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Related Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.In the early 20th century,...
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Updated: Jun 9, 2026

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Haplotype inference constrained by plausible haplotype data.

Michael R Fellows1, Tzvika Hartman, Danny Hermelin

  • 1Charles Darwin University, Darwin, NT Australia. michael.fellows@cdu.edu.au

IEEE/ACM Transactions on Computational Biology and Bioinformatics
|August 25, 2010
PubMed
Summary
This summary is machine-generated.

This study introduces a constrained haplotype inference problem (HIP) to ensure plausible haplotypes. New algorithms are developed for constrained perfect phylogeny haplotyping and constrained parsimony haplotyping, improving genetic analysis.

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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Genetics

Background:

  • Haplotype inference is crucial for understanding genetic variations and diseases.
  • Existing methods can generate implausible, rare, or unobserved haplotypes.
  • The perfect phylogeny and pure parsimony models are established frameworks for haplotype inference.

Purpose of the Study:

  • To address the limitation of implausible haplotypes in genetic analysis.
  • To introduce and study a constrained version of the haplotype inference problem.
  • To develop algorithms for constrained perfect phylogeny haplotyping (CPPH) and constrained parsimony haplotyping (CPH).

Main Methods:

  • Introducing a constraint where a pool of plausible haplotypes is provided.
  • Developing polynomial-time algorithms for restricted cases of CPPH.
  • Analyzing CPH for fixed-parameter tractability concerning the solution set size.

Main Results:

  • Initial insights and algorithms for CPPH in specific scenarios.
  • Demonstration that CPH is fixed-parameter tractable when parameterized by the solution set size.
  • A novel approach to ensure haplotype plausibility in genetic studies.

Conclusions:

  • The constrained haplotype inference problem offers a more biologically relevant approach.
  • The developed algorithms provide efficient solutions for specific constrained haplotyping scenarios.
  • This research contributes to more accurate and reliable genetic mutation and disease investigations.