A multi-core Multilocus Sequence Typing tool coupled with allele concatenation.
FastMLST is a high speed standalone script wrote in Python3, which takes assemblies in FASTA format (gzipped is also allowed) and determines its ST according to MLST schemes defined in PubMLST. The main advantage over other ST determination programs is that FastMLST allows the generation of a FASTA file containing the concatenated alleles for all analyzed genomes ready to be aligned and used in phylogenetic inference.
You can read a complete guide to MLST analysis in our Wiki.
You can install FastMLST using either Conda or pip. If you want the most up-to-date version, you can install it directly from GitHub using pip.
conda config --add channels defaults
conda config --add channels conda-forge
conda config --add channels bioconda
conda install fastmlstTo install the latest version directly from GitHub, use the following command:
pip install git+https://github.com/EnzoAndree/FastMLST.gitIt is expected that all dependencies will be resolved when using conda for installation.
- Python > 3
- Biopython
- tqdm
- pandas
- NCBI BLAST+
$ fastmlst cdiff_refferences/RT078_CDM120.fasta
RT078_CDM120.fasta,cdifficile,11,adk(5),atpA(8),dxr(5),glyA(11),recA(9),sodA(11),tpi(8),mlst_clade(5.0)
$ fastmlst cdiff_refferences/RT078_CDM120.fasta.gz
RT078_CDM120.fasta.gz,cdifficile,11,adk(5),atpA(8),dxr(5),glyA(11),recA(9),sodA(11),tpi(8),mlst_clade(5.0)
$ fastmlst cdiff_refferences/*.fasta
RT001_BI9.fasta,cdifficile,3,adk(1),atpA(1),dxr(2),glyA(1),recA(1),sodA(1),tpi(1),mlst_clade(1.0)
RT001_Liv24.fasta,cdifficile,3,adk(1),atpA(1),dxr(2),glyA(1),recA(1),sodA(1),tpi(1),mlst_clade(1.0)
RT002_TL178.fasta,cdifficile,8,adk(1),atpA(1),dxr(2),glyA(6),recA(1),sodA(5),tpi(1),mlst_clade(1.0)
RT012_CD630_chr_V12.fasta,cdifficile,54,adk(1),atpA(4),dxr(7),glyA(1),recA(1),sodA(3),tpi(3),mlst_clade(1.0)
RT014_TL176_v3.fasta,cdifficile,13,adk(1),atpA(1),dxr(6),glyA(1),recA(5),sodA(3),tpi(1),mlst_clade(1.0)
RT015_TL174.fasta,cdifficile,44,adk(2),atpA(5),dxr(2),glyA(1),recA(1),sodA(3),tpi(1),mlst_clade(1.0)
RT017_CF5.fasta,cdifficile,86,adk(3),atpA(7),dxr(3),glyA(8),recA(6),sodA(19),tpi(11),mlst_clade(4.0)
RT017_M68.fasta,cdifficile,37,adk(3),atpA(7),dxr(3),glyA(8),recA(6),sodA(9),tpi(11),mlst_clade(4.0)
RT023_CD305.fasta,cdifficile,791,adk(65),atpA(1),dxr(4),glyA(7),recA(2),sodA(8),tpi(7),mlst_clade(nan)
RT027_CD196.fasta,cdifficile,1,adk(1),atpA(1),dxr(1),glyA(10),recA(1),sodA(3),tpi(5),mlst_clade(2.0)
RT027_R20291_July2013.fasta,cdifficile,1,adk(1),atpA(1),dxr(1),glyA(10),recA(1),sodA(3),tpi(5),mlst_clade(2.0)
RT078_CDM120.fasta,cdifficile,11,adk(5),atpA(8),dxr(5),glyA(11),recA(9),sodA(11),tpi(8),mlst_clade(5.0)
RT106_Liv22.fasta,cdifficile,42,adk(1),atpA(1),dxr(2),glyA(1),recA(1),sodA(7),tpi(1),mlst_clade(1.0)
FastMLST uses as input a assembly in FASTA format. Optionally it can be compressed with gzip or bzip2.
