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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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Je, a versatile suite to handle multiplexed NGS libraries with unique molecular identifiers

TL;DR: Je is a suite of tools that accommodates complex barcoding strategies, extracts UMIs and filters read duplicates taking UMIs into account, and increased the number of unique reads by up to 36 %, compared to when UMIs are ignored.
Journal ArticleDOI

Guidelines for the selection of functional assays to evaluate the hallmarks of cancer

TL;DR: This work reviews the methods tailored to experimental cancer researchers to evaluate cell proliferation, programmed cell death, replicative immortality, induction of angiogenesis, invasion and metastasis, genome instability, and reprogramming of energy metabolism.
Journal ArticleDOI

Beyond Biodiversity: Can Environmental DNA (eDNA) Cut It as a Population Genetics Tool?

TL;DR: Current research that employs eDNA approaches for the study of populations is reviewed, challenges facing eDNA-based population genetic methodologies are outlined, and avenues of research for future developments are suggested.
Journal ArticleDOI

Inter-laboratory evaluation of SNP-based forensic identification by massively parallel sequencing using the Ion PGM™

TL;DR: In this paper, the authors evaluated the levels of sequence coverage, genotyping precision, sensitivity and mixed DNA patterns of a prototype version of the first commercial forensic NGS kit: the HID-Ion AmpliSeq™ Identity Panel with 169-markers designed for the Ion PGM™ system.
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Potential of genotyping-by-sequencing for genomic selection in livestock populations.

TL;DR: The accuracy of predictions is improved by increasing the size of training populations and the intensity of selection is increased by genotyping a larger number of selection candidates.
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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