The GPS Pipeline is a Nextflow pipeline designed for processing raw reads (FASTQ files) of Streptococcus pneumoniae samples. After preprocessing, the pipeline performs initial assessment based on the total bases in reads. Passed samples will be further assess based on assembly, mapping, and taxonomy. If the sample passes all quality controls (QC), the pipeline also provides the sample's serotype, multi-locus sequence typing (MLST), lineage (based on the Global Pneumococcal Sequence Cluster (GPSC)), and antimicrobial resistance (AMR) against multiple antimicrobials.
The pipeline is designed to be easy to set up and use, and is suitable for use on local machines and high-performance computing (HPC) clusters alike. Additionally, the pipeline only downloads essential files to enable the analysis, and no data is uploaded from the local environment, making it an ideal option for cases where the FASTQ files being analysed is confidential. After initialisation or the first successful complete run, the pipeline can be used offline unless you have changed the selection of any database or container image.
The development of this pipeline is part of the GPS Project (Global Pneumococcal Sequencing Project).
- A POSIX-compatible operating system (e.g. Linux, macOS, Windows with WSL) with Bash 3.2 or later
- Installation guide for WSL on Windows by Microsoft
- Java 11 or later (up to 22) (OpenJDK/Oracle Java)
- Installation guide for OpenJDK by freeCodeCamp
- Docker or Singularity/Apptainer
- Installation guides:
- For Linux
ℹ️ For Linux, Docker Engine or Singularity/Apptainer is recommended. Docker Desktop for Linux is known to cause permission issues on Linux, which could prevent the pipeline from working.
- Docker Engine on Linux by Docker
ℹ️ Make sure you also install
docker-compose-plugin
as per the guide - Apptainer on Linux by Apptainer
- Docker Engine on Linux by Docker
- For macOS
- Docker Desktop on macOS by Docker
ℹ️ After installation, you might need to allow Docker to access more system resources, especially CPU and Memory, to match the hardware requirement of the pipeline
- Docker Desktop on macOS by Docker
- For Windows with WSL
- Docker Desktop on Windows with WSL by Docker
- For Linux
- Installation guides:
It is recommended to have at least 16GB of RAM and 100GB of free storage
ℹ️ Details on storage
- The pipeline core files use ~5MB
- All default databases use ~19GB in total
- All Docker images use ~13GB in total; alternatively, Singularity images use ~4.5GB in total
- The pipeline generates ~1.8GB intermediate files for each sample on average
(These files can be removed when the pipeline run is completed, please refer to Clean Up)
(To further reduce storage requirement by sacrificing the ability to resume the pipeline, please refer to Experimental)
- Only Illumina paired-end short reads are supported
- Each sample is expected to be a pair of raw reads following this file name pattern:
*_{,R}{1,2}{,_001}.{fq,fastq}{,.gz}
- example 1:
SampleName_R1_001.fastq.gz
,SampleName_R2_001.fastq.gz
- example 2:
SampleName_1.fastq.gz
,SampleName_2.fastq.gz
- example 3:
SampleName_R1.fq
,SampleName_R2.fq
- example 1:
-
Clone the repository (if Git is installed on your system)
git clone https://github.com/sanger-bentley-group/gps-pipeline.git
or
Download and unzip/extract the latest release
-
Go into the local directory of the pipeline and it is ready to use without installation (the directory name might be different)
cd gps-pipeline
-
(Optional) You could perform an initialisation to download all required additional files and container images, so the pipeline can be used at any time with or without the Internet afterwards.
⚠️ Docker or Singularity must be running, and an Internet connection is required.- Using Docker as the container engine
./run_pipeline --init
- Using Singularity as the container engine
./run_pipeline --init -profile singularity
- Using Docker as the container engine
⚠️ Docker or Singularity must be running.
⚠️ If this is the first run and initialisation was not performed, an Internet connection is required.
ℹ️ By default, Docker is used as the container engine and all the processes are executed by the local machine. See Profile for details on running the pipeline with Singularity or on a HPC cluster.
