Stitch reads

We use PEAR to stitch pair-end reads together.

Our run_pear.pl wrapper script can simply be used like so:

run_pear.pl raw_data/*

Where "raw_data" is a folder that contains FASTQs with either "_R1_" and "_R2_" in their names (alternatively just "_1" and "_2" in the filenames will work).

Four FASTQs are created for each sample:

• assembled reads (typically ~98% of reads, although this can depend on your data type / quality)
• discarded reads (e.g. reads that are all Ns)
• unassembled reads, 1 FASTQ for each direction (we discard these for downstream analyses)

This script generates a summary of the percents of assembled, discarded and unassembled reads for each sample (by default: "pear_summary_log.txt").

Options:

• -o, --out_dir
  The name of the output directory to place all PEAR output files.

• -p, --parallel [<# of proc>]
  Using this option without a value will use all CPUs on machine, while giving it a value will limit to that many CPUs. Without option only one CPU is used.

• -g, --gzip_output
  Gzip the PEAR output files.

• -f, --full_log
  The location to write the PEAR full log file. Default is "pear_full_log.txt"

• -s, --summary_log
  The location to write the PEAR summary log file. Default is "pear_summary_log.txt"

• -h, --help
  Displays the entire help documentation.