SpoTyping

SpoTyping is a software for predicting spoligotype from sequencing reads, complete genomic sequences and assembled contigs.

Part I. Spoligotype prediction and SITVIT database query.

Prerequisites:

• Python2.7
• BLAST

Input:

1. Fastq file or pair-end fastq files
2. Fasta file of a complete genomic sequence or assembled contigs of an isolate

Output:

In the output file specified: predicted spoligotype in the format of binary code and octal code.
In the output log file: count of hits from BLAST result for each spacer sequence.
In the xls excel file: spoligotype query result downloaded from SITVIT WEB.
## Note: if the same spoligotype is queried before and have an xls file in the output directory, it will not be queried again.

Usage:

python SpoTyping.py [options] FASTQ_1 FASTQ_2(optional)

An Example call:

python2.7 SpoTyping.py read_1.fastq read_2.fastq –o spo.out

Options:

--version
show program's version number and exit

-h, --help
show this help message and exit

--seq
Set this if input is a fasta file that contains only complete genomic sequence or assembled contigs from an isolate. [Default is off]

-s SWIFT, --swift=SWIFT
swift mode, either "on" or "off" [Default: on]

-m MIN_STRICT, --min=MIN_STRICT
minimum number of error-free hits to support presence of a spacer [Default: 0.1*average read depth]

-r MIN_RELAX, --rmin=MIN_RELAX minimum number of 1-error-tolerant hits to support presence of a spacer [Default: 0.12 * average read depth]

-O OUTDIR, --outdir=OUTDIR
output directory [Default: running directory]

-o OUTPUT, --output=OUTPUT
basename of output files generated [Default: SpoTyping]

--noQuery
suppress the SITVIT database query [Default is off]

--filter
stringent filtering of reads (used only for low quality reads) [Default is off]

--sorted
set this only when the reads are sorted to a reference genome [Default is off]

-d, --debug
enable debug mode, keeping all intermediate files for checking [Default is off]

FASTQ_1/FASTA
input FASTQ read 1 file or sequence fasta file (mandatory)

FASTQ_2
input FASTQ read 2 file (optional for pair-end reads)

Suggestions:

1. It's highly suggested to use the default settings (including the swift mode).
2. Do wish to change the hit thresholds? Can adjust the thresholds to be 0.0180 to 0.1486 times the estimated read depth for error-free hits and 0.0180 to 0.1488 times the estimated read depth for 1-error-tolerant hits. (The read depth is estimated by dividing the sequencing throughput by 4,500,000, which is the estimated Mtb genome length.) The default setting already has this optimized.
3. For low quality sequence reads (reads with many 'N's or long homopolymers), please specify '--filter'.
4. If the reads are sorted against a reference genome (extracted form sorted bam files, for example), please specify '--sorted'.
   
   

SpoTyping seems slow? (Not finished in 5 mins, for example)

• Low quality of sequence reads? (reads with many 'N's or long homopolymers): try to use '--filter'.

# Example commad:
python SpoTyping.py --filter read_1.fastq.gz read_2.fastq.gz

Got weird spoligotype prediction?

• Reads are sorted against a reference genome?: try to use '--sorted'.

# Example commad:
python SpoTyping.py --sorted read_1.fastq.gz read_2.fastq.gz

• Sequencing throughput is very low? (<40Mbp, for example): SpoTyping may not be able to give accurate prediction due to the relatively low read depth.
  
  

Part II. Summary pie chart plot from the downloaded xls files.

Prerequisites:

• R
• R package: gdata

Input:

The xls file downloaded from SITVIT WEB.

Output:

A pdf file with the information in the xls file summarized with pie charts.

Usage:

Rscript SpoTyping_plot.r query_from_SITVIT.xls output.pdf

An example call:

Rscript SpoTypint_plot.r SITVIT_ONLINE.777777477760771.xls SITVIT_ONLINE.777777477760771.pdf