akutils phix_filtering

akutils phix_filtering - remove PhiX reads from raw sequence files

Usage (order is important):

akutils phix_filtering <output_directory> <mappingfile> <index> <read1> <read2>

<read2> is optional

This script takes raw fastqs and filters them for phix contamination. Raw fastqs are assumed to not be demultiplexed, and include associated separate index files. You can submit either a pair of reads or just a single read as input.

Data may be single or dual indexed, but dual indexed data needs to be concatenated together first and the resulting combined sequences represented in your mapping file as a single sequence. For instance, if your data has dual 8bp indexes, you will have a single 16bp index sequence in your mapping file.

Preparing dual-indexed data for filtering:
If you have akutils in your path, run the following to prep your dual indexed data for this workflow:

concatenate_fastqs.sh <index1> <index2>

There are several programs you need in place before this will work. See dependencies below. In addition, this script references the config file for akutils. This file tells the workflow important things like where your smalt index for phix resides and how many cores to use. You can modify your global config file or create a local one for a specific job by executing the following:

akutils configure

Mapping file:
This is a mapping file correctly formatted for QIIME. Index sequences must be in the CORRECT ORIENTATION!! If you have a QIIME mapping file with reverse complemented indexes (you have to pass --rev_comp_mapping_barcodes during demultiplexing), you can copy all the sequences from a column if you open your map in Excel or Libre, and paste it into the below website and it will return all sequences in columnar format which you can paste into another sheet containing your sample names and category columns.

online reverse/complement tool

Requires the following dependencies to run (cite as necessary):

1. QIIME 1.9.0 (qiime.org)
2. ea-utils (https://code.google.com/p/ea-utils/)
3. Fastx toolkit (http://hannonlab.cshl.edu/fastx_toolkit/)
4. Smalt (https://www.sanger.ac.uk/resources/software/smalt/)