$ fastmlst cdiff_refferences/RT078_CDM120.fasta
RT078_CDM120.fasta,cdifficile,11,adk(5),atpA(8),dxr(5),glyA(11),recA(9),sodA(11),tpi(8),mlst_clade(5.0)
The output is a comma separated file (csv) by default, but it can be modified using the -s option.
$ fastmlst -s '\t' cdiff_refferences/RT078_CDM120.fasta
RT078_CDM120.fasta cdifficile 11 adk(5) atpA(8) dxr(5) glyA(11) recA(9) sodA(11) tpi(8) mlst_clade(5.0)
There are two options for saving the result in a text file:
$ fastmlst -to mlst.csv cdiff_refferences/RT078_CDM120.fasta
$ fastmlst cdiff_refferences/RT078_CDM120.fasta > mlst.csv
Both options generate the mlst.csv file containing the FastMLST result.
FastMLST is able to generate a file in FASTA format with the alleles concatenated in the same way as they are in PubMLST. If any genome is not found in this result, it means that (1) Allele contain Ns, (2) alleles missing or (3) contamination (multiple alleles for one genome). Optionally the name could be modified with -fo option:
$ fastmlst cdiff_refferences/RT078_CDM120.fasta
FastMLST will try to use all available cores. It can be modified with -t option:
$ fastmlst -t 2 cdiff_refferences/RT078_CDM120.fasta
You also can specify to FastMLST the scheme name using the --scheme option, this is particularly useful when there is more than one scheme per species. If you use this option, it will generate a table with a new format (available since version 0.0.10) which is easier to use in other programs like phyloviz.
$ fastmlst --scheme cdifficile cdiff_refferences/RT078_CDM120.fasta
Genome,Scheme,ST,adk,atpA,dxr,glyA,recA,sodA,tpi,mlst_clade
RT078_CDM120.fasta,cdifficile,11,5,8,5,11,9,11,8,5.0
If you want the old format just add the option --legacy:
$ fastmlst --legacy --scheme cdifficile cdiff_refferences/RT078_CDM120.fasta
RT078_CDM120.fasta,cdifficile,11,adk(5),atpA(8),dxr(5),glyA(11),recA(9),sodA(11),tpi(8),mlst_clade(5.0)
A list of schemes supported is displayed with the option --scheme-list in the following format (n) code_name: Full species name
Hint: You must use just the code_name in the --scheme option.
$ fastmlst --scheme-list
There are 153 schemes (A round of applause to @keithajolley! (Jolley, et al., 2018)):
(1) achromobacter: Achromobacter spp.
(2) abaumannii#1: Acinetobacter baumannii#1
(3) abaumannii#2: Acinetobacter baumannii#2
(n) (...)
(151) xfastidiosa: Xylella fastidiosa
(152) ypseudotuberculosis: Yersinia pseudotuberculosis
(153) yruckeri: Yersinia ruckeri
A new option in version v0.0.14 is the possibility to obtain the alleles divided into individual FASTA files (one for each allele in the scheme), ready to be used in other programs such as MLSTest.
