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RNA-seq

RNA-seq

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 microarray-based...

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Updated: May 12, 2026

Improving Small RNA-seq: Less Bias and Better Detection of 2'-O-Methyl RNAs

Improving Small RNA-seq: Less Bias and Better Detection of 2'-O-Methyl RNAs

Published on: September 16, 2019

A tool for RNA sequencing sample identity check.

Jinyan Huang¹, Jun Chen, Mark Lathrop

¹School of life science, Tongji University, Shanghai, China.

Bioinformatics (Oxford, England)

|April 6, 2013

Summary

This summary is machine-generated.

RNA sample contamination and swapping can compromise transcriptome studies. IDCheck software integrates RNA sequencing and genotype data to accurately detect sample mix-ups, ensuring reliable gene expression quantitative trait loci (eQTL) analysis.

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Last Updated: May 12, 2026

Improving Small RNA-seq: Less Bias and Better Detection of 2'-O-Methyl RNAs

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Published on: September 16, 2019

Identification of Footprints of RNA:Protein Complexes via RNA Immunoprecipitation in Tandem Followed by Sequencing (RIPiT-Seq)

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Published on: July 10, 2019

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
Bioinformatics
Molecular Biology

Background:

RNA sequencing is crucial for transcriptome analysis and mapping gene expression quantitative trait loci (eQTLs).
Sample contamination or swapping in RNA sequencing poses significant challenges, leading to false discoveries and reduced statistical power.
Combining genetic and RNA sequencing data offers a robust method for identifying sample integrity issues.

Purpose of the Study:

To introduce IDCheck, a novel tool for assessing concordance between genotype and RNA sequencing data.
To provide an efficient method for detecting RNA sample contamination and resolving sample swapping.
To enhance the reliability of downstream analyses in transcriptomics and eQTL studies.

Main Methods:

IDCheck compares RNA sequencing read identity with SNP genotypes.
A likelihood-based method is employed to estimate relevant parameters.
Maximum likelihood estimates are used to identify sample contamination and correct sample pairings.

Main Results:

IDCheck effectively detects sample contamination by comparing genotype and RNA-seq data.
The tool successfully identifies correct sample pairs in cases of sample swapping.
IDCheck offers a convenient and efficient solution for evaluating and resolving sample identity issues.

Conclusions:

IDCheck provides a reliable solution for ensuring sample integrity in RNA sequencing studies.
The tool is essential for accurate gene expression quantitative trait loci (eQTL) mapping and other downstream analyses.
Utilizing IDCheck can prevent erroneous biological conclusions arising from sample mix-ups.