scholarly journals In Silico Probe-Based Detection of Citrus Viruses in NGS Data

2017 ◽  
Vol 107 (8) ◽  
pp. 988-993 ◽  
Author(s):  
T. L. Jooste ◽  
M. Visser ◽  
G. Cook ◽  
J. T. Burger ◽  
H. J. Maree
Keyword(s):  
Sequence Data ◽  
Simultaneous Detection ◽  
Rapid Identification ◽  
Sequencing Data ◽  
Metagenomic Sample ◽  
Field Samples ◽  
Input Dataset ◽  
Time Required ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data

The conservation of plant biosecurity relies on the rapid identification of pathogenic organisms, including viruses. With next-generation sequencing (NGS), it is possible to identify multiple viruses within a metagenomic sample. In this study, we explored the use of electronic probes (e-probes) for the simultaneous detection of 11 recognized citrus viruses. E-probes were designed and screened against raw sequencing data to minimize the bioinformatic processing time required. The e-probes were able to accurately detect their cognate viruses in simulated datasets, without any false negatives or positives. The efficiency of the e-probe-based approach was validated with NGS datasets generated from different RNA preparations: double-stranded RNA (dsRNA) from ‘Mexican’ lime infected with different Citrus tristeza virus (CTV) genotypes, dsRNA from field samples, and small RNA and total RNA from grapefruit infected with the CTV T3 genotype. A set of probes was made available that is able to accurately detect CTV in sequence data regardless of the input dataset or the genotype that plants are infected with.

scholarly journals The ICR96 exon CNV validation series: a resource for orthogonal assessment of exon CNV calling in NGS data

2017 ◽  
Vol 2 ◽  
pp. 35 ◽  
Author(s):  
Shazia Mahamdallie ◽  
Elise Ruark ◽  
Shawn Yost ◽  
Emma Ramsay ◽  
Imran Uddin ◽  
...  
Keyword(s):  
Sequencing Data ◽  
Targeted Next Generation Sequencing ◽  
Negative Results ◽  
Targeted Ngs ◽  
Predisposition Genes ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Validation Series ◽  
Generation Sequencing ◽  
Dependent Probe

Detection of deletions and duplications of whole exons (exon CNVs) is a key requirement of genetic testing. Accurate detection of this variant type has proved very challenging in targeted next-generation sequencing (NGS) data, particularly if only a single exon is involved. Many different NGS exon CNV calling methods have been developed over the last five years. Such methods are usually evaluated using simulated and/or in-house data due to a lack of publicly-available datasets with orthogonally generated results. This hinders tool comparisons, transparency and reproducibility. To provide a community resource for assessment of exon CNV calling methods in targeted NGS data, we here present the ICR96 exon CNV validation series. The dataset includes high-quality sequencing data from a targeted NGS assay (the TruSight Cancer Panel) together with Multiplex Ligation-dependent Probe Amplification (MLPA) results for 96 independent samples. 66 samples contain at least one validated exon CNV and 30 samples have validated negative results for exon CNVs in 26 genes. The dataset includes 46 exon CNVs in BRCA1, BRCA2, TP53, MLH1, MSH2, MSH6, PMS2, EPCAM or PTEN, giving excellent representation of the cancer predisposition genes most frequently tested in clinical practice. Moreover, the validated exon CNVs include 25 single exon CNVs, the most difficult type of exon CNV to detect. The FASTQ files for the ICR96 exon CNV validation series can be accessed through the European-Genome phenome Archive (EGA) under the accession number EGAS00001002428.

scholarly journals ALSgeneScanner: a pipeline for the analysis and interpretation of DNA NGS data of ALS patients

2018 ◽  
Author(s):  
Alfredo Iacoangeli ◽  
Ahmad Al Khleifat ◽  
William Sproviero ◽  
Aleksey Shatunov ◽  
Ashley R Jones ◽  
...  
Keyword(s):  
Motor Neurons ◽  
Health Care Professionals ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Next Generation Sequencing Data ◽  
Sequencing Data ◽  
Whole Exome ◽  
Exome Sequence Data ◽  
Als Patients ◽  
Ngs Data

AbstractAmyotrophic lateral sclerosis (ALS, MND) is a neurodegenerative disease of upper and lower motor neurons resulting in death from neuromuscular respiratory failure, typically within two years of first symptoms. Genetic factors are an important cause of ALS, with variants in more than 25 genes having strong evidence, and weaker evidence available for variants in more than 120 genes. With the increasing availability of Next-Generation sequencing data, non-specialists, including health care professionals and patients, are obtaining their genomic information without a corresponding ability to analyse and interpret it. Furthermore, the relevance of novel or existing variants in ALS genes is not always apparent. Here we present ALSgeneScanner, a tool that is easy to install and use, able to provide an automatic, detailed, annotated report, on a list of ALS genes from whole genome sequence data in a few hours and whole exome sequence data in about one hour on a readily available mid-range computer. This will be of value to non-specialists and aid in the interpretation of the relevance of novel and existing variants identified in DNA sequencing data.

