Pooling NextSeq fastq files

Pooling Illumina NextSeq 500 fastq files using a Snakemake directive

Requirement

• Unix (only tested on Linux)
• Snakemake
• Python 3.5+ (optional)
• basemount (optional)

Usage

Download or clone this repository in your standard software directory (doesn't need to be where the actual data is).

cd ~/software
git clone https://github.com/seb-mueller/pooling-nextseq-fastq.git

Navigate or Create your project folder where you want the pooled data to be created.

cd ~/analysis
mkdir mynextseqproject
cd mynextseqproject

Create a config.yaml file. This can be done manual using a text editor (an example config.yaml is included in this repo or see the content below): Each entry underneath the "SAMPLES:" line corresponds to a folder in the Samples directory of the basemount copied data (here the samples are sample1 and sample2, as can be seen in the tree at the bottom in this document). Note: Having to list all samples is a deliberate choice for reproducibility etc. reasons and the config.yaml should be thought of a companion to this project.

The generation can also be automized using the generate_config.py script. In this example we are using moch data shipped with this repo:

python3 ~/software/pooling-nextseq-fastq/generate_config.py --dir ~/software/pooling-nextseq-fastq/mynextseqdir

This should generate a config.yaml with the following content:

NEXTSEQDIR: /home/sm934/software/pooling-nextseq-fastq/mynextseqdir
OUTDIR: fastq_pooled
SAMPLES:
  sample1: null
  sample2: null

snakemake -s ~/software/pooling-nextseq-fastq/Snakefile

Note, snakemake expects the "Snakefile" in the directory it is run from, but since we don't need it in every project since all the project information are in the "config.yaml". So we just point it to the common Snakefile shipped with this repo using the -s flag.

Which should generate the following files:

├── config.yaml
├── fastq_pooled
│   ├── sample1_R1.fastq.gz
│   ├── sample1_R2.fastq.gz
│   ├── sample2_R1.fastq.gz
│   └── sample2_R2.fastq.gz
└── logs
    └── pooling_fastq
        ├── sample1.log
        └── sample2.log

Purpose of this script

This is meant to be an automated pipiline to merge fastq files form the NextSeq 500 machine which we are increasingly use. Due to the availability of BaseSpace Linux command line interface (CLI) called basemount, it is possible to automate the download of NGS data. We usually adapt the following workflow:

basemount ~/basespacemount
cd ~/basespacemount
cp -R mynextseqdir /myarchive

The output is a bit convoluted, but contains all we need in a structured way. Annoyingly, the data is split up into 4 lanes due to the nature of the machine. This can be considered as technial replicats and should be pooled, which is the pupose of this program.

mynextseqdir
├── AppResults
├── AppSessions
│   └── FASTQ Generation 2017-08-09 10:29:30Z
│       ├── Logs
│       ├── Logs.metadata
│       └── Properties
│           ├── Input.run-id.attributes
│           │   └── 0
│           ├── Input.Runs
│           ├── Output.Projects
│           └── Output.Samples
├── Properties
└── Samples
    ├── sample1
    │   ├── Files
    │   │   ├── samp1_L001_R1_001.fastq.gz
    │   │   ├── samp1_L001_R2_001.fastq.gz
    │   │   ├── samp1_L002_R1_001.fastq.gz
    │   │   ├── samp1_L002_R2_001.fastq.gz
    │   │   ├── samp1_L003_R1_001.fastq.gz
    │   │   ├── samp1_L003_R2_001.fastq.gz
    │   │   ├── samp1_L004_R1_001.fastq.gz
    │   │   └── samp1_L004_R2_001.fastq.gz
    │   ├── Files.metadata
    │   └── Properties
    │       ├── Input.Runs
    │       └── PerLaneAttributes.LaneNumbers
    └── sample2
        ├── Files
        │   ├── samp2_L001_R1_001.fastq.gz
        │   ├── samp2_L001_R2_001.fastq.gz
        │   ├── samp2_L002_R1_001.fastq.gz
        │   ├── samp2_L002_R2_001.fastq.gz
        │   ├── samp2_L003_R1_001.fastq.gz
        │   ├── samp2_L003_R2_001.fastq.gz
        │   ├── samp2_L004_R1_001.fastq.gz
        │   └── samp2_L004_R2_001.fastq.gz
        ├── Files.metadata
        └── Properties
            ├── Input.Runs
            └── PerLaneAttributes.LaneNumbers

General information

• This script is unzipping the raw files, concatenates them and gzip them again as opposed to just concatenating them, here is a discussion why: https://www.biostars.org/p/81924/.

• The actual processing is done with a bash script sitting in the script folder, this is planed to be ported to python at some point.

Pooling fastq files without Snakemake or without the basemount directory structure

If you don't have Snakemake you can just run the another script shipped in this repo (scripts/pooling_nextseq500_multisample.sh) (but would loose all the perks coming with Snakemake obviously):

bash pooling_nextseq500_multisample.sh dir_raw_data dir_local

This script still assumes the Basespace data structure, but should be easily adaptable. Please get in touch if this should be made more generic.