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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...

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Updated: Jul 13, 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

MosaiCatcher v2: a single-cell structural variations detection and analysis reference framework based on Strand-seq.

Thomas Weber¹, Marco Raffaele Cosenza¹, Jan Korbel^1,2

¹European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany.

Bioinformatics (Oxford, England)

|October 18, 2023

Summary

This summary is machine-generated.

MosaiCatcher v2 offers a standardized workflow for detecting structural variations (SV) in single cells using DNA template strand sequencing (Strand-seq). This enhanced framework ensures reproducible computational processing for human genetics and single-cell genomics research.

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Last Updated: Jul 13, 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

Detection of Copy Number Alterations Using Single Cell Sequencing

Detection of Copy Number Alterations Using Single Cell Sequencing

Published on: February 17, 2017

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

Area of Science:

Genomics
Single-cell analysis
Bioinformatics

Background:

Single-cell DNA template strand sequencing (Strand-seq) is a powerful technique for genomic analysis, including haplotype phasing and structural variation (SV) calling.
Existing workflows for Strand-seq data analysis can be complex and lack standardization, hindering reproducibility.

Purpose of the Study:

To present MosaiCatcher v2, a standardized workflow and reference framework for single-cell SV detection using Strand-seq.
To enhance the reproducibility and robustness of computational processing for Strand-seq data.

Main Methods:

Development of an automated upstream Quality Control (QC) and assembly sub-workflow with multistep normalization.
Integration of modules for SV functional characterization and genotyping (ArbiGent).
Implementation using the Snakemake workflow management system for platform portability.

Main Results:

MosaiCatcher v2 provides automated QC, normalization, and SV analysis functionalities.
The framework integrates SV functional characterization and genotyping.
A user-friendly web report is generated for shareable results.

Conclusions:

MosaiCatcher v2 establishes a cornerstone for reproducible computational processing of Strand-seq data.
The framework supports production environments in human genetics and single-cell genomics.
Compatibility with container and conda environments ensures robustness and accessibility.