$ fastmlst --scheme cdifficile cdiff_refferences/*.fasta --splited-output splited_mlst
Genome,Scheme,ST,adk,atpA,dxr,glyA,recA,sodA,tpi,mlst_clade
RT001_BI9.fasta,cdifficile,3,1,1,2,1,1,1,1,1.0
RT001_Liv24.fasta,cdifficile,3,1,1,2,1,1,1,1,1.0
RT002_TL178.fasta,cdifficile,8,1,1,2,6,1,5,1,1.0
RT012_CD630_chr_V12.fasta,cdifficile,54,1,4,7,1,1,3,3,1.0
RT014_TL176_v3.fasta,cdifficile,13,1,1,6,1,5,3,1,1.0
RT015_TL174.fasta,cdifficile,44,2,5,2,1,1,3,1,1.0
RT017_CF5.fasta,cdifficile,86,3,7,3,8,6,19,11,4.0
RT017_M68.fasta,cdifficile,37,3,7,3,8,6,9,11,4.0
RT023_CD305.fasta,cdifficile,791,65,1,4,7,2,8,7,
RT027_CD196.fasta,cdifficile,1,1,1,1,10,1,3,5,2.0
RT027_R20291_July2013.fasta,cdifficile,1,1,1,1,10,1,3,5,2.0
RT078_CDM120.fasta,cdifficile,11,5,8,5,11,9,11,8,5.0
RT106_Liv22.fasta,cdifficile,42,1,1,2,1,1,7,1,1.0
$ ls splited_mlst/
adk.fasta atpA.fasta dxr.fasta glyA.fasta recA.fasta sodA.fasta tpi.fasta
$ cat splited_mlst/adk.fasta
>RT001_BI9.fasta adk
CATATATCAACAGGAGATATATTCAGAAAGAATATAAAAGAGGGAACAGAACTTGGAAAA
AAAGCTAAAGAATACATGGACCAAGGTTTATTAGTACCAGATGAGTTAACTGTAGGTTTA
GTTACTGATAGAATATCTCAAGAAGATTGTAAAAATGGATTTATGTTAGATGGATTTCCA
AGAAATGTAGCACAAGGAGAACATTTAGATATCTTCTTAAAAAATGCTGGTATATCACTA
GATAAAGTTGTCAATATTGAAGTTGATAAGAGTATATTAGTGTCTAGAGCAGTTGGTAGA
AGAATATGTAAGTCTTGTGGAGCTACTTACCATGTTGAGTTTAATCCTCCTAAAGTAGAA
GGTGTATGTGATGTATGCCAAGGAGAATTATATCAAAGAGCTGATGATAATGAAGAAACT
GTATCTAAGAGAATACAAGTTTATCTAGATGAAACTAAGCCTTTAGTAGATTATTATAGC
AAACAAGGTATAATAGCAGAT
...
>RT106_Liv22.fasta adk
CATATATCAACAGGAGATATATTCAGAAAGAATATAAAAGAGGGAACAGAACTTGGAAAA
AAAGCTAAAGAATACATGGACCAAGGTTTATTAGTACCAGATGAGTTAACTGTAGGTTTA
GTTACTGATAGAATATCTCAAGAAGATTGTAAAAATGGATTTATGTTAGATGGATTTCCA
AGAAATGTAGCACAAGGAGAACATTTAGATATCTTCTTAAAAAATGCTGGTATATCACTA
GATAAAGTTGTCAATATTGAAGTTGATAAGAGTATATTAGTGTCTAGAGCAGTTGGTAGA
AGAATATGTAAGTCTTGTGGAGCTACTTACCATGTTGAGTTTAATCCTCCTAAAGTAGAA
GGTGTATGTGATGTATGCCAAGGAGAATTATATCAAAGAGCTGATGATAATGAAGAAACT
GTATCTAAGAGAATACAAGTTTATCTAGATGAAACTAAGCCTTTAGTAGATTATTATAGC
AAACAAGGTATAATAGCAGAT
FastMLST now supports configuring a custom location for the PubMLST database. By default, the tool uses a cache directory at ~/.cache/fastmlst/pubmlst. However, if you prefer to store the database in an alternate location (for example, on a high-performance drive or in a centralized directory), you can override this default path using the --db_path command-line argument.
When the --db_path option is provided, FastMLST calls a helper function (set_pathdb) that:
- Overrides the default database path: The internal global
pathdbvariable is updated to use your specified path. - Ensures the custom directory exists: The directory is automatically created if it does not exist.
- Uses the custom path for all subsequent operations: All processes (such as fetching, updating, or reading database files) use the new path.
To run FastMLST with a custom MLST database directory, simply use the --db_path option:
$ fastmlst --db_path /path/to/your/custom/db [other-options] genomes...For instance, if you want the MLST database to reside in /data/fastmlst_db, run:
$ fastmlst --db_path /data/fastmlst_db cdiff_refferences/RT078_CDM120.fasta- Optimizing I/O Performance: Place the database on a disk with faster read/write speeds.
