scholarly journals GeMSTONE: Orchestrated Prioritization of Human Germline Mutations in the Cloud

2016 ◽  
Author(s):  
Siwei Chen ◽  
Juan Felipe Beltrán ◽  
Xiaomu Wei ◽  
Steven Lipkin ◽  
Clara Esteban-Jurado ◽  
...  
Keyword(s):  
Next Generation Sequencing Data ◽  
Sequencing Data ◽  
Variant Prioritization ◽  
Computational Tools ◽  
Exome Sequencing Data ◽  
Comprehensive Collection ◽  
High Level ◽  
Scoring Tool ◽  
Data Libraries ◽  
Generation Sequencing

Integrative analysis of whole-genome/exome-sequencing data has been challenging, especially for the non-programming research community, as it requires leveraging an inordinate number of computational tools. Even computational biologists find it unexpectedly difficult to reproduce results from others or optimize their own strategies in an end-to-end workflow. We introduce Germline Mutation Scoring Tool fOr Next-generation sEquencing data (GeMSTONE), a cloud- based variant prioritization tool with high-level customization and a comprehensive collection of bioinformatics tools and data libraries (http://gemstone.yulab.org/). GeMSTONE generates and readily accepts a sharable 'recipe' file for each run to either replicate existing results or analyze new data with identical parameters.

scholarly journals PIMBA: a PIpeline for MetaBarcoding Analysis

2021 ◽  
Author(s):  
Renato R. M. Oliveira ◽  
Raissa L S Silva ◽  
Gisele L. Nunes ◽  
Guilherme Oliveira
Keyword(s):  
Environmental Samples ◽  
Next Generation Sequencing Data ◽  
Ecological Studies ◽  
Sequencing Data ◽  
Monitoring Method ◽  
Computational Tools ◽  
Dna Metabarcoding ◽  
Reference Databases ◽  
User Friendly ◽  
Generation Sequencing

DNA metabarcoding is an emerging monitoring method capable of assessing biodiversity from environmental samples (eDNA). Advances in computational tools have been required due to the increase of Next-Generation Sequencing data. Tools for DNA metabarcoding analysis, such as MOTHUR, QIIME, Obitools, and mBRAVE have been widely used in ecological studies. However, some difficulties are encountered when there is a need to use custom databases. Here we present PIMBA, a PIpeline for MetaBarcoding Analysis, which allows the use of customized databases, as well as other reference databases used by the softwares mentioned here. PIMBA is an open-source and user-friendly pipeline that consolidates all analyses in just three command lines.

scholarly journals Analysis of structural and functional organization of the curly birch chloroplast genome based on the next-generation sequencing data

2019 ◽  
Vol 63 (3) ◽  
pp. 312-316 ◽  
Author(s):  
O. Yu. Baranov ◽  
P. S. Kiryanov ◽  
S. V. Pantelev ◽  
L. V. Mozharovskaya ◽  
A. V. Padutov ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Chloroplast Genome ◽  
Real Time ◽  
Real Time Pcr ◽  
Functional Organization ◽  
Next Generation Sequencing Data ◽  
Sequencing Data ◽  
Pcr Method ◽  
High Level ◽  
Generation Sequencing

The sequencing and annotation of the curly birch chloroplast genome were carried out. A high level of similarity of the structural and functional organization of cpDNA among the species of the Betulaceae family was revealed. A set of primers was developed to assess the level of expression of EST markers of the curly birch cpDNA by the real time PCR method.

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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