Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

16.8K
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...
16.8K
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

19.3K
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%...
19.3K
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.9K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.9K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Fast and reliable association discovery in large-scale microbiome studies and meta-analyses using PALM.

bioRxiv : the preprint server for biology·2026
Same author

Incidence and Severity of Postacute Sequelae of SARS-CoV-2 Infection in the Omicron Era: A Prospective Cohort Study.

The Journal of infectious diseases·2026
Same author

Microbiome preterm birth DREAM challenge: Crowdsourcing machine learning approaches to advance preterm birth research.

Cell reports. Medicine·2025
Same author

Durability of 2024-2025 COVID-19 Vaccines Against JN.1 Subvariants.

JAMA internal medicine·2025
Same author

Hypothesis Tests of Indirect Effects for Multiple Mediators.

Statistical methods & applications·2025
Same author

Melody: meta-analysis of microbiome association studies for discovering generalizable microbial signatures.

Genome biology·2025
Same journal

Comparison of methods for assessing effects of risk factors on disease progression in Mendelian randomization under index event bias.

American journal of human genetics·2026
Same journal

Deciding "what" to screen for and "when": The importance of natural history information.

American journal of human genetics·2026
Same journal

Homologous recombination deficiency-driven genomic instability in ovarian cancer as an indicator of BRCA1 and BRCA2 variant pathogenicity.

American journal of human genetics·2026
Same journal

Individuals who deviate from polygenic expectation are enriched for damaging variants in genes linked to rare disease.

American journal of human genetics·2026
Same journal

Integrating social determinants of health and genetic risk in disease risk models.

American journal of human genetics·2026
Same journal

De novo variants in LDB1 are linked to distinct neurodevelopmental phenotypes determined by variant location and differing pathomechanisms.

American journal of human genetics·2026
See all related articles

Related Experiment Video

Updated: Apr 9, 2026

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

15.9K

Meta-analysis for Discovering Rare-Variant Associations: Statistical Methods and Software Programs.

Zheng-Zheng Tang1, Dan-Yu Lin2

  • 1Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN 37203, USA.

American Journal of Human Genetics
|June 23, 2015
PubMed
Summary
This summary is machine-generated.

Meta-analysis of sequencing studies effectively identifies rare variants linked to complex diseases. This approach, using summary statistics, rivals individual participant data analysis in power for genetic association studies.

More Related Videos

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

13.7K
Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
09:34

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

35.0K

Related Experiment Videos

Last Updated: Apr 9, 2026

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

15.9K
Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

13.7K
Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
09:34

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

35.0K

Area of Science:

  • Genomics and Bioinformatics
  • Statistical Genetics
  • Computational Biology

Background:

  • Next-generation sequencing (NGS) is crucial for identifying rare variants associated with complex human diseases.
  • Detecting associations with rare variants necessitates large sample sizes, making meta-analysis essential.
  • Existing meta-analysis methods require comprehensive evaluation for sequencing data.

Purpose of the Study:

  • To provide a comprehensive overview of statistical methods for meta-analysis of sequencing studies.
  • To compare major software packages for rare-variant association meta-analysis.
  • To introduce PreMeta, a tool for integrating incompatible summary statistics.

Main Methods:

  • Discussed calculation of summary statistics, gene-level association tests, and trait transformation.
  • Evaluated fixed-effects vs. random-effects models and conditional analysis for signal removal.
  • Compared four software packages (MASS, RAREMETAL, MetaSKAT, seqMeta) based on methodology, pipeline, and interface.

Main Results:

  • Meta-analysis using properly calculated summary statistics is as powerful as joint individual-participant data analysis.
  • Demonstrated performance of different meta-analysis methods using simulated and empirical data.
  • Highlighted differences in statistical methodology, analysis pipelines, and user interfaces of the compared software.

Conclusions:

  • Meta-analysis is a powerful and efficient strategy for discovering rare-variant associations in complex diseases.
  • PreMeta integrates major meta-analysis tools, enabling consortia to combine diverse summary statistics.
  • The study provides guidance on selecting appropriate methods and software for rare-variant meta-analysis.