scholarly journals Bioinformatic strategies for the analysis of genomic aberrations detected by targeted NGS panels with clinical application

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10897
Author(s):  
Jakub Hynst ◽  
Veronika Navrkalova ◽  
Karol Pal ◽  
Sarka Pospisilova
Keyword(s):  
Relevant Information ◽  
Bioinformatic Analysis ◽  
Rapid Identification ◽  
Integrated Analysis ◽  
Clinical Settings ◽  
Sequencing Data ◽  
Targeted Ngs ◽  
Genomic Aberrations ◽  
Validation Procedure ◽  
Next Generation Sequencing Ngs

Molecular profiling of tumor samples has acquired importance in cancer research, but currently also plays an important role in the clinical management of cancer patients. Rapid identification of genomic aberrations improves diagnosis, prognosis and effective therapy selection. This can be attributed mainly to the development of next-generation sequencing (NGS) methods, especially targeted DNA panels. Such panels enable a relatively inexpensive and rapid analysis of various aberrations with clinical impact specific to particular diagnoses. In this review, we discuss the experimental approaches and bioinformatic strategies available for the development of an NGS panel for a reliable analysis of selected biomarkers. Compliance with defined analytical steps is crucial to ensure accurate and reproducible results. In addition, a careful validation procedure has to be performed before the application of NGS targeted assays in routine clinical practice. With more focus on bioinformatics, we emphasize the need for thorough pipeline validation and management in relation to the particular experimental setting as an integral part of the NGS method establishment. A robust and reproducible bioinformatic analysis running on powerful machines is essential for proper detection of genomic variants in clinical settings since distinguishing between experimental noise and real biological variants is fundamental. This review summarizes state-of-the-art bioinformatic solutions for careful detection of the SNV/Indels and CNVs for targeted sequencing resulting in translation of sequencing data into clinically relevant information. Finally, we share our experience with the development of a custom targeted NGS panel for an integrated analysis of biomarkers in lymphoproliferative disorders.

scholarly journals Rapid feedback on hospital onset SARS-CoV-2 infections combining epidemiological and sequencing data

2020 ◽  
Author(s):  
Oliver T Stirrup ◽  
Joseph Hughes ◽  
Matthew Parker ◽  
David G Partridge ◽  
James G Shepherd ◽  
...  
Keyword(s):  
Mutation Rate ◽  
Sequence Data ◽  
Rapid Assessment ◽  
Epidemiological Data ◽  
Rapid Identification ◽  
Infection Prevention And Control ◽  
Sequencing Data ◽  
Additional Information ◽  
Close Sequence ◽  
Healthcare Associated

AbstractBackgroundRapid identification and investigation of healthcare-associated infections (HCAIs) is important for suppression of SARS-CoV-2, but the infection source for hospital onset COVID-19 infections (HOCIs) cannot always be readily identified based only on epidemiological data. Viral sequencing data provides additional information regarding potential transmission clusters, but the low mutation rate of SARS-CoV-2 can make interpretation using standard phylogenetic methods difficult.MethodsWe developed a novel statistical method and sequence reporting tool (SRT) that combines epidemiological and sequence data in order to provide a rapid assessment of the probability of HCAI among HOCI cases (defined as first positive test >48 hours following admission) and to identify infections that could plausibly constitute outbreak events. The method is designed for prospective use, but was validated using retrospective datasets from hospitals in Glasgow and Sheffield collected February-May 2020.ResultsWe analysed data from 326 HOCIs. Among HOCIs with time-from-admission ≥8 days the SRT algorithm identified close sequence matches from the same ward for 160/244 (65.6%) and in the remainder 68/84 (81.0%) had at least one similar sequence elsewhere in the hospital, resulting in high estimated probabilities of within-ward and within-hospital transmission. For HOCIs with time-from-admission 3-7 days, the SRT probability of healthcare acquisition was >0.5 in 33/82 (40.2%).ConclusionsThe methodology developed can provide rapid feedback on HOCIs that could be useful for infection prevention and control teams, and warrants further prospective evaluation. The integration of epidemiological and sequence data is important given the low mutation rate of SARS-CoV-2 and its variable incubation period.

scholarly journals Communicating Regulatory High Throughput Sequencing Data Using BioCompute Objects

