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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)).

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A Cost-Effective Approach to Sequence Hundreds of Complete Mitochondrial Genomes.

TL;DR: The approach discussed in this paper is optimized for sequencing mitochondrial genomes on an Illumina platform and with the proper modifications, could be easily applied to other small genomes and sequencing platforms.

Molecular epidemiology of Staphylococcus epidermidis in prosthetic joint infections

TL;DR: Staphylococcus epidermidis is ubiquitous in the human microbiota, but also an important pathogen in healthcare-associated infections, such as prosthetic joint infections (PJIs), and in this thesis, asp ...
Journal ArticleDOI

Genetic Improvement of Cereals and Grain Legumes.

TL;DR: This Special Issue is an effort to report the genetic improvements by adapting genomic techniques and genomic selection related to higher yields and increased tolerance to biotic and abiotic stresses.
Journal ArticleDOI

Performance Evaluation of Commercial Library Construction Kits for PCR-based Targeted Sequencing Using a Unique Molecular Identifier

TL;DR: This study is the first systematic evaluation of commercial library construction kits for PCR-based targeted deep sequencing utilizing UMIs and suggests the Qiagen HASTP achieved the highest library complexity based on the depth of unique coverage indicating superb library construction efficiency.
References
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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.
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