BAYSIC statistics

To access cutting-edge analytics on consensus tools, life science contexts and associated fields, you will need to subscribe to our premium service.

Subscribe
info

Citations per year

Citations chart
info

Popular tool citations

chevron_left Variant recalibration chevron_right
Popular tools chart
info

Tool usage distribution map

Tool usage distribution map
info

Associated diseases

Associated diseases

Protocols

To access compelling stats and trends, optimize your time and resources and pinpoint new correlations, you will need to subscribe to our premium service.

Subscribe

BAYSIC specifications

Information


Unique identifier OMICS_03611
Name BAYSIC
Alternative name BAYeSian Integrated Caller
Software type Package/Module
Interface Command line interface
Restrictions to use Academic or non-commercial use
Operating system Unix/Linux, Mac OS, Windows
Programming languages Perl, R
Computer skills Advanced
Stability Stable
Maintained No

Versioning


Add your version

Maintainer


This tool is not available anymore.

Publication for BAYeSian Integrated Caller

BAYSIC in pipeline

2017
PMCID: 5737360
PMID: 29048530
DOI: 10.1093/gbe/evx199

[…] sequences were called using four separate algorithms: gatk, freebayes, platypus, and samtools (; ; ; ). variants were converted to allelic primitives using gatk, and a consensus set was called by baysic using a 0.80 posterior probability (). finally, indels, variants with >10% missing data in the ingroup samples, and variants with more than two alleles were filtered out. we then classified […]


To access a full list of citations, you will need to upgrade to our premium service.

BAYSIC in publications

 (4)
PMCID: 5852328
PMID: 29552334
DOI: 10.1016/j.csbj.2018.01.003

[…] assembled and re-aligned., machine learning methods have been very successful in classification, and variant calling is essentially a classification problem. mutationseq, somaticseq, snooper, and baysic , , , are representative variant callers that apply machine learning methods. mutationseq extracts relevant features on each site and trains four classifiers (random forest, bayesian adaptive […]

PMCID: 5737360
PMID: 29048530
DOI: 10.1093/gbe/evx199

[…] sequences were called using four separate algorithms: gatk, freebayes, platypus, and samtools (; ; ; ). variants were converted to allelic primitives using gatk, and a consensus set was called by baysic using a 0.80 posterior probability (). finally, indels, variants with >10% missing data in the ingroup samples, and variants with more than two alleles were filtered out. we then classified […]

PMCID: 5455959
PMID: 28419349
DOI: 10.1093/molbev/msx123

[…] variants were called separately using gatk, freebayes and samtools (; ; ). these variant call sets were converted to allelic primitives using gatk, and combined into a high credibility set using baysic (). we subsequently removed indels, any sites with more than two alleles, with more than 10% missing data, and any with a site quality lower than a phred score of 40 to produce the final […]

PMCID: 4658170
PMID: 26600436
DOI: 10.1371/journal.pone.0143199

[…] it possible to assess variant calls relative to a set of validated high quality variants. while such frameworks are useful for accessing the results from a single processive analysis, tools such as baysic [] have shown that aggregating variants from multiple variant callers yields an overall improvements in both sensitivity and specificity compared to any individual tool, making it increasingly […]


To access a full list of publications, you will need to upgrade to our premium service.

BAYSIC institution(s)
Baylor Health, Baylor Institute for Immunology Research, Dallas, TX, USA; Genformatic, LLC, Austin, TX, USA

BAYSIC reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review BAYSIC