2020 ◽  
Author(s):  
Charles Hadley S. King ◽  
Jonathon Keeney ◽  
Nuria Guimera ◽  
Souvik Das ◽  
Brian Fochtman ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
Biological Data ◽  
Sequencing Data ◽  
Regulatory Submission ◽  
High Throughput Sequencing Data ◽  
Analysis Workflow ◽  
Regulatory Submissions ◽  
High Concordance ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data

AbstractFor regulatory submissions of next generation sequencing (NGS) data it is vital for the analysis workflow to be robust, reproducible, and understandable. This project demonstrates that the use of the IEEE 2791-2020 Standard, (BioCompute objects [BCO]) enables complete and concise communication of NGS data analysis results. One arm of a clinical trial was replicated using synthetically generated data made to resemble real biological data. Two separate, independent analyses were then carried out using BCOs as the tool for communication of analysis: one to simulate a pharmaceutical regulatory submission to the FDA, and another to simulate the FDA review. The two results were compared and tabulated for concordance analysis: of the 118 simulated patient samples generated, the final results of 117 (99.15%) were in agreement. This high concordance rate demonstrates the ability of a BCO, when a verification kit is included, to effectively capture and clearly communicate NGS analyses within regulatory submissions. BCO promotes transparency and induces reproducibility, thereby reinforcing trust in the regulatory submission process.

scholarly journals HAPDeNovo: a haplotype-based approach for filtering and phasing de novo mutations in linked read sequencing data

2017 ◽  
Author(s):  
Xin Zhou ◽  
Serafim Batzoglou ◽  
Arend Sidow ◽  
Lu Zhang
Keyword(s):  
False Positive ◽  
De Novo ◽  
False Positives ◽  
Sequencing Data ◽  
De Novo Mutations ◽  
Congenital Diseases ◽  
Genome Wide ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Haplotype Information

AbstractBackgroundDe novo mutations (DNMs) are associated with neurodevelopmental and congenital diseases, and their detection can contribute to understanding disease pathogenicity. However, accurate detection is challenging because of their small number relative to the genome-wide false positives in next generation sequencing (NGS) data. Software such as DeNovoGear and TrioDeNovo have been developed to detect DNMs, but at good sensitivity they still produce many false positive calls.ResultsTo address this challenge, we develop HAPDeNovo, a program that leverages phasing information from linked read sequencing, to remove false positive DNMs from candidate lists generated by DNM-detection tools. Short reads from each phasing block are allocated to each of the two haplotypes followed by generating a haploid genotype for each putative DNM.HAPDeNovo removes variants that are called as heterozygous in one of the haplotypes because they are almost certainly false positives. Our experiments on 10X Chromium linked read sequencing trio data reveal that HAPDeNovo eliminates 80% to 99% of false positives regardless of how large the candidate DNM set is.ConclusionsHAPDeNovo leverages the haplotype information from linked read sequencing to remove spurious false positive DNMs effectively, and it increases accuracy of DNM detection dramatically without sacrificing sensitivity.

scholarly journals Validation of Variant Assembly Using HAPHPIPE with Next-Generation Sequence Data from Viruses

Viruses ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 758 ◽  
Author(s):  
Keylie M. Gibson ◽  
Margaret C. Steiner ◽  
Uzma Rentia ◽  
Matthew L. Bendall ◽  
Marcos Pérez-Losada ◽  
...  
Keyword(s):  
De Novo ◽  
Sequence Data ◽  
Consensus Sequence ◽  
Sequence Assembly ◽  
Next Generation ◽  
Consensus Sequences ◽  
Bioinformatic Tools ◽  
Hiv Gp120 ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data

Next-generation sequencing (NGS) offers a powerful opportunity to identify low-abundance, intra-host viral sequence variants, yet the focus of many bioinformatic tools on consensus sequence construction has precluded a thorough analysis of intra-host diversity. To take full advantage of the resolution of NGS data, we developed HAplotype PHylodynamics PIPEline (HAPHPIPE), an open-source tool for the de novo and reference-based assembly of viral NGS data, with both consensus sequence assembly and a focus on the quantification of intra-host variation through haplotype reconstruction. We validate and compare the consensus sequence assembly methods of HAPHPIPE to those of two alternative software packages, HyDRA and Geneious, using simulated HIV and empirical HIV, HCV, and SARS-CoV-2 datasets. Our validation methods included read mapping, genetic distance, and genetic diversity metrics. In simulated NGS data, HAPHPIPE generated pol consensus sequences significantly closer to the true consensus sequence than those produced by HyDRA and Geneious and performed comparably to Geneious for HIV gp120 sequences. Furthermore, using empirical data from multiple viruses, we demonstrate that HAPHPIPE can analyze larger sequence datasets due to its greater computational speed. Therefore, we contend that HAPHPIPE provides a more user-friendly platform for users with and without bioinformatics experience to implement current best practices for viral NGS assembly than other currently available options.

