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Updated: Apr 18, 2026

Targeted DNA Methylation Analysis by Next-generation Sequencing

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

TagDust2: a generic method to extract reads from sequencing data.

Timo Lassmann^1,2

¹RIKEN Center for Life Science Technologies (CLST), RIKEN Yokohama Institute, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, 230-0045, Kanagawa, Japan. timolassmann@gmail.com.

BMC Bioinformatics

|January 29, 2015

Summary

This summary is machine-generated.

TagDust2 accurately extracts more high-quality mappable reads from raw next-generation sequencing (NGS) data. This flexible tool automates initial NGS data analysis steps, supporting various library types and read architectures.

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G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome

G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome

Published on: March 22, 2018

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Next-generation sequencing (NGS) data analysis requires extracting mappable reads from raw sequencing output.
Barcodes, adaptors, and sequencing errors complicate the extraction of usable reads.

Purpose of the Study:

To present TagDust2, a novel computational approach for efficient and accurate read extraction in NGS data.
To improve the quality and quantity of mappable reads obtained from raw sequencing data.

Main Methods:

Utilizes a library of hidden Markov models (HMM) for generic read extraction.
Supports multiplexed single-end, paired-end, and unique molecular identifier (UMI) libraries.
Includes post-processing steps for contaminant exclusion and low-complexity sequence filtering.
Features automatic detection of library types.

Main Results:

TagDust2 extracts a higher number of reads with improved quality compared to existing methods.
Successfully processes diverse NGS library architectures, including multiplexed and UMI-containing data.
Automates library type detection for streamlined analysis.

Conclusions:

TagDust2 offers a feature-rich, flexible, and adaptive solution for converting raw NGS reads to mappable reads.
Automates and clarifies initial NGS data analysis steps, enhancing pipeline efficiency.
TagDust2 is freely available for use in bioinformatics workflows.