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+# SeqSero2 v1.1.0
+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
+
+# 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). 
+
+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/);
+
+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/);
+
+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. 
+
+Raw reads k-mer workflow (originally SeqSeroK) depends on:
+
+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
+
+# Installation
+### Conda
+To install the latest SeqSero2 Conda package (recommended):  
+```
+conda install -c bioconda seqsero2=1.1.0
+```
+### Git
+To install the SeqSero2 git repository locally:
+```
+git clone https://github.com/denglab/SeqSero2.git
+cd SeqSero2
+python3 -m pip install --user .
+```
+### 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) 
+
+    -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)