wijerasa / pypeamplicon Goto Github PK

Authors:

Saranga Wijeratne & Vitor Pavinato

CITATION

INSTALLATION

You should install the softwares and python packages listed below in order to run the pipeline. For the softwares installation follow the instructions provided in their webpages. For the python packages, install them either by pip or anaconda depending which python installation you have.

Third part softwares:

• usearch;
• bbmap and bbsplit;
• seqtk
• picard;
• freebayes.

Python packages:

USAGE

python pypeamplicon.py pypeamplicon_config.cfg

CONFIGURATION FILE

In order to run the pipeline you should speficy the configuration file. This file contains paths and necessary information to run the pipeline. Below are detailed information in how to set each configuration section.

[SOFTWARES]

You should install and specify their path.

[REF]

You should specify the path for the file containing the FASTA sequence you are using as a reference sequence. It can be either the reference genome/scaffold OR the fragment homologous to the amplicon.

[FQDIR]

You should specify where the .fastq files were stored.

[WORKINGDIR]

You should specify your working directory. We suggest the following organization:

• <Project_folder> as the working directory;
  • Where you store your reference file;
  • <Raw_files> Where you store your raw fastq files;

[COMMANSUFFIX]

In this section you can specify the type of the sequencing data you have

• PE: for paired-end data;
• SE: for single-end data;

For PE data you should provide the sulfix for the first-read files (R1) and for the second-read files (R2). However, in order to work, your raw fastq files should have this sulfix at the end of the file name (right before .fastq).

[CLUSTERFILTER]

Clustering filter section allows you to control the behavior of two parameters that define the filtering of your raw data:

1. filtercutoff: the minimum percentege of similarities between reads that are combined in a cluster of reads;
2. <>.

POSTPROCESSING SCRIPTS

At the final stage of the pipeline, the variant calling is performed using freebayes. However if, for some reason, you would like to have more control at this stage, we provide a sh script that runs freebayes. The parameters set in this script were tested in three independet datasets. You can modify it to fit your needs.

Script freebayes-pypeamplicon.sh

sh freebayes-ampliconseq-belgica.sh <input.bam> <output.vcf> <populations-file>

The population-file is a tab limited file containing in each row:

<sample_id> tab <pop_id>

If you are working with amplicon sequencing and have a list of targeted SNPs (already tested in other experiments), you probably are interested in process the raw vcf of the amplicon sequencing experiment to remove the non-targeted snps. We have two other sh scripts that allow you to:

1. Keep only the targeted SNPs in the filtered .vcf file;
2. Keep only the non-target SNPs in another .vcf file.

To keep only the targeted SNPs

sh vcfintersect-targets.sh <input.vcf> <output.vcf>

To keep only the non-targeted SNPs

sh vcfintersect-non-targets.sh <input.vcf> <output.vcf>

In both scripts you need to specify a BED file that contains the position of the targeted SNPs.