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Related Experiment Video

Updated: May 24, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Novel tree-based method to generate markers from rare variant data.

Yuan Jiang¹, Jennifer S Brennan, Rose Calixte

¹Department of Epidemiology and Public Health, Yale School of Public Health, School of Medicine, Yale University, 60 College Street, PO Box 208034, New Haven, CT 06520-8034, USA. heping.zhang@yale.edu.

BMC Proceedings

|March 1, 2012

Summary

This summary is machine-generated.

This study introduces a new tree-based method for rare variant analysis, improving detection of gene interactions and identifying associations between FLT1 and Affect phenotype.

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Rare Event Detection Using Error-corrected DNA and RNA Sequencing

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Published on: August 3, 2018

Area of Science:

Genetics
Bioinformatics
Statistical genomics

Background:

Current rare variant analysis methods often collapse variants, potentially losing interaction information.
Analyzing single-nucleotide polymorphism (SNP) interactions directly from data is more biologically intuitive.

Purpose of the Study:

To propose a novel tree-based method for rare variant analysis that detects SNP interactions.
To generate candidate markers by automatically identifying interactions within rare variants.
To assess candidate markers using repeated logistic regressions with phenotype replications.

Main Methods:

A novel tree-based approach to automatically detect SNP interactions.
Generation of candidate markers from rare variants.
Utilizing 200 phenotype replications for marker assessment via logistic regression.

Main Results:

The proposed method shows potential in rare variant analysis.
Correctly identified the association between the FLT1 gene and the Affect phenotype.
Some false positives were observed in the results.

Conclusions:

The novel tree-based method effectively detects SNP interactions for rare variant analysis.
The approach successfully identified a known gene-phenotype association.
Further refinement may be needed to reduce false positives.