- You can run the pipeline without options. It will attempt to get the raw reads from the default location (i.e.
input
directory inside thegps-pipeline
local directory)./run_pipeline
- You can also specify the location of the raw reads by adding the
--reads
option./run_pipeline --reads /path/to/raw-reads-directory
- For a test run, you could obtain a small test dataset by running the included
download_test_input
script. The dataset will be saved to thetest_input
directory inside the pipeline local directory. You can then run the pipeline on the test data./download_test_input ./run_pipeline --reads test_input
9870_5#52
will fail the Taxonomy QC and hence Overall QC, therefore without analysis results17175_7#59
and21127_1#156
should pass Overall QC, therefore with analysis results
- By default, Docker is used as the container engine and all the processes are executed by the local machine. To change this, you could use Nextflow's built-in
-profile
option to switch to other available profilesℹ️
-profile
is a built-in Nextflow option, it only has one leading-
./run_pipeline -profile [profile name]
- Available profiles:
Profile Name Details standard
(Default)Docker is used as the container engine.
Processes are executed locally.singularity
Singularity is used as the container engine.
Processes are executed locally.lsf
The pipeline should be launched from a LSF cluster head node with this profile.
Singularity is used as the container engine.
Processes are submitted to your LSF cluster viabsub
by the pipeline.
(Tested on Wellcome Sanger Institute farm5 LSF cluster only)
(Option--kraken2_memory_mapping
default change tofalse
.)
- If the pipeline is interrupted mid-run, Nextflow's built-in
-resume
option can be used to resume the pipeline execution instead of starting from scratch again - You should use the same command of the original run, only add
-resume
at the end (i.e. all pipeline options should be identical)ℹ️
-resume
is a built-in Nextflow option, it only has one leading-
- If the original command is
./run_pipeline --reads /path/to/raw-reads-directory
- The command to resume the pipeline execution should be
./run_pipeline --reads /path/to/raw-reads-directory -resume
- If the original command is
- During the run of the pipeline, Nextflow generates a considerable amount of intermediate files
- If the run has been completed and you do not intend to use the
-resume
option or those intermediate files, you can remove the intermediate files using one of the following ways:- Run the included
clean_pipeline
script- It runs the commands in manual removal for you
- It removes the
work
directory and log files within thegps-pipeline
local directory
./clean_pipeline
- Manual removal
- Remove the
work
directory and log files within thegps-pipeline
local directory
rm -rf work rm -rf .nextflow.log*
- Remove the
- Run
nextflow clean
command- This built-in command cleans up cache and work directories
- By default, it only cleans up the latest run
- For details and available options of
nextflow clean
, refer to the Nextflow documentation
./nextflow clean
- Run the included
The pipeline is compatible with Launchpad of Seqera Platform (previously known as Nextflow Tower) and Nextflow -with-tower
option. For more information, please refer to the Seqera Platform documentation.
- The tables below contain the available options that can be used when you run the pipeline
- Usage:
./run_pipeline [option] [value]
ℹ️ To permanently change the value of an option, edit the
nextflow.config
file inside thegps-pipeline
local directory.
ℹ️
$projectDir
is a Nextflow built-in implicit variables, it is defined as the local directory ofgps-pipeline
.
ℹ️ Pipeline options are not built-in Nextflow options, they are lead with
--
instead of-
Option | Values | Description |
---|---|---|
--init |
true or false (Default: false ) |
Use alternative workflow for initialisation, which means downloading all required additional files and container images, and creating databases. Can be enabled by including --init without value. |
--version |
true or false (Default: false ) |
Use alternative workflow for showing versions of pipeline, container images, tools and databases. Can be enabled by including --version without value.(This workflow pulls the required container images if they are not yet available locally) |
--help |
true or false (Default: false ) |
Show help message. Can be enabled by including --help without value. |
⚠️ --output
overwrites existing results in the target directory if there is any
⚠️ --db
does not accept user provided local databases, directory content will be overwritten
Option | Values | Description |
---|---|---|
--reads |
Any valid path (Default: "$projectDir/input" ) |
Path to the input directory that contains the reads to be processed. |
--output |
Any valid path (Default: "$projectDir/output" ) |
Path to the output directory that save the results. |
--db |
Any valid path (Default: "$projectDir/databases" ) |
Path to the directory saving databases used by the pipeline. |
--assembly_publish |
"link" or "symlink" or "copy" (Default: "link" ) |
Method used by Nextflow to publish the generated assemblies. (The default setting "link" means hard link, therefore will fail if the output directory is set to outside of the working file system) |
ℹ️ Read QC does not have directly accessible parameters. The minimum base count in reads of Read QC is based on the multiplication of
--length_low
and--depth
of Assembly QC (i.e. default value is38000000
).
