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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.
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Updated: Apr 24, 2026

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

subSeq: determining appropriate sequencing depth through efficient read subsampling.

David G Robinson¹, John D Storey²

¹Lewis-Sigler Institute for Integrative Genomics and Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA.

Bioinformatics (Oxford, England)

|September 6, 2014

Summary

This summary is machine-generated.

Determining optimal sequencing depth is crucial for RNA-Seq experiments. The subSeq R package efficiently assesses read depth saturation to ensure sufficient data for accurate biological research.

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Area of Science:

Genomics
Bioinformatics

Background:

Next-generation sequencing (NGS), including RNA-Seq, is vital in modern biological research.
Experiment power and accuracy are highly dependent on sequencing read depth.
Establishing optimal read depth is a significant challenge in experimental design.

Purpose of the Study:

To develop a method for determining optimal sequencing depth for RNA-Seq experiments.
To provide a tool for validating adequate read depth in existing experiments.

Main Methods:

Randomly subsampling sequencing data to lower depths.
Analyzing the saturation point of statistical power and accuracy metrics.
Introducing the subSeq R package for efficient subsampling and metric calculation.

Main Results:

The subSeq R package enables determination of the most useful sequencing depth for future experiments.
It allows confirmation of whether existing experiments possess sufficient depth to support their conclusions.
The package employs a novel and efficient subsampling approach.

Conclusions:

Subsampling is an effective strategy for assessing sequencing depth.
The subSeq R package provides a valuable tool for RNA-Seq experimental design and validation.