jd_dada2: Run DADA2 ASV inference from primer- and adapter-removed...

In jdwiyanto/mbiome: A convenient wrapper to visualise and run core analyses for multi-variable microbiome data

Description

Function must be run on folders containing the fastq files to be inferred to ASV. This function will output several files, including the list of filtered reads, sequence table file in RDS form (chimera not removed!), redundant fasta files for PAPRICA input, and save the whole environment (.R file)

Usage

jd_dada2(seqlength_min = 400, seqlength_max = 470, truncLen = c(0, 0))

Arguments

seqlength_min	minimum sequence length to keep, default to 400 for V3-V4 region
seqlength_max	maximum sequence length to keep, default to 470 for V3-V4 region
trunclen	= dada2 input determining the length of sequence to keep after quality control. Default to no trimming c(0,0)

Details

It is important to take note that different sample batch should be run separately. Recommended to keep each batch on separate folder and run this function on a folder loop. For example:

for (directory in 1:length(list.dirs(recursive = F))) path = getwd() dire = list.dirs(recursive = F) setwd(diredirectory) jd_dada2() setwd(path)

Value

csv files of filtered reads summary, ASV sequence table in RDS format, PAPRICA-friendly redundant fasta sequence files, saved R environment

jdwiyanto/mbiome documentation built on April 18, 2021, 3:31 a.m.