Option | Values | Description |
---|---|---|
--spneumo_percentage |
Any integer or float value (Default: 60.00 ) |
Minimum S. pneumoniae percentage in reads to pass Taxonomy QC. |
--non_strep_percentage |
Any integer or float value (Default: 2.00 ) |
Maximum non-Streptococcus genus percentage in reads to pass Taxonomy QC. |
--ref_coverage |
Any integer or float value (Default: 60.00 ) |
Minimum reference coverage percentage by the reads to pass Mapping QC. |
--het_snp_site |
Any integer value (Default: 220 ) |
Maximum non-cluster heterozygous SNP (Het-SNP) site count to pass Mapping QC. |
--contigs |
Any integer value (Default: 500 ) |
Maximum contig count in assembly to pass Assembly QC. |
--length_low |
Any integer value (Default: 1900000 ) |
Minimum assembly length to pass Assembly QC. |
--length_high |
Any integer value (Default: 2300000 ) |
Maximum assembly length to pass Assembly QC. |
--depth |
Any integer or float value (Default: 20.00 ) |
Minimum sequencing depth to pass Assembly QC. |
ℹ️ The output of SPAdes-based assembler is deterministic for a given count of threads. Hence, using
--assembler_thread
with a specific value can guarantee the generated assemblies will be reproducible for others using the same value.
Option | Values | Description |
---|---|---|
--assembler |
"shovill" or "unicycler" (Default: "shovill" ) |
Using which SPAdes-based assembler to assemble the reads. |
--assembler_thread |
Any integer value (Default: 0 ) |
Number of threads used by the assembler. 0 means all available. |
--min_contig_length |
Any integer value (Default: 500 ) |
Minimum legnth of contig to be included in the assembly. |
Option | Values | Description |
---|---|---|
--ref_genome |
Any valid path to a .fa or .fasta file(Default: "$projectDir/data/ATCC_700669_v1.fa" ) |
Path to the reference genome for mapping. |
Option | Values | Description |
---|---|---|
--kraken2_db_remote |
Any valid URL to a Kraken2 database in .tar.gz or .tgz format(Default: Minikraken v1) |
URL to a Kraken2 database. |
--kraken2_memory_mapping |
true or false (Default: true ) |
Using the memory mapping option of Kraken2 or not.true means not loading the database into RAM, suitable for memory-limited or fast storage environments. |
Option | Values | Description |
---|---|---|
--seroba_db_remote |
Any valid URL to a SeroBA release in .tar.gz or .tgz format(Default: SeroBA v1.0.7) |
URL to a SeroBA release. |
--seroba_kmer |
Any integer value (Default: 71 ) |
Kmer size for creating the KMC database of SeroBA. |
Option | Values | Description |
---|---|---|
--poppunk_db_remote |
Any valid URL to a PopPUNK database in .tar.gz or .tgz format(Default: GPS v9) |
URL to a PopPUNK database. |
--poppunk_ext_remote |
Any valid URL to a PopPUNK external clusters file in .csv format(Default: GPS v9 GPSC Designation) |
URL to a PopPUNK external clusters file. |
Option | Values | Description |
---|---|---|
--ariba_ref |
Any valid path to a .fa or .fasta file(Default: "$projectDir/data/ariba_ref_sequences.fasta" ) |
Path to the reference sequences for preparing ARIBA database. |
--ariba_metadata |
Any valid path to a tsv file(Default: "$projectDir/data/ariba_metadata.tsv" ) |
Path to the metadata file for preparing ARIBA database. |
--resistance_to_mic |
Any valid path to a tsv file(Default: "$projectDir/data/resistance_to_MIC.tsv" ) |
Path to the resistance phenotypes to MIC (minimum inhibitory concentration) lookup table. |
ℹ️ This section is only valid when Singularity is used as the container engine
Option | Values | Description |
---|---|---|
--singularity_cachedir |
Any valid path (Default: "$projectDir/singularity_cache" ) |
Path to the directory where Singularity images should be saved to. |
Option | Values | Description |
---|---|---|
--lite |
true or false (Default: false ) |
Reduce storage requirement by removing intermediate .sam and .bam files once they are no longer needed while the pipeline is still running.The quantity of reduction of storage requirement cannot be guaranteed. Can be enabled by including --lite without value. |
- By default, the pipeline outputs the results into the
output
directory inside thegps-pipeline
local directory - It can be changed by adding the option
--output
./run_pipeline --output /path/to/output-directory
- The following directories and files are output into the output directory
Directory / File Description assemblies
This directory contains all assemblies ( .fasta
) generated by the pipelineresults.csv
This file contains all the information generated by the pipeline on each sample info.txt
This file contains information regarding the pipeline and parameters of the run
- The following fields can be found in the output
results.csv
ℹ️ The output fields in Other AMR / Virulence type depends on the provided ARIBA reference sequences and metadata file, and resistance phenotypes to MIC lookup table, the below table is based on the defaults.
