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Related Concept Videos

Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
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.
GWAS does not require the identification of the target gene involved in...
Pleiotropy01:33

Pleiotropy

Pleiotropy is the phenomenon in which a single gene impacts multiple, seemingly unrelated phenotypic traits. For example, defects in the SOX10 gene cause Waardenburg Syndrome Type 4, or WS4, which can cause defects in pigmentation, hearing impairments, and an absence of intestinal contractions necessary for elimination. This diversity of phenotypes results from the expression pattern of SOX10 in early embryonic and fetal development. SOX10 is found in neural crest cells that form melanocytes,...
Genetic Variation01:25

Genetic Variation

Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
Genes exist in different versions called alleles, which...
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an organic...

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Related Experiment Video

Updated: May 7, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Maximum parsimony xor haplotyping by sparse dictionary selection.

Abdulkadir Elmas1, Guido H Jajamovich, Xiaodong Wang

  • 1Department of Electrical Engineering, Columbia University, 500 W 120th St, New York, 10027 NY, USA. wangx@ee.columbia.edu.

BMC Genomics
|September 25, 2013
PubMed
Summary

This study introduces a new greedy method for haplotype inference using xor-genotype data. The approach effectively infers haplotype pairs, showing improved accuracy, especially with large datasets and missing data.

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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Related Experiment Videos

Last Updated: May 7, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Area of Science:

  • Genomics
  • Computational Biology

Background:

  • Xor-genotype analysis offers a cost-effective alternative to individual genotype sequencing.
  • Haplotype inference methods are increasingly utilizing xor-genotype data.
  • Inferring haplotype pairs from group xor-genotypes is feasible with limited regular genotypes.

Purpose of the Study:

  • To develop a novel framework for maximum parsimony-based haplotype inference from xor-genotype data.
  • To present a greedy algorithm for accurate haplotype pair inference when combined with sparse regular genotypes.

Main Methods:

  • A maximum parsimony framework utilizing sparse dictionary search.
  • A greedy inference algorithm applied to xor-genotypes augmented with regular genotypes.
  • Performance evaluation on synthetic datasets of varying sizes and comparison with existing methods (PPXH, XOR-HAPLOGEN).

Main Results:

  • The proposed greedy method demonstrates high inference quality across various conditions, particularly for large datasets.
  • Significant performance improvements were observed on the real-world CFTR database.
  • The algorithm maintains accuracy even with missing data and typing errors.

Conclusions:

  • The developed greedy algorithm provides a robust and accurate solution for haplotype inference from xor-genotypes.
  • The method shows superior performance compared to state-of-the-art techniques, especially in large-scale genomic analyses.
  • The algorithm's resilience to data imperfections makes it valuable for practical applications.