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Related Concept Videos

Mutations01:39

Mutations

Overview
Mutations01:35

Mutations

Mutations are changes in the sequence of DNA. These changes can occur spontaneously or they can be induced by exposure to environmental factors. Mutations can be characterized in a number of different ways: whether and how they alter the amino acid sequence of the protein, whether they occur over a small or large area of DNA, and whether they occur in somatic cells or germline cells.
Chromosomal Alterations Are Large-Scale Mutations
While point mutations are changes in a single nucleotide in...
Mutations01:39

Mutations

Overview
Point and Frameshift Mutations01:30

Point and Frameshift Mutations

Point mutations are genetic alterations involving the change of a single nucleotide base pair in DNA. Depending on how the alteration affects protein synthesis, they can lead to various consequences.Point mutations fall into the following types:Silent mutations occur when a nucleotide change does not alter the amino acid sequence due to the redundancy of the genetic code. For instance, changing ACC to ACA still encodes threonine, leaving the protein function unaffected. This occurs because...
Mutations in Microorganisms01:18

Mutations in Microorganisms

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,...
Next-generation Sequencing03:00

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.

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Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors
11:15

Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors

Published on: September 20, 2016

GAMES identifies and annotates mutations in next-generation sequencing projects.

Maria Elena Sana1, Maria Iascone, Daniela Marchetti

  • 1DAMA, Data Mining for Analysis of DNA, Department of Morphology and Embryology and TecnoPolo for Life Sciences, University of Ferrara, Ferrara, Italy.

Bioinformatics (Oxford, England)
|October 26, 2010
PubMed
Summary
This summary is machine-generated.

Genomic Analysis of Mutations Extracted by Sequencing (GAMES) simplifies complex next-generation sequencing data. This pipeline effectively reduces complexity for large-scale DNA sequencing projects, aiding researchers in data interpretation.

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Using Next Generation Sequencing to Identify Mutations Associated with Repair of a CAS9-induced Double Strand Break Near the CD4 Promoter
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Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors
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Using Next Generation Sequencing to Identify Mutations Associated with Repair of a CAS9-induced Double Strand Break Near the CD4 Promoter
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Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing

Published on: October 18, 2013

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Next-generation sequencing (NGS) generates vast amounts of data, posing challenges in analysis and interpretation.
  • Existing software for NGS data analysis often provides insufficient annotation and lacks functional comprehension for end-users.
  • Effective tools are needed to bridge the gap between raw sequencing data and actionable biological insights.

Purpose of the Study:

  • To develop an efficient bioinformatics pipeline for analyzing and interpreting next-generation sequencing data.
  • To reduce the complexity of large-scale DNA sequencing projects for researchers.
  • To provide enhanced annotation and functional comprehension of sequencing data.

Main Methods:

  • Development of the GAMES (Genomic Analysis of Mutations Extracted by Sequencing) pipeline.
  • Implementation of multiple filtering and annotation levels, including read alignment, quality control, and mutational analysis.
  • Integration of results with genome annotations and matching variations to known polymorphisms.
  • Utilizing diverse approaches for predicting functional mutations.

Main Results:

  • GAMES provides a comprehensive analysis pipeline for NGS data, acting as an intermediary between data and investigators.
  • The pipeline performs detailed filtering, annotation, and quality control, including aligning reads to a reference genome.
  • GAMES effectively reduces complexity by sorting mismatches/deletions, matching variations to polymorphisms, and predicting functional mutations.

Conclusions:

  • GAMES offers an efficient solution for managing and interpreting large-scale DNA sequencing data.
  • The pipeline enhances the usability of NGS data through advanced annotation and functional prediction.
  • GAMES facilitates a more effective complexity reduction in genomic analysis projects for academic users.