ℹ️ The inferred Minimum Inhibitory Concentration (MIC) range of an antimicrobial in "Other AMR" type is only provided if it is included in the resistance phenotypes to MIC lookup table. The default lookup table is based on 2014 CLSI guidelines.
ℹ️ For resistance phenotypes: S = Sensitive/Susceptible; I = Intermediate; R = Resistant
ℹ️ For virulence genes: POS = Positive; NEG = Negative
⚠️ If the result ofOverall_QC
of a sample isREAD_ONE_CORRUPTED
,READ_TWO_CORRUPTED
or both, the specific read file is found to be corrupted (i.e. incomplete/damaged Gzip file, mis-match(s) in read length and quality-score length). You might want to reacquire the read file from its source, or discard the sample if the source file is corrupted as well.⚠️ If the result ofOverall_QC
of a sample isASSEMBLER FAILURE
, the assembler has crashed when trying to assembly the reads. You might want to re-run the sample with another assembler, or discard the sample if it is a low quality one.⚠️ If the result ofSerotype
of a sample isSEROBA FAILURE
, SeroBA has crashed when trying to serotype the sample.Field Type Description Sample_ID
Identification Sample ID based on the raw reads file name Read_QC
QC Read quality control result Assembly_QC
QC Assembly quality control result Mapping_QC
QC Mapping quality control result Taxonomy_QC
QC Taxonomy quality control result Overall_QC
QC Overall quality control result
(Based onAssembly_QC
,Mapping_QC
andTaxonomy_QC
)Bases
Read Number of bases in the reads
(Default: ≥ 38 Mb to pass Read QC)Contigs#
Assembly Number of contigs in the assembly
(Default: ≤ 500 to pass Assembly QC)Assembly_Length
Assembly Total length of the assembly
(Default: 1.9 - 2.3 Mb to pass Assembly QC)Seq_Depth
Assembly Sequencing depth of the assembly
(Default: ≥ 20x to pass Assembly QC)Ref_Cov_%
Mapping Percentage of reference covered by reads
(Default: ≥ 60% to pass Mapping QC)Het-SNP#
Mapping Non-cluster heterozygous SNP (Het-SNP) site count
(Default: ≤ 220 to pass Mapping QC)S.Pneumo_%
Taxonomy Percentage of reads assigned to Streptococcus pneumoniae
(Default: ≥ 60% to pass Taxonomy QC)Top_Non-Strep_Genus
Taxonomy The most abundant non-Streptococcus genus in reads Top_Non-Strep_Genus_%
Taxonomy Percentage of reads assigned to the most abundant non-Streptococcus genus
(Default: ≤ 2% to pass Taxonomy QC)GPSC
Lineage GPSC Lineage Serotype
Serotype Serotype ST
MLST Sequence Type (ST) aroE
MLST Allele ID of aroE gdh
MLST Allele ID of gdh gki
MLST Allele ID of gki recP
MLST Allele ID of recP spi
MLST Allele ID of spi xpt
MLST Allele ID of xpt ddl
MLST Allele ID of ddl pbp1a
PBP AMR Allele ID of pbp1a pbp2b
PBP AMR Allele ID of pbp2b pbp2x
PBP AMR Allele ID of pbp2x AMO_MIC
PBP AMR Estimated minimum inhibitory concentration (MIC) of amoxicillin (AMO) AMO_Res
PBP AMR Inferred resistance phenotype against AMO CFT_MIC
PBP AMR Estimated MIC of ceftriaxone (CFT) CFT_Res(Meningital)
PBP AMR Inferred resistance phenotype against CFT in meningital form CFT_Res(Non-meningital)
PBP AMR Inferred resistance phenotype against CFT in non-meningital form TAX_MIC
PBP AMR Estimated MIC of cefotaxime (TAX) TAX_Res(Meningital)
PBP AMR Inferred resistance phenotype against TAX in meningital form TAX_Res(Non-meningital)
PBP AMR Inferred resistance phenotype against TAX in non-meningital form CFX_MIC
PBP AMR Estimated MIC of cefuroxime (CFX) CFX_Res
PBP AMR Inferred resistance phenotype against CFX MER_MIC
PBP AMR Estimated MIC of meropenem (MER) MER_Res
