RESEQ

RESEQ is a python script that combines mapping tools and bootstrap to access reproducibility in next generation sequencing data. It uses paired end FASTQ-files as input.

Dependencies and Installation

Dependencies:

• Unix based operating system
• Python 2.7 (recommended)
• Bowtie2
• Samtools
• R 3.3 (optional)

Taxonomy and reference Data.

Reference Sequences:

For virus detection you need the complete reference sequences which are available at ncbi:
https://ftp.ncbi.nlm.nih.gov/refseq/release/viral/
Simply download the sequences, concatenate them and if needed remove new lines from sequences.
Example Template:

>genome1
AATTGGCC
>genome2
GGTTAAAC

EDIT YOUR PATH IN reseq.py LINE 19

Taxonomy Data:

You can download the taxonomy dumb here: https://ftp.ncbi.nlm.nih.gov/pub/taxonomy/
note that to speed up analysis you can alter the file to only include entries which you are mapping to

EDIT YOUR PATH IN reseq.py IN LINE: 22

Bowtie2:

Follow installation here:
http://bowtie-bio.sourceforge.net/bowtie2/index.shtml

Bowtie needs to create index files for mapping:

$: bowtie2-build yourReferenceData.fna indexOut

EDIT THIS PATH IN reseq.py IN LINE 16 WITH THE PREFIX

Samtools:

Follow installation here: http://www.htslib.org/

Using RESEQ

python reseq.py -i _input1.fastq_ -j _input2.fastq 

reseq provides parameters to optimize your run. To view all parameters type:

python reseq.py -h

  -h, --help        show this help message and exit
  -i INPUTR1        fastQ input file R1
  -j INPUTR2        fastQ input file R2
  -n LOOPCOUNT      number of repetitions
  -o OUTPUT         output name
  -s SEQUENCECOUNT  number of sequences extracted
  -r REPLACE        "n": to draw with out replacement Default=draw with
                    replacement
  -d DELETETMP      "n": to keep all temporary files. Default value deletes
                    all tmp files
  -S DELETESAM      "n": to keep all sam / bam files. Default value deletes
                    all files
  -R USER           "y": use R to apply mixture model for False/True positive
                    likelihood predictions
  -t THREADS        number of threads

known issues

• if data sets are too small reseq can sometimes draw the same reads from the fastQ files. To prevent this reseq is implemented with a seed for each bootstrap repitition. To remove this seed you can comment out line 105
• FASTQ files sometimes have different header conventions to distinguish between paired end files. In this version reseq is hard coded for the following:

@xxxxxx 1:N:0:5

to change this you can edit how the headers should be distinguished at line 99. For example if your header strukture looks like this:

@xxxxxx/1
change line 86 and 99 from:

R2Dict[lines[0].strip("\n").split(" ")[0]]= x

to

R2Dict[lines[0].strip("\n").split("/")[0]]= x