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Related Concept Videos

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%...
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,...
Genome Copying Errors02:46

Genome Copying Errors

DNA replication is a well-evolved process that copies millions of base pairs with high fidelity during each cell division. Occasionally a wrong base or a long stretch of wrong bases may get added to the daughter strands. If the errors are left unchecked, cells might accumulate several mutations that might endanger theirĀ  survival. Therefore, the copying errors are checked and repaired at three levels.
Gene Conversion02:08

Gene Conversion

Other than maintaining genome stability via DNA repair, homologous recombination plays an important role in diversifying the genome. In fact, the recombination of sequences forms the molecular basis of genomic evolution. Random and non-random permutations of genomic sequences create a library of new amalgamated sequences. These newly formed genomes can determine the fitness and survival of cells. In bacteria, homologous and non-homologous types of recombination lead to the evolution of new...
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...
Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

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.

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Related Experiment Video

Updated: May 7, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing
09:45

Detection of Copy Number Alterations Using Single Cell Sequencing

Published on: February 17, 2017

A method for calling copy number polymorphism using haplotypes.

Gun Ho Jang1, Jason D Christie, Rui Feng

  • 1Department of Biostatistics and Epidemiology, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania Philadelphia, PA, USA.

Frontiers in Genetics
|September 27, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a novel haplotype-based method for accurately calling copy number polymorphisms (CNPs) by leveraging linkage disequilibrium (LD) information. The method demonstrates improved sensitivity and accuracy in detecting copy number variations (CNVs) compared to existing approaches.

Keywords:
CNPCNVGWAShaplotypeintegrated SNP and CNVjoint SNP and CNV calling

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Characterizing Mutational Load and Clonal Composition of Human Blood
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Characterizing Mutational Load and Clonal Composition of Human Blood

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Last Updated: May 7, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing
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Published on: February 17, 2017

Measuring Single-Cell Mitochondrial DNA Copy Number and Heteroplasmy Using Digital Droplet Polymerase Chain Reaction
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Measuring Single-Cell Mitochondrial DNA Copy Number and Heteroplasmy Using Digital Droplet Polymerase Chain Reaction

Published on: July 12, 2022

Characterizing Mutational Load and Clonal Composition of Human Blood
07:58

Characterizing Mutational Load and Clonal Composition of Human Blood

Published on: July 11, 2019

Area of Science:

  • Human genomics
  • Population genetics
  • Bioinformatics

Background:

  • Single nucleotide polymorphisms (SNPs) and copy number variations (CNVs) are key genomic features.
  • Current genotyping platforms often analyze SNPs and CNVs independently.
  • Integrated analysis of SNPs and CNVs, termed copy number polymorphisms (CNPs), requires advanced methods.

Purpose of the Study:

  • To develop a haplotype-based maximum likelihood method for CNP calling.
  • To integrate multi-locus linkage disequilibrium (LD) information for improved accuracy.
  • To provide a computationally efficient algorithm for CNP detection, even with missing data.

Main Methods:

  • Developed a haplotype-based maximum likelihood model for CNP calling.
  • Utilized multi-locus LD information from population data.
  • Implemented an iterative algorithm for haplotype frequency estimation and CNP calling optimization.
  • Compared performance against established CNV callers like PennCNV, HMM-CNP, segCNV, and cnvHap.

Main Results:

  • The proposed method showed higher sensitivity and accuracy in detecting various CNV regions through simulations.
  • Performance was superior in regions with higher LD, longer CNVs, and common CNVs.
  • Applied to HapMap CEU samples and acute lung injury (ALI) patient data, demonstrating good consistency and accuracy.

Conclusions:

  • Haplotype-based CNP calling effectively utilizes LD information for enhanced accuracy.
  • The developed method offers a sensitive and computationally efficient approach for integrated SNP and CNV analysis.
  • This approach provides a valuable tool for genomic studies requiring precise CNP detection.