combination of patient and amplicon region, including the initial number of reads, filtered out reads
(for being below a given frequency threshold or unique to a single strand), overlapping frequency
between both strands and the common reads (in percentage and nº of reads).
After execution, two FASTA files for each combination of sample and pool will be saved in a newly generated MACH folder; the first includes multiple alignment between forward and reverse strand haplotypes, and the second includes the forward and reverse strands intersected. Additionaly, some report files will be generated in the reports folder:
MA.Intersects-SummRprt.txt: Includes the sumary results by reads number after abundance filter and
MA.Intersects.plots.pdf: Includes different barplots for each sample representing the frequency of
forward, reverse and intersected strand haplotypes.
IntersectBarplots.pdf: Includes different barplots for all combinations of patient and pool,
representing the number of intersected and filtered out reads, the intersection yield and global yield.
A new file named
muscle options will be generated and saved in a folder named "tmp".
splitDir <- "./splits" # Save the file names with complete path splitfiles <- list.files(splitDir,recursive=TRUE,full.names=TRUE,include.dirs=TRUE) # Get data samples <- read.table("./data/samples.csv", sep="\t", header=T, colClasses="character",stringsAsFactors=F) mids <- read.table("./data/mids.csv", sep="\t", header=T, stringsAsFactors=F) # Apply previous function from QA analysis pm.res <- demultiplexPrimer(splitfiles,samples,primers) # Save the files generated by previous function trimDir <- "./trim" trimfiles <- list.files(trimDir,recursive=TRUE,full.names=TRUE,include.dirs=TRUE) # Define necessary parameters min.seq.len <- 150 thr <- 0.2 int.res <- ConsHaplotypes(trimfiles, pm.res, thr, min.seq.len)
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