High-Throughput Computational Approaches to Analyzing Histone Modification Next-Generation Sequencing Data

2012 ◽  
Author(s):  
Jie Lv ◽  
Hongbo Liu ◽  
Qiong Wu ◽  
Yan Zhang
Keyword(s):  
Next Generation Sequencing ◽  
Histone Modification ◽  
High Throughput ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Sequencing Data ◽  
Computational Approaches ◽  
Generation Sequencing

scholarly journals Automated genotyping of microsatellite loci from feces with high throughput sequences

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258906
Author(s):  
Isabel Salado ◽  
Alberto Fernández-Gil ◽  
Carles Vilà ◽  
Jennifer A. Leonard
Keyword(s):  
Next Generation Sequencing ◽  
High Throughput ◽  
Microsatellite Loci ◽  
High Throughput Sequencing ◽  
Individual Identification ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Sequencing Data ◽  
Software Packages ◽  
Generation Sequencing

Ecological and conservation genetic studies often use noninvasive sampling, especially with elusive or endangered species. Because microsatellites are generally short in length, they can be amplified from low quality samples such as feces. Microsatellites are highly polymorphic so few markers are enough for reliable individual identification, kinship determination, or population characterization. However, the genotyping process from feces is expensive and time consuming. Given next-generation sequencing (NGS) and recent software developments, automated microsatellite genotyping from NGS data may now be possible. These software packages infer the genotypes directly from sequence reads, increasing throughput. Here we evaluate the performance of four software packages to genotype microsatellite loci from Iberian wolf (Canis lupus) feces using NGS. We initially combined 46 markers in a single multiplex reaction for the first time, of which 19 were included in the final analyses. Megasat was the software that provided genotypes with fewer errors. Coverage over 100X provided little additional information, but a relatively high number of PCR replicates were necessary to obtain a high quality genotype from highly unoptimized, multiplexed reactions (10 replicates for 18 of the 19 loci analyzed here). This could be reduced through optimization. The use of new bioinformatic tools and next-generation sequencing data to genotype these highly informative markers may increase throughput at a reasonable cost and with a smaller amount of laboratory work. Thus, high throughput sequencing approaches could facilitate the use of microsatellites with fecal DNA to address ecological and conservation questions.

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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