scispace - formally typeset
Journal ArticleDOI

Sequencing depth and coverage: key considerations in genomic analyses

TLDR
The issue of sequencing depth in the design of next-generation sequencing experiments is discussed and current guidelines and precedents on the issue of coverage are reviewed for four major study designs, including de novo genome sequencing, genome resequencing, transcriptome sequencing and genomic location analyses.
Abstract
Sequencing technologies have placed a wide range of genomic analyses within the capabilities of many laboratories. However, sequencing costs often set limits to the amount of sequences that can be generated and, consequently, the biological outcomes that can be achieved from an experimental design. In this Review, we discuss the issue of sequencing depth in the design of next-generation sequencing experiments. We review current guidelines and precedents on the issue of coverage, as well as their underlying considerations, for four major study designs, which include de novo genome sequencing, genome resequencing, transcriptome sequencing and genomic location analyses (for example, chromatin immunoprecipitation followed by sequencing (ChIP-seq) and chromosome conformation capture (3C)).

read more

Content maybe subject to copyright    Report

Citations
More filters
Journal ArticleDOI

Targeted capture in evolutionary and ecological genomics

TL;DR: This work aims to increase the accessibility of targeted capture to researchers working in nonmodel taxa by discussing capture methods that circumvent the need of a reference genome, and highlight the evolutionary and ecological applications where this approach is emerging as a powerful sequencing strategy.
Journal ArticleDOI

Next maSigPro: updating maSigPro bioconductor package for RNA-seq time series.

TL;DR: This work has updated maSigPro to support RNA-seq time series analysis by introducing generalized linear models in the algorithm to support the modeling of count data while maintaining the traditional functionalities of the package.
Journal ArticleDOI

Bioinformatic processing of RAD-seq data dramatically impacts downstream population genetic inference

TL;DR: It is recommended that RAD‐seq studies employ reference‐based approaches to a closely related genome, and due to the high stochasticity associated with the pipeline advocate the use of multiple pipelines to ensure robust population genetic and demographic inferences.
Journal ArticleDOI

Implementing TMB measurement in clinical practice: considerations on assay requirements

TL;DR: The factors for adoption of TMB measurement into clinical practice are outlined, providing an understanding of T MB assay considerations throughout the sample journey, and principles to effectively implement TMB assays in a clinical setting are suggested to aid and optimise treatment decisions.
References
More filters
Journal ArticleDOI

edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.

TL;DR: EdgeR as mentioned in this paper is a Bioconductor software package for examining differential expression of replicated count data, which uses an overdispersed Poisson model to account for both biological and technical variability and empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference.
Journal ArticleDOI

Initial sequencing and analysis of the human genome.

Eric S. Lander, +248 more
- 15 Feb 2001 - 
TL;DR: The results of an international collaboration to produce and make freely available a draft sequence of the human genome are reported and an initial analysis is presented, describing some of the insights that can be gleaned from the sequence.
Journal ArticleDOI

Differential expression analysis for sequence count data.

Simon Anders, +1 more
- 27 Oct 2010 - 
TL;DR: A method based on the negative binomial distribution, with variance and mean linked by local regression, is proposed and an implementation, DESeq, as an R/Bioconductor package is presented.
Journal ArticleDOI

RNA-Seq: a revolutionary tool for transcriptomics

TL;DR: The RNA-Seq approach to transcriptome profiling that uses deep-sequencing technologies provides a far more precise measurement of levels of transcripts and their isoforms than other methods.
Journal ArticleDOI

TopHat: discovering splice junctions with RNA-Seq

TL;DR: The TopHat pipeline is much faster than previous systems, mapping nearly 2.2 million reads per CPU hour, which is sufficient to process an entire RNA-Seq experiment in less than a day on a standard desktop computer.
Related Papers (5)