scholarly journals Vy-PER: eliminating false positive detection of virus integration events in next generation sequencing data

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Michael Forster ◽  
◽  
Silke Szymczak ◽  
David Ellinghaus ◽  
Georg Hemmrich ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
False Positive ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Sequencing Data ◽  
False Positive Detection ◽  
Virus Integration ◽  
Generation Sequencing

scholarly journals rmvPFBAM: Removing Primers from BAM Files Based on Amplicon-Based Next-Generation Sequencing and Cloud Computing When Analyzing Personal Genome Data

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Yanjun Ma
Keyword(s):  
Next Generation Sequencing ◽  
False Positive ◽  
Large Scale ◽  
Genomic Data ◽  
Next Generation Sequencing Data ◽  
Personal Genome ◽  
Next Generation ◽  
Sequencing Data ◽  
Personal Genomic ◽  
Generation Sequencing

Personal genomic data constitute one important part of personal health data. However, due to the large amount of personal genomic data obtained by the next-generation sequencing technology, special tools are needed to analyze these data. In this article, we will explore a tool analyzing cloud-based large-scale genome sequencing data. Analyzing and identifying genomic variations from amplicon-based next-generation sequencing data are necessary for the clinical diagnosis and treatment of cancer patients. When processing the amplicon-based next-generation sequencing data, one essential step is removing primer sequences from the reads to avoid detecting false-positive mutations introduced by nonspecific primer binding and primer extension reactions. At present, the removing primer tools usually discard primer sequences from the FASTQ file instead of BAM file, but this method could cause some downstream analysis problems. Only one tool (BAMClipper) removes primer sequences from BAM files, but it only modified the CIGAR value of the BAM file, and false-positive mutations falling in the primer region could still be detected based on its processed BAM file. So, we developed one cutting primer tool (rmvPFBAM) removing primer sequences from the BAM file, and the mutations detected based on the processed BAM file by rmvPFBAM are highly credible. Besides that, rmvPFBAM runs faster than other tools, such as cutPrimers and BAMClipper.

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.

scholarly journals BIGpre: A Quality Assessment Package for Next-Generation Sequencing Data

2011 ◽  
Vol 9 (6) ◽  
pp. 238-244 ◽  
Author(s):  
Tongwu Zhang ◽  
Yingfeng Luo ◽  
Kan Liu ◽  
Linlin Pan ◽  
Bing Zhang ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Quality Assessment ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Sequencing Data ◽  
Generation Sequencing
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