PBP AMR Inferred resistance phenotype against MER PEN_MIC
PBP AMR Estimated MIC of penicillin (PEN) PEN_Res(Meningital)
PBP AMR Inferred resistance phenotype against PEN in meningital form PEN_Res(Non-meningital)
PBP AMR Inferred resistance phenotype against PEN in non-meningital form CHL_MIC
Other AMR Inferred MIC of Chloramphenicol (CHL) CHL_Res
Other AMR Estimated resistance phenotype against CHL CHL_Determinant
Other AMR Known determinants that estimated the CHL resistance phenotype CLI_MIC
Other AMR Inferred MIC of Clindamycin (CLI) CLI_Res
Other AMR Estimated resistance phenotype against CLI CLI_Determinant
Other AMR Known determinants that estimated the CLI resistance phenotype COT_MIC
Other AMR Inferred MIC of Co-Trimoxazole (COT) COT_Res
Other AMR Estimated resistance phenotype against COT COT_Determinant
Other AMR Known determinants that estimated the COT resistance phenotype DOX_MIC
Other AMR Inferred MIC of Doxycycline (DOX) DOX_Res
Other AMR Estimated resistance phenotype against DOX DOX_Determinant
Other AMR Known determinants that estimated the DOX resistance phenotype ERY_MIC
Other AMR Inferred MIC of Erythromycin (ERY) ERY_Res
Other AMR Estimated resistance phenotype against ERY ERY_Determinant
Other AMR Known determinants that estimated the ERY resistance phenotype ERY_CLI_Res
Other AMR Estimated resistance phenotype against Erythromycin (ERY) and Clindamycin (CLI) ERY_CLI_Determinant
Other AMR Known determinants that estimated the ERY and CLI resistance phenotype FQ_Res
Other AMR Estimated resistance phenotype against Fluoroquinolones (FQ) FQ_Determinant
Other AMR Known determinants that estimated the FQ resistance phenotype KAN_Res
Other AMR Estimated resistance phenotype against Kanamycin (KAN) KAN_Determinant
Other AMR Known determinants that estimated the KAN resistance phenotype LFX_MIC
Other AMR Inferred MIC of Levofloxacin (LFX) LFX_Res
Other AMR Estimated resistance phenotype against LFX LFX_Determinant
Other AMR Known determinants that estimated the LFX resistance phenotype RIF_MIC
Other AMR Inferred MIC of Rifampin (RIF) RIF_Res
Other AMR Estimated resistance phenotype against RIF RIF_Determinant
Other AMR Known determinants that estimated the RIF resistance phenotype SMX_Res
Other AMR Estimated resistance phenotype against Sulfamethoxazole (SMX) SMX_Determinant
Other AMR Known determinants that estimated the SMX resistance phenotype TET_MIC
Other AMR Inferred MIC of Tetracycline (TET) TET_Res
Other AMR Estimated resistance phenotype against TET TET_Determinant
Other AMR Known determinants that estimated the TET resistance phenotype TMP_Res
Other AMR Estimated resistance phenotype against Trimethoprim (TMP) TMP_Determinant
Other AMR Known determinants that estimated the TMP resistance phenotype VAN_MIC
Other AMR Inferred MIC of Vancomycin (VAN) VAN_Res
Other AMR Estimated resistance phenotype against VAN VAN_Determinant
Other AMR Known determinants that estimated the VAN resistance phenotype PILI1
Virulence Expression of PILI-1 PILI1_Determinant
Virulence Known determinants that estimated the PILI-1 expression PILI2
Virulence Expression of PILI-2 PILI2_Determinant
Virulence Known determinants that estimated the PILI-2 expression
This project uses open-source components. You can find the homepage or source code of their open-source projects along with license information below. I acknowledge and am grateful to these developers for their contributions to open source.
