scholarly journals A Bayes factor approach with informative prior for rare genetic variant analysis from next generation sequencing data

Biometrics ◽  
2020 ◽  
Author(s):  
Jingxiong Xu ◽  
Wei Xu ◽  
Laurent Briollais
Keyword(s):  
Next Generation Sequencing ◽  
Bayes Factor ◽  
Genetic Variant ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Sequencing Data ◽  
Rare Genetic Variant ◽  
Informative Prior ◽  
Variant Analysis ◽  
Generation Sequencing

A Benchmark of Structural Variant Analysis Tools for Next Generation Sequencing Data

2013 ◽  
Vol 2 (4) ◽  
pp. 86-98
Author(s):  
Chatzinikolaou Panagiotis ◽  
Makris Christos ◽  
Dimitrios Vlachakis ◽  
Sophia Kossida
Keyword(s):  
Next Generation Sequencing ◽  
Level Structure ◽  
Atomic Level ◽  
Protein Sequencing ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Sequencing Data ◽  
Variant Analysis ◽  
Generation Sequencing

In language of genetics and biochemistry, sequencing is the determination of an unbranched biopolymer's primary structure. A sequence is a symbolic linear depiction, result of sequencing. This sequence is a succinct summary of the most of the sequenced molecule's atomic-level structure. (Most known is DNA-sequencing, RNA-sequencing, Protein-sequencing and Next-Generation-sequencing)

scholarly journals SMN1 copy‐number and sequence variant analysis from next‐generation sequencing data

2020 ◽  
Vol 41 (12) ◽  
pp. 2073-2077
Author(s):  
Daniel Lopez‐Lopez ◽  
Carlos Loucera ◽  
Rosario Carmona ◽  
Virginia Aquino ◽  
Josefa Salgado ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Copy Number ◽  
Next Generation Sequencing Data ◽  
Sequence Variant ◽  
Next Generation ◽  
Sequencing Data ◽  
Variant Analysis ◽  
Generation Sequencing

scholarly journals An integrative variant analysis suite for whole exome next-generation sequencing data

2012 ◽  
Vol 13 (1) ◽  
pp. 8 ◽  
Author(s):  
Danny Challis ◽  
Jin Yu ◽  
Uday S Evani ◽  
Andrew R Jackson ◽  
Sameer Paithankar ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Sequencing Data ◽  
Whole Exome ◽  
Variant Analysis ◽  
Generation Sequencing

scholarly journals NGSremix: A software tool for estimating pairwise relatedness between admixed individuals from next-generation sequencing data

2021 ◽  
Author(s):  
Anne Krogh Nøhr ◽  
Kristian Hanghøj ◽  
Genis Garcia Erill ◽  
Zilong Li ◽  
Ida Moltke ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Genetic Research ◽  
Likelihood Estimation ◽  
Software Tool ◽  
Estimation Methods ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Sequencing Data ◽  
Ngs Data ◽  
Generation Sequencing

Abstract Estimation of relatedness between pairs of individuals is important in many genetic research areas. When estimating relatedness, it is important to account for admixture if this is present. However, the methods that can account for admixture are all based on genotype data as input, which is a problem for low-depth next-generation sequencing (NGS) data from which genotypes are called with high uncertainty. Here we present a software tool, NGSremix, for maximum likelihood estimation of relatedness between pairs of admixed individuals from low-depth NGS data, which takes the uncertainty of the genotypes into account via genotype likelihoods. Using both simulated and real NGS data for admixed individuals with an average depth of 4x or below we show that our method works well and clearly outperforms all the commonly used state-of-the-art relatedness estimation methods PLINK, KING, relateAdmix, and ngsRelate that all perform quite poorly. Hence, NGSremix is a useful new tool for estimating relatedness in admixed populations from low-depth NGS data. NGSremix is implemented in C/C ++ in a multi-threaded software and is freely available on Github https://github.com/KHanghoj/NGSremix.

scholarly journals recoup: flexible and versatile signal visualization from next generation sequencing

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Panagiotis Moulos
Keyword(s):  
Next Generation Sequencing ◽  
Next Generation Sequencing Data ◽  
Special Focus ◽  
Next Generation ◽  
Sequencing Data ◽  
User Friendliness ◽  
Computational Environment ◽  
Level Data ◽  
Data Signal ◽  
Generation Sequencing

Abstract Background The relentless continuing emergence of new genomic sequencing protocols and the resulting generation of ever larger datasets continue to challenge the meaningful summarization and visualization of the underlying signal generated to answer important qualitative and quantitative biological questions. As a result, the need for novel software able to reliably produce quick, comprehensive, and easily repeatable genomic signal visualizations in a user-friendly manner is rapidly re-emerging. Results recoup is a Bioconductor package for quick, flexible, versatile, and accurate visualization of genomic coverage profiles generated from Next Generation Sequencing data. Coupled with a database of precalculated genomic regions for multiple organisms, recoup offers processing mechanisms for quick, efficient, and multi-level data interrogation with minimal effort, while at the same time creating publication-quality visualizations. Special focus is given on plot reusability, reproducibility, and real-time exploration and formatting options, operations rarely supported in similar visualization tools in a profound way. recoup was assessed using several qualitative user metrics and found to balance the tradeoff between important package features, including speed, visualization quality, overall friendliness, and the reusability of the results with minimal additional calculations. Conclusion While some existing solutions for the comprehensive visualization of NGS data signal offer satisfying results, they are often compromised regarding issues such as effortless tracking of processing and preparation steps under a common computational environment, visualization quality and user friendliness. recoup is a unique package presenting a balanced tradeoff for a combination of assessment criteria while remaining fast and friendly.

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