All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

AccuCalc: A Python Package for Accuracy Calculation in GWAS

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F23%3A73622300" target="_blank" >RIV/61989592:15310/23:73622300 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.mdpi.com/2073-4425/14/1/123" target="_blank" >https://www.mdpi.com/2073-4425/14/1/123</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.3390/genes14010123" target="_blank" >10.3390/genes14010123</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    AccuCalc: A Python Package for Accuracy Calculation in GWAS

  • Original language description

    The genome-wide association study (GWAS) is a popular genomic approach that identifies genomic regions associated with a phenotype and, thus, aims to discover causative mutations (CM) in the genes underlying the phenotype. However, GWAS discoveries are limited by many factors and typically identify associated genomic regions without the further ability to compare the viability of candidate genes and actual CMs. Therefore, the current methodology is limited to CM identification. In our recent work, we presented a novel approach to an empowered &quot;GWAS to Genes&quot; strategy that we named Synthetic phenotype to causative mutation (SP2CM). We established this strategy to identify CMs in soybean genes and developed a web-based tool for accuracy calculation (AccuTool) for a reference panel of soybean accessions. Here, we describe our further development of the tool that extends its utilization for other species and named it AccuCalc. We enhanced the tool for the analysis of datasets with a low-frequency distribution of a rare phenotype by automated formatting of a synthetic phenotype and added another accuracy-based GWAS evaluation criterion to the accuracy calculation. We designed AccuCalc as a Python package for GWAS data analysis for any user-defined species-independent variant calling format (vcf) or HapMap format (hmp) as input data. AccuCalc saves analysis outputs in user-friendly tab-delimited formats and also offers visualization of the GWAS results as Manhattan plots accentuated by accuracy. Under the hood of Python, AccuCalc is publicly available and, thus, can be used conveniently for the SP2CM strategy utilization for every species.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10608 - Biochemistry and molecular biology

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Genes

  • ISSN

    2073-4425

  • e-ISSN

  • Volume of the periodical

    14

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    CH - SWITZERLAND

  • Number of pages

    13

  • Pages from-to

    "123-1"-"123-13"

  • UT code for WoS article

    000916901900001

  • EID of the result in the Scopus database

    2-s2.0-85146758298