- ARIBA: rapid antimicrobial resistance genotyping directly from sequencing reads Hunt M, Mather AE, Sánchez-Busó L, Page AJ, Parkhill J , Keane JA, Harris SR. Microbial Genomics 2017. doi: 110.1099/mgen.0.000131
- License (GPL-3.0): https://github.com/sanger-pathogens/ariba/blob/master/LICENSE
- This tool is used in
GET_ARIBA_DB
andOTHER_RESISTANCE
processes of theamr.nf
module
- Twelve years of SAMtools and BCFtools. Petr Danecek, James K Bonfield, Jennifer Liddle, John Marshall, Valeriu Ohan, Martin O Pollard, Andrew Whitwham, Thomas Keane, Shane A McCarthy, Robert M Davies, Heng Li. GigaScience, Volume 10, Issue 2, February 2021, giab008, https://doi.org/10.1093/gigascience/giab008
- Licenses
- BCFtools (MIT/Expat or GPL-3.0): https://github.com/samtools/bcftools/blob/develop/LICENSE
- SAMtools (MIT/Expat): https://github.com/samtools/samtools/blob/develop/LICENSE
- These tools are used in
SAM_TO_SORTED_BAM
andSNP_CALL
processes of themapping.nf
module
- Li H. (2013) Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv:1303.3997v2 [q-bio.GN]
- License (GPL-3.0): https://github.com/lh3/bwa/blob/master/COPYING
- This tool is used in
GET_REF_GENOME_BWA_DB
andMAPPING
processes of themapping.nf
module
Docker Images of ARIBA, BCFtools, BWA, fastp, Kraken 2, mlst, PopPUNK, QUAST, SAMtools, Shovill, Unicycler
- State Public Health Bioinformatics Workgroup (@StaPH-B)
- License (GPL-3.0): https://github.com/StaPH-B/docker-builds/blob/master/LICENSE
- These Docker images provide containerised environments with different bioinformatics tools for processes of multiple modules
Docker Image of network-multitool
- Wbitt - We Bring In Tomorrow's Technolgies (@WBITT)
- License (MIT): https://github.com/wbitt/Network-MultiTool/blob/master/LICENSE
- This Docker image provides the containerised environment with Bash tools for processes of multiple modules
- Alexander Mancevice (@amancevice)
- License (MIT): https://github.com/amancevice/docker-pandas/blob/main/LICENSE
- This Docker image provides the containerised environment with Python and Pandas for
GENERATE_OVERALL_REPORT
process of theoutput.nf
module,HET_SNP_COUNT
process of themapping.nf
module andPARSE_OTHER_RESISTANCE
process of theamr.nf
module
- Shifu Chen, Yanqing Zhou, Yaru Chen, Jia Gu; fastp: an ultra-fast all-in-one FASTQ preprocessor, Bioinformatics, Volume 34, Issue 17, 1 September 2018, Pages i884–i890, https://doi.org/10.1093/bioinformatics/bty560
- License (MIT): https://github.com/OpenGene/fastp/blob/master/LICENSE
- This tool is used in
PREPROCESS
process of thepreprocess.nf
module
- Victoria Dyster (@blue-moon22)
- License (GPL-3.0): https://github.com/sanger-bentley-group/GPSC_pipeline_nf/blob/master/LICENSE
- Code adapted into the
get_lineage.sh
script
- Wood, D.E., Lu, J. & Langmead, B. Improved metagenomic analysis with Kraken 2. Genome Biol 20, 257 (2019). https://doi.org/10.1186/s13059-019-1891-0
- License (MIT): https://github.com/DerrickWood/kraken2/blob/master/LICENSE
- This tool is used in
TAXONOMY
process of thetaxonomy.nf
module
- Narender Kumar (@kumarnaren)
- License (GPL-3.0): https://github.com/kumarnaren/mecA-HetSites-calculator/blob/master/LICENSE
- Code was rewritten into the
het_snp_count.py
script
