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author estrain
date Sat, 07 Sep 2019 13:51:19 -0400
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estrain@2 1 # SeqSero2 v1.0.1
estrain@2 2 Salmonella serotype prediction from genome sequencing data.
estrain@2 3
estrain@2 4 Online version: http://www.denglab.info/SeqSero2
estrain@2 5
estrain@2 6 # Introduction
estrain@2 7 SeqSero2 is a pipeline for Salmonella serotype prediction from raw sequencing reads or genome assemblies
estrain@2 8
estrain@2 9 # Dependencies
estrain@2 10 SeqSero has three workflows:
estrain@2 11
estrain@2 12 (A) Allele micro-assembly (default). This workflow takes raw reads as input and performs targeted assembly of serotype determinant alleles. Assembled alleles are used to predict serotype and flag potential inter-serotype contamination in sequencing data (i.e., presence of reads from multiple serotypes due to, for example, cross or carryover contamination during sequencing).
estrain@2 13
estrain@2 14 Allele micro-assembly workflow depends on:
estrain@2 15
estrain@2 16 1. Python 3;
estrain@2 17
estrain@2 18 2. Biopython 1.73;
estrain@2 19
estrain@2 20 3. [Burrows-Wheeler Aligner v0.7.12](http://sourceforge.net/projects/bio-bwa/files/);
estrain@2 21
estrain@2 22 4. [Samtools v1.8](http://sourceforge.net/projects/samtools/files/samtools/);
estrain@2 23
estrain@2 24 5. [NCBI BLAST v2.2.28+](https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE_TYPE=BlastDocs&DOC_TYPE=Download);
estrain@2 25
estrain@2 26 6. [SRA Toolkit v2.8.0](http://www.ncbi.nlm.nih.gov/Traces/sra/sra.cgi?cmd=show&f=software&m=software&s=software);
estrain@2 27
estrain@2 28 7. [SPAdes v3.9.0](http://bioinf.spbau.ru/spades);
estrain@2 29
estrain@2 30 8. [Bedtools v2.17.0](http://bedtools.readthedocs.io/en/latest/);
estrain@2 31
estrain@2 32 9. [SalmID v0.11](https://github.com/hcdenbakker/SalmID).
estrain@2 33
estrain@2 34
estrain@2 35 (B) Raw reads k-mer. This workflow takes raw reads as input and performs rapid serotype prediction based on unique k-mers of serotype determinants.
estrain@2 36
estrain@2 37 Raw reads k-mer workflow (originally SeqSeroK) depends on:
estrain@2 38
estrain@2 39 1. Python 3;
estrain@2 40 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);
estrain@2 41
estrain@2 42
estrain@2 43 (C) Genome assembly k-mer. This workflow takes genome assemblies as input and the rest of the workflow largely overlaps with the raw reads k-mer workflow
estrain@2 44
estrain@2 45
estrain@2 46 # Executing the code
estrain@2 47 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.
estrain@2 48
estrain@2 49 Usage: SeqSero2_package.py
estrain@2 50
estrain@2 51 -m <string> (which workflow to apply, 'a'(raw reads allele micro-assembly), 'k'(raw reads and genome assembly k-mer), default=a)
estrain@2 52
estrain@2 53 -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)
estrain@2 54
estrain@2 55 -i <file> (/path/to/input/file)
estrain@2 56
estrain@2 57 -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)
estrain@2 58
estrain@2 59 -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)
estrain@2 60
estrain@2 61 -d <string> (output directory name, if not set, the output directory would be 'SeqSero_result_'+time stamp+one random number)
estrain@2 62
estrain@2 63 -c <flag> (if '-c' was flagged, SeqSero2 will only output serotype prediction without the directory containing log files)
estrain@2 64
estrain@2 65 --check <flag> (use '--check' flag to check the required dependencies)
estrain@2 66
estrain@2 67 -v, --version (show program's version number and exit)
estrain@2 68
estrain@2 69
estrain@2 70 # Examples
estrain@2 71 Allele mode:
estrain@2 72
estrain@2 73 # Allele workflow ("-m a", default), for separated paired-end raw reads ("-t 2"), use 10 threads in mapping and assembly ("-p 10")
estrain@2 74 SeqSero2_package.py -p 10 -t 2 -i R1.fastq.gz R2.fastq.gz
estrain@2 75
estrain@2 76 K-mer mode:
estrain@2 77
estrain@2 78 # Raw reads k-mer ("-m k"), for separated paired-end raw reads ("-t 2")
estrain@2 79 SeqSero2_package.py -m k -t 2 -i R1.fastq.gz R2.fastq.gz
estrain@2 80
estrain@2 81 # Genome assembly k-mer ("-t 4", genome assemblies only predicted by the k-mer workflow, "-m k")
estrain@2 82 SeqSero2_package.py -m k -t 4 -i assembly.fasta
estrain@2 83
estrain@2 84 # Output
estrain@2 85 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).
estrain@2 86
estrain@2 87
estrain@2 88 # Citation
estrain@2 89 Zhang S, Yin Y, Jones MB, Zhang Z, Deatherage Kaiser BL, Dinsmore BA, Fitzgerald C, Fields PI, Deng X.
estrain@2 90 Salmonella serotype determination utilizing high-throughput genome sequencing data.
estrain@2 91 **J Clin Microbiol.** 2015 May;53(5):1685-92.[PMID:25762776](http://jcm.asm.org/content/early/2015/03/05/JCM.00323-15)