scholarly journals An NGS Workflow Blueprint for DNA Sequencing Data and Its Application in Individualized Molecular Oncology

2015 ◽  
Vol 14s5 ◽  
pp. CIN.S30793 ◽  
Author(s):  
Jian Li ◽  
Aarif Mohamed Nazeer Batcha ◽  
Björn Gaining ◽  
Ulrich R. Mansmann
Keyword(s):  
Data Storage ◽  
Individualized Medicine ◽  
Integrated Analysis ◽  
Sequencing Data ◽  
Molecular Oncology ◽  
Analysis Workflow ◽  
Sequencing Quality ◽  
Technical Simplicity ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data

Next-generation sequencing (NGS) technologies that have advanced rapidly in the past few years possess the potential to classify diseases, decipher the molecular code of related cell processes, identify targets for decision-making on targeted therapy or prevention strategies, and predict clinical treatment response. Thus, NGS is on its way to revolutionize oncology. With the help of NGS, we can draw a finer map for the genetic basis of diseases and can improve our understanding of diagnostic and prognostic applications and therapeutic methods. Despite these advantages and its potential, NGS is facing several critical challenges, including reduction of sequencing cost, enhancement of sequencing quality, improvement of technical simplicity and reliability, and development of semiautomated and integrated analysis workflow. In order to address these challenges, we conducted a literature research and summarized a four-stage NGS workflow for providing a systematic review on NGS-based analysis, explaining the strength and weakness of diverse NGS-based software tools, and elucidating its potential connection to individualized medicine. By presenting this four-stage NGS workflow, we try to provide a minimal structural layout required for NGS data storage and reproducibility.

scholarly journals MitoSuite: a graphical tool for human mitochondrial genome profiling in massive parallel sequencing

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3406 ◽  
Author(s):  
Koji Ishiya ◽  
Shintaroh Ueda
Keyword(s):  
Mitochondrial Genome ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Sequencing Data ◽  
High Coverage ◽  
Graphical Tool ◽  
Genome Variations ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Human Mitochondrial Genome

Recent rapid advances in high-throughput, next-generation sequencing (NGS) technologies have promoted mitochondrial genome studies in the fields of human evolution, medical genetics, and forensic casework. However, scientists unfamiliar with computer programming often find it difficult to handle the massive volumes of data that are generated by NGS. To address this limitation, we developed MitoSuite, a user-friendly graphical tool for analysis of data from high-throughput sequencing of the human mitochondrial genome. MitoSuite generates a visual report on NGS data with simple mouse operations. Moreover, it analyzes high-coverage sequencing data but runs on a stand-alone computer, without the need for file upload. Therefore, MitoSuite offers outstanding usability for handling massive NGS data, and is ideal for evolutionary, clinical, and forensic studies on the human mitochondrial genome variations. It is freely available for download from the website https://mitosuite.com.

scholarly journals Easymap: A User-Friendly Software Package for Rapid Mapping-by-Sequencing of Point Mutations and Large Insertions

2021 ◽  
Vol 12 ◽  
Author(s):  
Samuel Daniel Lup ◽  
David Wilson-Sánchez ◽  
Sergio Andreu-Sánchez ◽  
José Luis Micol
Keyword(s):  
Point Mutations ◽  
Rapid Identification ◽  
Graphical Interface ◽  
Rna Seq ◽  
Source Program ◽  
Next Generation Sequencing Ngs ◽  
User Friendly ◽  
Ngs Data ◽  
Mapping By Sequencing ◽  
Generation Sequencing

Mapping-by-sequencing strategies combine next-generation sequencing (NGS) with classical linkage analysis, allowing rapid identification of the causal mutations of the phenotypes exhibited by mutants isolated in a genetic screen. Computer programs that analyze NGS data obtained from a mapping population of individuals derived from a mutant of interest to identify a causal mutation are available; however, the installation and usage of such programs requires bioinformatic skills, modifying or combining pieces of existing software, or purchasing licenses. To ease this process, we developed Easymap, an open-source program that simplifies the data analysis workflows from raw NGS reads to candidate mutations. Easymap can perform bulked segregant mapping of point mutations induced by ethyl methanesulfonate (EMS) with DNA-seq or RNA-seq datasets, as well as tagged-sequence mapping for large insertions, such as transposons or T-DNAs. The mapping analyses implemented in Easymap have been validated with experimental and simulated datasets from different plant and animal model species. Easymap was designed to be accessible to all users regardless of their bioinformatics skills by implementing a user-friendly graphical interface, a simple universal installation script, and detailed mapping reports, including informative images and complementary data for assessment of the mapping results. Easymap is available at http://genetics.edu.umh.es/resources/easymap; its Quickstart Installation Guide details the recommended procedure for installation.

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