- Torsten Seemann (@tseemann)
- License (GPL-2.0): https://github.com/tseemann/mlst/blob/master/LICENSE
- Incorporates components of the PubMLST database
- This tool is used in
MLST
process of themlst.nf
module
- P. Di Tommaso, et al. Nextflow enables reproducible computational workflows. Nature Biotechnology 35, 316–319 (2017) doi:10.1038/nbt.3820
- License (Apache 2.0): https://github.com/nextflow-io/nextflow/blob/master/COPYING
- This project is a Nextflow pipeline; Nextflow executable
nextflow
is included in this repository
- Lees JA, Harris SR, Tonkin-Hill G, Gladstone RA, Lo SW, Weiser JN, Corander J, Bentley SD, Croucher NJ. Fast and flexible bacterial genomic epidemiology with PopPUNK. Genome Research 29:1-13 (2019). doi:10.1101/gr.241455.118
- License (Apache 2.0): https://github.com/bacpop/PopPUNK/blob/master/LICENSE
- This tool is used in
LINEAGE
process of thelineage.nf
module
- Alla Mikheenko, Andrey Prjibelski, Vladislav Saveliev, Dmitry Antipov, Alexey Gurevich, Versatile genome assembly evaluation with QUAST-LG, Bioinformatics (2018) 34 (13): i142-i150. doi: 10.1093/bioinformatics/bty266. First published online: June 27, 2018
- License (GPL-2.0): https://github.com/ablab/quast/blob/master/LICENSE.txt
- This tool is used in
ASSEMBLY_ASSESS
process of theassembly.nf
module
- SeroBA: rapid high-throughput serotyping of Streptococcus pneumoniae from whole genome sequence data. Epping L, van Tonder, AJ, Gladstone RA, GPS Consortium, Bentley SD, Page AJ, Keane JA, Microbial Genomics 2018, doi: 10.1099/mgen.0.000186
- License (GPL-3.0): https://github.com/sanger-pathogens/seroba/blob/master/LICENSE
- This project uses a Docker image of a fork
- The fork provides SeroBA with the latest updates as the original repository is no longer maintained
- The Docker image provides the containerised environment with SeroBA for
GET_SEROBA_DB
andSEROTYPE
processes of theserotype.nf
module
- Narender Kumar (@kumarnaren)
- License (GPL-3.0): https://github.com/kumarnaren/resistanceDatabase/blob/main/LICENSE
sequences.fasta
is renamed toariba_ref_sequences.fasta
and modifiedmetadata.tsv
is renamed toariba_metadata.tsv
and modified- The files are used as the default inputs of
GET_ARIBA_DB
process of theamr.nf
module
- Torsten Seemann (@tseemann)
- License (GPL-3.0): https://github.com/tseemann/shovill/blob/master/LICENSE
- This tool is used in
ASSEMBLY_SHOVILL
process of theassembly.nf
module
- Pathogenwatch (@pathogenwatch-oss)
- License (MIT): https://github.com/pathogenwatch-oss/spn-resistance-pbp/blob/main/LICENSE
- This is a modified version of AMR predictor by Ben Metcalf (@BenJamesMetcalf) at the Centre for Disease Control (CDC)
- This project uses a Docker image of a fork
- The fork changes the Docker image from a Docker executable image to a Docker environment for Nextflow integration
- The Docker image provides the containerised environment with SPN-PBP-MAR for
PBP_RESISTANCE
process of theamr.nf
module
- Wick RR, Judd LM, Gorrie CL, Holt KE. Unicycler: resolving bacterial genome assemblies from short and long sequencing reads. PLoS Comput Biol 2017.
- License (GPL-3.0): https://github.com/rrwick/Unicycler/blob/main/LICENSE
- This tool is used in
ASSEMBLY_UNICYCLER
process of theassembly.nf
module