bakta | standardized annotation of bacterial genomes | Genomics library
kandi X-RAY | bakta Summary
kandi X-RAY | bakta Summary
Comprehensive & taxonomy-independent database Bakta provides a large and taxonomy-independent database using UniProt's entire UniRef protein sequence cluster universe. Thus, it achieves favourable annotations in terms of sensitivity and specificity along the broad continuum ranging from well-studied species to unknown genomes from MAGs. Protein sequence identification Bakta exactly identifies known identical protein sequences (IPS) from RefSeq and UniProt allowing the fine-grained annotation of gene alleles (AMR) or closely related but distinct protein families. This is achieved via an alignment-free sequence identification (AFSI) approach using full-length MD5 protein sequence hash digests. Fast This AFSI approach substantially accellerates the annotation process by avoiding computationally expensive homology searches for identified genes. Thus, Bakta can annotate a typical bacterial genome in 10 ±5 min on a laptop, plasmids in a couple of seconds/minutes. Database cross-references Fostering the FAIR principles, Bakta exploits its AFSI approach to annotate CDS with database cross-references (dbxref) to RefSeq (WP_*), UniRef100 (UniRef100_*) and UniParc (UPI*). By doing so, IPS allow the surveillance of distinct gene alleles and streamlining comparative analysis as well as posterior (external) annotations of putative & hypothetical protein sequences which can be mapped back to existing CDS via these exact & stable identifiers (E. coli gene ymiA ...more). Currently, Bakta identifies ~214.8 mio, ~199 mio and ~161 mio distinct protein sequences from UniParc, UniRef100 and RefSeq, respectively. Hence, for certain genomes, up to 99 % of all CDS can be identified this way, skipping computationally expensive sequence alignments. FAIR annotations To provide standardized annotations adhearing to FAIR principles, Bakta utilizes a versioned custom annotation database comprising UniProt's UniRef100 & UniRef90 protein clusters (FAIR -> DOI/DOI) enriched with dbxrefs (GO, COG, EC) and annotated by specialized niche databases. For each db version we provide a comprehensive log file of all imported sequences and annotations. Small proteins / short open reading frames Bakta detects and annotates small proteins/short open reading frames (sORF) which are not predicted by tools like Prodigal. Expert annotation systems To provide high quality annotations for certain proteins of higher interest, e.g. AMR & VF genes, Bakta includes & merges different expert annotation systems. Currently, Bakta uses NCBI's AMRFinderPlus for AMR gene annotations as well as an generalized protein sequence expert system with distinct coverage, identity and priority values for each sequence, currenlty comprising the VFDB as well as NCBI's BlastRules. Comprehensive workflow Bakta annotates ncRNA cis-regulatory regions, oriC/oriV/oriT and assembly gaps as well as standard feature types: tRNA, tmRNA, rRNA, ncRNA genes, CRISPR, CDS. GFF3 & INSDC conform annotations Bakta writes GFF3 and INSDC-compliant (Genbank & EMBL) annotation files ready for submission (checked via GenomeTools GFF3Validator, table2asn_GFF and ENA Webin-CLI for GFF3 and EMBL file formats, respectively for representative genomes of all ESKAPE species). Bacteria & plasmids only Bakta was designed to annotate bacteria (isolates & MAGs) and plasmids, only. This decision by design has been made in order to tweak the annotation process regarding tools, preferences & databases and to streamline further development & maintenance of the software. Reasoning By annotating bacterial genomes in a standardized, taxonomy-independent, high-throughput and local manner, Bakta aims at a well-balanced tradeoff between fully featured but computationally demanding pipelines like PGAP and rapid highly customizable offline tools like Prokka. Indeed, Bakta is heavily inspired by Prokka (kudos to Torsten Seemann) and many command line options are compatible for the sake of interoperability and user convenience. Hence, if Bakta does not fit your needs, please consider trying Prokka.
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Top functions reviewed by kandi - BETA
- Write a GFF3 file
- Encode the annotations
- Write the signal peptide
- Encode an attribute
- Write an insdc output to a genome
- Extract EC number and EC number from the given notes
- Select the ncrRNA class from a feature
- Revise dbxrefs
- Run diamond search
- Performs overlap filter on a genome
- Run hmmsearch
- Lookup a sequence of features in the database
- Run prediction on sequences_path
- Annotate a sequence of AA
- Check that the database directory exists
- Test whether the dependencies are met
- Writes user protein protein sequences file
- Updates an AMRinder database
- Download a file from Zenodo
- Combine annotation
- Detect feature overlaps between contigs
- Sets up NCBI
- Detect pseudogenes from candidates
- Run ncrna on contigs_path
- Predict ncrRNA regions from contigs_path
- Use blastn to predict features
bakta Key Features
bakta Examples and Code Snippets
Community Discussions
Trending Discussions on bakta
QUESTION
I am getting Error: Cannot find module
(shared the full stack trace at the end) error when trying to test my lambda with sam local invoke
command. Basically, I created a typescript project and using AWS CDK to create my lambda resources.
Here is my project directory structure
...ANSWER
Answered 2021-Mar-19 at 19:44I was referencing my actual src
directory which should be replaced with dist/src
in my case. So, code
parameter should be code: lambda.Code.fromAsset('dist/src')
instead of code: lambda.Code.fromAsset('src')
.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install bakta
Bakta requires a mandatory database which is publicly hosted at Zenodo: Further information is provided in the database section below.
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