# SeqSero2 alpha-test version
Salmonella serotyping from genome sequencing data


# Introduction 
SeqSero2 is a pipeline for Salmonella serotype determination from raw sequencing reads or genome assemblies. This is a alpha test version. A web app will be available soon.


# Dependencies 
SeqSero has two modes:


(A) k-mer based mode (default), which applies unique k-mers of serotype determinant alleles to determine Salmonella serotypes in a fast speed. Special thanks to Dr. Hendrik Den Bakker for his significant contribution to this mode, details can be found in [SeqSeroK](https://github.com/hcdenbakker/SeqSeroK) and [SalmID](https://github.com/hcdenbakker/SalmID).

K-mer mode is a independant pipeline, it only requires:

1. Python 3;
2. [SRA Toolkit](http://www.ncbi.nlm.nih.gov/Traces/sra/sra.cgi?cmd=show&f=software&m=software&s=software) (optional, just used to fastq-dump sra files);


(B) allele based mode (if users want to extract serotype determinant alleles), which applies a hybrid approach of reads-mapping and micro-assembly.

Allele mode depends on:

1. Python 3; 

2. [Burrows-Wheeler Aligner](http://sourceforge.net/projects/bio-bwa/files/); 

3. [Samtools](http://sourceforge.net/projects/samtools/files/samtools/);

4. [NCBI BLAST](https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE_TYPE=BlastDocs&DOC_TYPE=Download);

5. [SRA Toolkit](http://www.ncbi.nlm.nih.gov/Traces/sra/sra.cgi?cmd=show&f=software&m=software&s=software);

6. [SPAdes](http://bioinf.spbau.ru/spades);

7. [Bedtools](http://bedtools.readthedocs.io/en/latest/);

8. [SalmID](https://github.com/hcdenbakker/SalmID).


# Executing the code 
Make sure all SeqSero2 and its dependency executables are added to your path (e.g. to ~/.bashrc). Then type SeqSero2_package.py to get detailed instructions.

    Usage: SeqSero2_package.py 

    -m <string> (which mode to apply, 'k'(kmer mode), 'a'(allele mode), default=k)

    -t <string> (input data type, '1' for interleaved paired-end reads, '2' for separated paired-end reads, '3' for single reads, '4' for genome assembly, '5' for nanopore fasta, '6'for nanopore fastq)

    -i <file> (/path/to/input/file)

    -p <int> (number of threads for allele mode, if p >4, only 4 threads will be used for assembly since the amount of extracted reads is small, default=1) 

    -b <string> (algorithms for bwa mapping for allele mode; 'mem' for mem, 'sam' for samse/sampe; default=mem; optional; for now we only optimized for default "mem" mode)
 
    -d <string> (output directory name, if not set, the output directory would be 'SeqSero_result_'+time stamp+one random number)
	
	-c <flag> (if '-c' was flagged, SeqSero2 will use clean mode and only output serotyping prediction without the directory containing log files)
	

# Examples
K-mer mode:

    # K-mer (default), for separated paired-end raw reads ("-t 2")
	SeqSero2_package.py -t 2 -i R1.fastq.gz R2.fastq.gz
	
	# K-mer (default), for assemblies ("-t 4", assembly only predcited by K-mer mode)
	SeqSero2_package.py -t 4 -i assembly.fasta

Allele mode:

    # Allele mode ("-m a"), for separated paired-end raw reads ("-t 2"), use 10 threads in mapping and assembly ("-p 10")
	SeqSero2_package.py -m a -p 10 -t 2 -i R1.fastq.gz R2.fastq.gz
	
	
# Output 
Upon executing the command, a directory named 'SeqSero_result_Time_your_run' will be created. Your result will be stored in 'Seqsero_result.txt' in that directory. And the assembled alleles can also be found in the directory if using "-m a" (allele mode).


# Citation
Zhang S, Yin Y, Jones MB, Zhang Z, Deatherage Kaiser BL, Dinsmore BA, Fitzgerald C, Fields PI, Deng X.  
Salmonella serotype determination utilizing high-throughput genome sequencing data.  
**J Clin Microbiol.** 2015 May;53(5):1685-92.[PMID:25762776](http://jcm.asm.org/content/early/2015/03/05/JCM.00323-15)