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RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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Related Experiment Video

Updated: Jul 15, 2025

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

Local read haplotagging enables accurate long-read small variant calling.

Alexey Kolesnikov¹, Daniel Cook¹, Maria Nattestad¹

¹Google Inc, 1600 Amphitheatre Pkwy, Mountain View, CA.

Biorxiv : the Preprint Server for Biology

|September 25, 2023

Summary

This summary is machine-generated.

This study introduces a novel local haplotype approximation for long-read sequencing, enhancing variant calling accuracy across diverse platforms like PacBio and Oxford Nanopore Technologies. This method improves DeepVariant

Keywords:

DeepVariant Long Reads Nanopore PacBio HiFi PacBio Revio Variant Calling

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Related Experiment Videos

Last Updated: Jul 15, 2025

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

Targeted DNA Methylation Analysis by Next-generation Sequencing

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Area of Science:

Genomics and Bioinformatics
Next-Generation Sequencing Technologies

Background:

Long-read sequencing facilitates variant detection in challenging genomic regions and aids clinical genetic diagnosis.
Emerging third-generation sequencing platforms (Pacific Biosciences, Oxford Nanopore Technologies) offer advanced capabilities but require adaptable variant calling methods.
Deep neural network-based variant callers leverage local haplotyping for improved genotyping accuracy with long-reads.

Conclusions:

The developed local haplotype approximation significantly enhances variant calling performance for long-read sequencing.
This method provides a scalable and adaptable solution for diverse sequencing platforms.
The enhanced DeepVariant offers a universal approach for accurate genetic variant detection in clinical and research settings.