- Managing Disk Usage: Store the database on a separate partition or drive with more available space.
- Custom Deployment Setups: Particularly useful in multi-user or cluster environments where centralized data management is preferred.
Note: Ensure that the directory you specify has proper write permissions. FastMLST will automatically create the directory (and any necessary parent directories) if they do not already exist.
| Symbol | Meaning | Length | Identity |
|---|---|---|---|
n |
Exact intact allele | 100% | 100% |
~n |
Novel full length allele similar to n | 100% | ≥ -pid |
n? |
Partial match to known allele | ≥ -cov |
≥ -pid |
- |
Allele missing (or allele containing Ns) | < -cov |
< -pid |
n,m |
Multiple alleles |
FastMLST uses a scoring system to determine the scheme to be employed similar to that proposed by Tseemann. The score for a scheme with N alleles is as follows:
- +100/N points for an exact allele match e.g.
1 - +70/N points for a novel allele match e.g.
~1 - +20/N points for a partial allele match e.g.
1? - 0 points for a missing allele e.g.
-
You should always, always, always keep the PubMLST database updated. Fortunately there is a function to simply update the database:
$ fastmlst --update-mlst
You can indicate how many schemes will be downloaded in parallel with -t option if you want more download speed.
$ fastmlst --update-mlst -t 24
usage: fastmlst [-h] [-t THREADS] [-v {0,1,2}] [-s SEPARATOR] [-sch SCHEME] [--scheme-list] [-fo FASTAOUTPUT] [-to TABLEOUTPUT] [-cov COVERAGE] [-pid IDENTITY] [--update-mlst]
[-sp SPLITED_OUTPUT] [--fasta2line] [--longheader] [--legacy] [-n NOVEL] [-V] [--db_path DB_PATH]
[genomes ...]
⚡️🧬 FastMLST: A multi-core tool for multilocus sequence typing of draft genome assemblies
positional arguments:
genomes
options:
-h, --help show this help message and exit
-t THREADS, --threads THREADS
Number of threads to use (default 14)
-v {0,1,2}, --verbose {0,1,2}
Verbose output level choices: [0, 1, 2]
-s SEPARATOR, --separator SEPARATOR
Choose a character to use as a separator (default ",")
-sch SCHEME, --scheme SCHEME
Set a scheme target (I am not dumb, let me choose a scheme by myself!)
--scheme-list Show all schemes supported
-fo FASTAOUTPUT, --fastaoutput FASTAOUTPUT
File name of the concatenated alleles output (default "")
-to TABLEOUTPUT, --tableoutput TABLEOUTPUT
File name of the MLST table output (default STDOUT)
-cov COVERAGE, --coverage COVERAGE
DNA %Cov to report high quality partial allele [?] (default 99%)
-pid IDENTITY, --identity IDENTITY
DNA %Identity of full allelle to consider 'similar' [~] (default 95%)
--update-mlst Perform an update of the PubMLST database
-sp SPLITED_OUTPUT, --splited-output SPLITED_OUTPUT
Directory output for splited alleles (default "")
--fasta2line The fasta files will be in fasta2line format
--longheader If --longheader is invoked, the header of FASTA file contain a long description
--legacy If --legacy is invoked, the csv reported contain the gene name and the allele id in the row [adk(1),atpA(4),dxr(7),glyA(1),recA(1),sodA(3),tpi(3)]. This option
is only available when the --scheme is defined
-n NOVEL, --novel NOVEL
File name of the novel alleles
-V, --version Show program's version number and exit
--db_path DB_PATH Custom directory for MLST database (default: ~/.cache/fastmlst/pubmlst)
Guerrero-Araya E, Muñoz M, Rodríguez C, Paredes-Sabja D. FastMLST: A Multi-core Tool for Multilocus Sequence Typing of Draft Genome Assemblies. Bioinform Biol Insights. 2021 Nov 27;15:11779322211059238. doi: 10.1177/11779322211059238. PMID: 34866905; PMCID: PMC8637782.
