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1 # SeqSero2S
2
3 Salmonella serotype prediction from genome sequencing data.
4
5 Online version: http://www.denglab.info/SeqSero2
6
7 # Updates since SS2 v1.2.1
8 1. Convert the sequences of the following alleles to their reverse complement sequences in the SeqSero2 database.
9 ```
10 -fliC_b_Wien_CDC_b,d,j__1488\
11 -fliC_d_from-II-48:d:z6_SRR1168371__1521\
12 -fliC_a_Salmonella.enterica_from-cdc-Stk2184_other.a__1488
13 -fliC_l,v_from-Nchanga_SRR1153349__1503
14 -fliC_l,z13,z28_Salmonella.enterica_from-CDC_2011K-0215_l,v__1506
15 -fljB_1,7_Salmonella.enterica_from-cdc_Stk1415_1__1521
16 -fljB_1,5_from-cdc_Stk2184_1__1521
17 -fljB_1,5_from-Infantis-micro-assembly_SRR1106258_1__1521
18 -fljB_z6_from-II-48:d:z6_SRR1168371__1503
19 ```
20 2. Delete the following alleles from the SeqSero2 database because of the existence of mutations.
21 ```
22 -fliC_y_Bareillystr_AOZP01000027_other.y__1508
23 -fliC_d_Muenchenstr_ARYW01000085_b,d,j__1496
24 -fliC_d_Muenchenstr_ARYX01000110_b,d,j__1488
25 -fliC_g,m_Enteritidisstr_ALHD01000038_g,m__1507
26 -fljB_1,2_Newportstr_AYDZ01000021_1__1510
27 ```
28 2. Add a fliC 1,5,7 allele and a fliC 1,2,7 allele into the SeqSero2 database.
29 ```
30 -fliC_1,5,7_Salmonella.enterica_from-cdc-Stk1778_1,5,7_1521
31 -fliC_1,2,7_Salmonella.enterica_from-cdc-Stk2293_1,2,7_1521
32 ```
33 3. Delete the O54 allele
34 ```
35 -O-54_wbbF__1380
36 ```
37 4. Fixed the bug that caused the misidentification of O9 and O2 by the micro-assembly workflow
38 5. Update serotype names based on the simplified KWS scheme
39 6. Remove the 9,46,27 allele
40 ```
41 -O-9,46,27_partial_wzy__1019
42 ```
43 7. Remove two fljB_1,2 allels
44 ```
45 -fljB_1,2_from-Brazzaville_SRR2058145_1__1521
46 -fljB_1,2_Salmonella.enterica_1,4,5,12:i:1,2,7_AY353272_1__1521
47 ```
48 8. Run 7-gene MLST analysis using stringMLST/mlst
49
50 # Introduction
51 SeqSero2S is a pipeline for Salmonella serotype prediction from raw sequencing reads or genome assemblies
52
53 # Dependencies
54 SeqSero2S has three workflows:
55
56 (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).
57
58 Allele micro-assembly workflow depends on:
59
60 1. Python 3;
61 2. Biopython 1.73;
62 3. [Burrows-Wheeler Aligner v0.7.12](http://sourceforge.net/projects/bio-bwa/files/);
63 4. [Samtools v1.8](http://sourceforge.net/projects/samtools/files/samtools/);
64 5. [NCBI BLAST v2.2.28+](https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE_TYPE=BlastDocs&DOC_TYPE=Download);
65 6. [SRA Toolkit v2.8.0](http://www.ncbi.nlm.nih.gov/Traces/sra/sra.cgi?cmd=show&f=software&m=software&s=software);
66 7. [SPAdes v3.9.0](http://bioinf.spbau.ru/spades);
67 8. [Bedtools v2.17.0](http://bedtools.readthedocs.io/en/latest/);
68 9. [SalmID v0.11](https://github.com/hcdenbakker/SalmID);
69 10. [stringMLST v0.6.3](https://github.com/jordanlab/stringMLST);
70
71 (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.
72
73 Raw reads k-mer workflow (originally SeqSeroK) depends on:
74
75 1. Python 3;
76 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);
77 3. [mlst v2.22.1](https://github.com/tseemann/mlst).
78
79
80 (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
81
82 # Installation
83 ### Git
84 Install mlst and stringMLST first
85 ```
86 conda install mlst
87 ```
88 ```
89 pip install stringMLST
90 ```
91 To install the SeqSero2S git repository locally:
92 ```
93 git clone https://github.com/LSTUGA/SeqSero2S.git
94 cd SeqSero2S
95 python3 -m pip install --user .
96 ```
97
98 # Executing the code
99 Make sure all SeqSero2S and its dependency executables are added to your path (e.g. to ~/.bashrc). Then type SeqSero2S.py to get detailed instructions.
100
101 Usage: SeqSero2S.py
102
103 -m <string> (which workflow to apply, 'a'(raw reads allele micro-assembly), 'k'(raw reads and genome assembly k-mer), default=a)
104
105 -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 reads (fasta/fastq))
106
107 -i <file> (/path/to/input/file)
108
109 -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)
110
111 -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)
112
113 -d <string> (output directory name, if not set, the output directory would be 'SeqSero_result_'+time stamp+one random number)
114
115 -c <flag> (if '-c' was flagged, SeqSero2S will only output serotype prediction without the directory containing log files)
116
117 -n <string> (optional, to specify a sample name in the report output)
118
119 -s <flag> (if '-s' was flagged, SeqSero2S will not output header in SeqSero_result.tsv)
120
121 --check <flag> (use '--check' flag to check the required dependencies)
122
123 -v, --version (show program's version number and exit)
124
125
126 # Examples
127 Allele mode:
128
129 # Allele workflow ("-m a", default), for separated paired-end raw reads ("-t 2"), use 10 threads in mapping and assembly ("-p 10")
130 SeqSero2S.py -p 10 -t 2 -i R1.fastq.gz R2.fastq.gz
131
132 K-mer mode:
133
134 # Raw reads k-mer ("-m k"), for separated paired-end raw reads ("-t 2")
135 SeqSero2S.py -m k -t 2 -i R1.fastq.gz R2.fastq.gz
136
137 # Genome assembly k-mer ("-t 4", genome assemblies only predicted by the k-mer workflow, "-m k")
138 SeqSero2S.py -m k -t 4 -i assembly.fasta
139
140 # Output
141 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).
142
143
144 # Citation
145 Zhang S, Den-Bakker HC, Li S, Dinsmore BA, Lane C, Lauer AC, Fields PI, Deng X.
146 SeqSero2: rapid and improved Salmonella serotype determination using whole genome sequencing data.
147 **Appl Environ Microbiology. 2019 Sep; 85(23):e01746-19.** [PMID: 31540993](https://aem.asm.org/content/early/2019/09/17/AEM.01746-19.long)
148
149 Zhang S, Yin Y, Jones MB, Zhang Z, Deatherage Kaiser BL, Dinsmore BA, Fitzgerald C, Fields PI, Deng X.
150 Salmonella serotype determination utilizing high-throughput genome sequencing data.
151 **J Clin Microbiol. 2015 May;53(5):1685-92.** [PMID: 25762776](http://jcm.asm.org/content/early/2015/03/05/JCM.00323-15)