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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-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...
Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
Chi-square Analysis02:46

Chi-square Analysis

The chi-square test is a statistical hypothesis test. It is used to check whether there is a significant difference between an expected value and an observed value. In the context of genetics, it enables us to either accept or reject a hypothesis, based on how much the observed values deviate from the expected values.
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
Odds Ratio01:09

Odds Ratio

The odds ratio (OR) is a statistical measure used extensively in epidemiology and research to quantify the strength of association between exposure and outcome across different groups. Unlike relative risk, which compares the probabilities of an event occurring, the odds ratio compares the odds of an event occurring in the exposed group to the odds of it occurring in the unexposed group. The odds, in this context, are calculated as the probability of the event happening divided by the...

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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

CNVRuler: a copy number variation-based case-control association analysis tool.

Ji-Hong Kim1, Hae-Jin Hu, Seon-Hee Yim

  • 1Integrated Research Center for Genome Polymorphism, Department of Microbiology, School of Medicine, Catholic University of Korea, Seoul 137-701, Korea.

Bioinformatics (Oxford, England)
|April 28, 2012
PubMed
Summary
This summary is machine-generated.

CNVRuler is a new, user-friendly program for copy number variation (CNV) association studies. It standardizes CNV region definitions and supports various statistical tests, improving upon existing genome-wide association study (GWAS) methods.

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Detection of Rare Mutations in CtDNA Using Next Generation Sequencing
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Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Genome-wide association studies (GWAS) traditionally focus on single nucleotide polymorphisms (SNPs).
  • Copy number variation (CNV) association studies are less established, with a lack of standardized methods for defining CNV regions (CNVRs).
  • Existing tools often lack appropriate CNVR definitions crucial for accurate association analysis.

Purpose of the Study:

  • To introduce CNVRuler, a user-friendly software program designed for CNV-association studies.
  • To provide a standardized approach for defining CNVRs, essential for robust GWAS.
  • To offer flexible analytical options for CNV association analysis.

Main Methods:

  • CNVRuler accepts outputs from 10 common CNV defining algorithms as input.
  • It facilitates the determination of three distinct CNVR definitions.
  • The software integrates four statistical association tests and population stratification options.
  • CNVRuler is built upon the open-source R and Java programming languages.

Main Results:

  • CNVRuler provides a standardized pipeline for CNV-association studies.
  • It enhances the definition and analysis of CNVRs.
  • The software supports diverse statistical approaches for genetic association.

Conclusions:

  • CNVRuler addresses the need for standardized CNV region definitions in GWAS.
  • It offers a versatile and user-friendly platform for CNV association analysis.
  • The program improves the methodology for identifying genetic associations with CNVs.