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To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes.
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Mutations are heritable changes in an organism’s genome involving alterations in the base sequence of DNA or RNA. These changes can influence cellular processes and phenotypic traits, potentially transforming the unaltered wild type into a mutant form. Such changes, termed forward mutations, are pivotal in shaping the genetic diversity of organisms.RNA viruses exhibit the highest mutation rates due to the absence of robust proofreading mechanisms during genome replication. In contrast,...
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Characterizing Mutational Load and Clonal Composition of Human Blood
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myVCF: a desktop application for high-throughput mutations data management.

Alessandro Pietrelli1,2, Luca Valenti1,3

  • 1Internal Medicine and Metabolic Diseases, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milano, Italy.

Bioinformatics (Oxford, England)
|October 17, 2017
PubMed
Summary
This summary is machine-generated.

myVCF is a new desktop application designed to simplify the management and interpretation of genetic variant data from next-generation sequencing for non-bioinformaticians. It allows researchers to easily explore, query, and visualize mutations, accelerating disease association studies.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Next-generation sequencing (NGS) generates vast amounts of data, posing challenges for non-expert researchers and clinicians.
  • Interpreting genetic variants associated with human diseases requires accessible tools for data management and analysis.

Purpose of the Study:

  • To develop a user-friendly desktop application, myVCF, to facilitate the management and interpretation of NGS data.
  • To provide non-bioinformaticians with tools to access and analyze genetic variants efficiently.

Main Methods:

  • Developed myVCF, a standalone, cross-platform desktop application with a browser interface.
  • Integrated a SQLite database for storing genetic variants and sample genotypes from VCF files.
  • Implemented a search engine for querying variants by chromosomal region, gene, or dbSNP ID.

Main Results:

  • myVCF efficiently manages multiple sequencing projects and annotated VCF files.
  • The application enables flexible data exploration and querying of genetic variants.
  • myVCF generates summary statistics on mutation distribution across samples and the genome/exome.

Conclusions:

  • myVCF empowers end-users without extensive programming or bioinformatics skills to explore, query, visualize, and export mutation data.
  • The platform simplifies the functional interpretation of genetic variants, accelerating research in human diseases.
  • myVCF bridges the gap between complex sequencing data and clinical/research end-users.