Rare Variant Analysis
Rare Variant Analysis - Related Videos
14:06
Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
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Cited by 10 •
2012
Pooled DNA sequencing is a fast and cost-effective strategy to detect rare variants associated with complex phenotypes in large cohorts. Here we describe the computational analysis of pooled, next-generation sequencing of 32 cancer-related genes using the SPLINTER software package. This method is scalable, and applicable to any phenotype of interest.
07:50
Chip-Based Digital PCR to Detect Rare Transcript Variants Using a Nanofluidic Chip
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2025
This video demonstrates chip-based digital PCR — a variation of the digital PCR technique that is useful in detecting rare transcript variants. The PCR reaction is partitioned into the chambers of a nanofluidic chip, each of which acts as an independent reaction. The detection of fluorescence signals from the chambers with amplified targets confirms the presence of rare transcript variants in the sample.
00:06
In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila
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Cited by 43 •
2019
The goal of this protocol is to outline the design and performance of in vivo experiments in Drosophila melanogaster to assess the functional consequences of rare gene variants associated with human diseases.
09:25
Detection and Enrichment of Rare Antigen-specific B Cells for Analysis of Phenotype and Function
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Cited by 36 •
2017
A simple yet effective method that employs magnetic nanoparticles to detect and enrich antigen-reactive B cells for functional and phenotypic analysis is described.
02:30
Histone Variants at the Centromere
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2020
Histone variants are the histone proteins with structural and sequence variations. These variants may be regarded as “mutant” forms that replace their canonical histone counterparts in the nucleosomes. Specific post-translational modifications on the histone variants enable further chromatin complexity and regulate tissue-specific gene expression. The most common histone variants are from histone H2A, H2B, and linker histone H1 families. However, several variants of histone H3 variants are also...
FAQs
Population-frequency filtering removes variants that occur too commonly to fit the study’s rare-variant focus, allowing analysts to concentrate on less frequent changes. This step narrows the candidate list before functional annotation and statistical testing. In inherited disease research, the resulting candidates can then be evaluated for possible relationships with disease status, biological traits, or observed genotype–phenotype patterns.
Quality control helps ensure that the variants entering an analysis are supported by reliable sequencing data. Functional annotation adds biological information about those changes, making it easier to organize and prioritize candidates rather than treating every detected variant identically. Together, these steps improve the interpretability of downstream statistical results and support more focused investigation of potential disease-associated variants.
Individual-variant analysis examines the statistical relationship of one rare change with a trait or disease. Because rare changes may each occur too infrequently for strong evidence alone, researchers can also aggregate multiple variants within a gene or pathway. This combined approach evaluates their collective effect and can reveal associations that would be difficult to detect by studying variants separately.
By linking prioritized genetic changes with observed traits, researchers can examine whether particular variants, genes, or pathways correspond to specific phenotypic patterns. Aggregating rare variants within genes or pathways is especially relevant when complex disorders reflect contributions from multiple genetic changes. These analyses can identify candidate genes involved in disease biology and clarify how genetic variation relates to measured outcomes.
A typical workflow begins with DNA sequencing, followed by quality control to assess the reliability of detected changes. Analysts then apply population-frequency filters, annotate variant function, and use statistical methods to test individual variants or aggregate effects within genes and pathways. The final results prioritize candidates for follow-up, including genotype–phenotype evaluation, segregation studies, or diagnostic interpretation.
In research, the approach helps identify genes involved in inherited disease and complex disorders, while also supporting studies of genotype–phenotype relationships. In clinical interpretation, prioritized variants can contribute to diagnostic assessment when considered with other evidence. Family-based segregation studies provide an additional context by examining how candidate variants track with disease within a family.