Mercurial > repos > cstrittmatter > ss2v110
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author | cstrittmatter |
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date | Fri, 01 May 2020 13:30:43 -0400 |
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--- a/README.md Thu Apr 30 21:47:42 2020 -0400 +++ b/README.md Fri May 01 13:30:43 2020 -0400 @@ -1,51 +1,117 @@ -[![DOI](https://zenodo.org/badge/97020646.svg)](https://zenodo.org/badge/latestdoi/97020646) +# SeqSero2 v1.1.1 +Salmonella serotype prediction from genome sequencing data. + +Online version: http://www.denglab.info/SeqSero2 + +# Introduction +SeqSero2 is a pipeline for Salmonella serotype prediction from raw sequencing reads or genome assemblies -# SalmID -Rapid tool to check taxonomic ID of single isolate samples. Currently only IDs Salmonella species and subspecies, and some common contaminants (Listeria, Escherichia). +# Dependencies +SeqSero2 has three workflows: + +(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). -## Requirements: -Python 3 +Allele micro-assembly workflow depends on: + +1. Python 3; + +2. Biopython 1.73; + +3. [Burrows-Wheeler Aligner v0.7.12](http://sourceforge.net/projects/bio-bwa/files/); -## Installation: -The easy way with homebrew ([Linux](http://linuxbrew.sh/) or [MacOS](https://brew.sh/)): -``` -brew install brewsci/bio/salmid -``` -Big thanks to [Torsten Seemann](https://tseemann.github.io/) for including this in homebrew! +4. [Samtools v1.8](http://sourceforge.net/projects/samtools/files/samtools/); + +5. [NCBI BLAST v2.2.28+](https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE_TYPE=BlastDocs&DOC_TYPE=Download); + +6. [SRA Toolkit v2.8.0](http://www.ncbi.nlm.nih.gov/Traces/sra/sra.cgi?cmd=show&f=software&m=software&s=software); + +7. [SPAdes v3.9.0](http://bioinf.spbau.ru/spades); + +8. [Bedtools v2.17.0](http://bedtools.readthedocs.io/en/latest/); -Alternatively download from GitHub: +9. [SalmID v0.11](https://github.com/hcdenbakker/SalmID). + + +(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. -```bash -git clone https://github.com/hcdenbakker/SalmID.git -``` +Raw reads k-mer workflow (originally SeqSeroK) depends on: -build a wheel using [poetry](https://poetry.eustace.io/): +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); + + +(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 -```bash -cd SalmID -poetry build +# Installation +### Conda +To install the latest SeqSero2 Conda package (recommended): +``` +conda install -c bioconda seqsero2=1.1.1 ``` - -and install using `pip` - -```bash -pip install dist/salmid*.whl +### Git +To install the SeqSero2 git repository locally: ``` - -To execute: +git clone https://github.com/denglab/SeqSero2.git +cd SeqSero2 +python3 -m pip install --user . ``` -SalmID.py -e .fastq.gz -``` -This will perform a SalmID run on all fastq.gz files in the current directory. -``` -SalmID.py -i your_fastq_gz.fastq.gz -``` -This will perform a SalmID run on an individual file (i.e., your_fastq_gz.fastq.gz) -``` -SalmID.py -d directory_with_data -e _1.fastq.gz -``` -This will perform a SalmID run on all files in directory 'directory_with_data' with extension '_1.fastq.gz' +### Other options +Third party SeqSero2 installations (may not be the latest version of SeqSero2): \ +https://github.com/B-UMMI/docker-images/tree/master/seqsero2 \ +https://github.com/denglab/SeqSero2/issues/13 + + +# 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 workflow to apply, 'a'(raw reads allele micro-assembly), 'k'(raw reads and genome assembly k-mer), default=a) + + -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) -## Todo's and thoughts for future releases: -- Provide coverage estimates for genomes in sample based on kmer frequencies -- Write code to use SalmID on long read (minion, pacbio) platforms + -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 only output serotype prediction without the directory containing log files) + + -n <string> (optional, to specify a sample name in the report output) + + -s <flag> (if '-s' was flagged, SeqSero2 will not output header in SeqSero_result.tsv) + + --check <flag> (use '--check' flag to check the required dependencies) + + -v, --version (show program's version number and exit) + + +# Examples +Allele mode: + + # Allele workflow ("-m a", default), for separated paired-end raw reads ("-t 2"), use 10 threads in mapping and assembly ("-p 10") + SeqSero2_package.py -p 10 -t 2 -i R1.fastq.gz R2.fastq.gz + +K-mer mode: + + # Raw reads k-mer ("-m k"), for separated paired-end raw reads ("-t 2") + SeqSero2_package.py -m k -t 2 -i R1.fastq.gz R2.fastq.gz + + # Genome assembly k-mer ("-t 4", genome assemblies only predicted by the k-mer workflow, "-m k") + SeqSero2_package.py -m k -t 4 -i assembly.fasta + +# 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, Den-Bakker HC, Li S, Dinsmore BA, Lane C, Lauer AC, Fields PI, Deng X. +SeqSero2: rapid and improved Salmonella serotype determination using whole genome sequencing data. +**Appl Environ Microbiology. 2019 Sep; 85(23):e01746-19.** [PMID: 31540993](https://aem.asm.org/content/early/2019/09/17/AEM.01746-19.long) + +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)