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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.
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Related Experiment Video

Updated: Oct 23, 2025

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

VariantStore: an index for large-scale genomic variant search.

Prashant Pandey¹, Yinjie Gao¹, Carl Kingsford²

¹Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, USA.

|August 20, 2021

Summary

This summary is machine-generated.

VariantStore efficiently indexes genomic variants from thousands of samples using a variation graph, overcoming reference bias. This enables rapid, flexible variant queries across diverse coordinate systems.

Keywords:

Graph genomes Pangenomes Variation graph

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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

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Last Updated: Oct 23, 2025

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

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

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

Published on: August 21, 2016

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

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Scaling genomic variant indexing to large sample sizes is computationally intensive.
Multiple coordinate systems in genomic data introduce reference biases.
Efficient variant search across diverse samples is crucial for genomic research.

Purpose of the Study:

To present VariantStore, a novel system for indexing and querying genomic variants.
To enable variant searches across multiple sample-specific coordinate systems.
To address the computational challenges of scaling genomic variant indexes.

Main Methods:

Developed VariantStore, a system utilizing a variation graph for indexing.
Indexed genomic variants from large-scale projects like TCGA and 1000 Genomes.
Implemented variant querying across sample-specific coordinate systems.

Main Results:

VariantStore successfully indexed variants from TCGA in 4 hours and 1000 Genomes in 3 hours.
Variant queries in a gene were completed in 0.002 to 3 seconds.
The system used only 10% of the memory required by full data representations.

Conclusions:

VariantStore offers a scalable and efficient solution for genomic variant indexing and querying.
The system effectively handles multiple coordinate systems, reducing reference bias.
VariantStore significantly improves the speed and resource efficiency of large-scale genomic data analysis.