CoverView: a sequence quality evaluation tool for next generation sequencing data

Münz, Márton; Mahamdallie, Shazia; Yost, Shawn; Rimmer, Andrew; Poyastro-Pearson, Emma; Strydom, Ann; Seal, Sheila; Ruark, Elise; Rahman, Nazneen

doi:10.12688/wellcomeopenres.14306.1

Cited by 7 publications

(9 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As part of our automated NGS analysis pipeline sample BAM files with their corresponding .BAI index files are inputted into CoverView 11 . We defined 1471 test regions in a BED file.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

The Quality Sequencing Minimum (QSM): providing comprehensive, consistent, transparent next generation sequencing data quality assurance

et al. 2018

Self Cite

View full text Add to dashboard Cite

Next generation sequencing (NGS) is routinely used in clinical genetic testing. Quality management of NGS testing is essential to ensure performance is consistently and rigorously evaluated. Three primary metrics are used in NGS quality evaluation: depth of coverage, base quality and mapping quality. To provide consistency and transparency in the utilisation of these metrics we present the Quality Sequencing Minimum (QSM). The QSM defines the minimum quality requirement a laboratory has selected for depth of coverage (C), base quality (B) and mapping quality (M) and can be applied per base, exon, gene or other genomic region, as appropriate. The QSM format is CX_BY(P Y)_MZ(P Z). X is the parameter threshold for C, Y the parameter threshold for B, P Y the percentage of reads that must reach Y, Z the parameter threshold for M, P Z the percentage of reads that must reach Z. The data underlying the QSM is in the BAM file, so a QSM can be easily and automatically calculated in any NGS pipeline. We used the QSM to optimise cancer predisposition gene testing using the TruSight Cancer Panel (TSCP). We set the QSM as C50_B10(85)_M20(95). Test regions falling below the QSM were automatically flagged for review, with 100/1471 test regions QSM-flagged in multiple individuals. Supplementing these regions with 132 additional probes improved performance in 85/100. We also used the QSM to optimise testing of genes with pseudogenes such as PTEN and PMS2. In TSCP data from 960 individuals the median number of regions that passed QSM per sample was 1429 (97%). Importantly, the QSM can be used at an individual report level to provide succinct, comprehensive quality assurance information about individual test performance. We believe many laboratories would find the QSM useful. Furthermore, widespread adoption of the QSM would facilitate consistent, transparent reporting of genetic test performance by different laboratories.

show abstract

“…As part of our automated NGS analysis pipeline sample BAM files with their corresponding .BAI index files are inputted into CoverView 11 . We defined 1471 test regions in a BED file.…”

Section: Resultsmentioning

confidence: 99%

“…A standard BAM file contains the data required for the QSM and a QSM can be easily and automatically applied in any NGS pipeline. We have developed a freely available tool called CoverView to do this 11 . Alternatively, custom scripting within any NGS analytical pipeline should readily allow application of a QSM.…”

Section: Introductionmentioning

confidence: 99%

The Quality Sequencing Minimum (QSM): providing comprehensive, consistent, transparent next generation sequencing data quality assurance

et al. 2018

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, the optimal way to visualize and evaluate the obtained coverage data is not universally defined. Several tools have been designed to evaluate the coverage of target regions after short-read sequencing in a diagnostic setting 2,9,10 . While these tools are useful to monitor quality control of runs and samples during technical validation of sequencing tests, unlike CovReport, they do not generate exon-level coverage visualization that can be directly annexed to the diagnostic report.…”

Section: Discussionmentioning

confidence: 99%

A new tool CovReport generates easy-to-understand sequencing coverage summary for diagnostic reports

Gorokhov

Cerino

Mortreux

et al. 2020

Sci Rep

View full text Add to dashboard Cite

in order to properly interpret the results of a diagnostic gene panel sequencing test, gene coverage needs to be taken into consideration. if coverage is too low, an additional re-sequencing test is needed to make sure that a pathogenic variant is not missed. to facilitate the interpretation of coverage data, we designed covReport, a novel easy-to-use visualization tool. covReport generates a concise coverage summary that allows one-glance assessment of the sequencing test performance. Both gene-level and exon-level coverage can be immediately appreciated and taken into consideration for further medical decisions. covReport does not require complex installation and can thus be easily implemented in any diagnostic laboratory setting. A user-friendly interface generates a graphic summary of coverage that can be directly included in the diagnostic report. in addition to a stand-alone version, we also provide a command line version of covReport that can be integrated into any bioinformatics pipeline. this flexible tool is now part of routine sequencing analysis at the Department of Medical Genetics at La timone Hospital (Marseille, france). covReport is available at http://jdotsoft.com/covReport.php. it is implemented in Java and supported on Windows, Mac oS X and Linux.

show abstract

“…Given the critical importance of coverage data, several tools have been previously developed to evaluate the coverage of target regions after short-read sequencing in a diagnostic setting [2,6,7].…”

Section: Discussionmentioning

confidence: 99%

A new tool CovReport generates easy-to-understand sequencing coverage summary for diagnostic reports

Gorokhov

Cerino

Bartoli

et al. 2019

Preprint

View full text Add to dashboard Cite

In order to properly interpret the results of a diagnostic gene panel sequencing test, gene coverage needs to be taken into consideration. If coverage is too low, an additional re-sequencing test is needed to make sure that a pathogenic variant is not missed. To facilitate the interpretation of coverage data, we designed CovReport, a novel easy-to-use visualization tool. CovReport generates a concise coverage summary that allows one-glance assessment of the sequencing test performance. Both gene-level and exon-level coverage can be immediately appreciated and taken into consideration for further medical decisions. CovReport does not require complex installation and can thus be easily implemented in any diagnostic laboratory setting. A user-friendly interface generates a graphic summary of coverage that can be directly included in the diagnostic report. In addition to a stand-alone version, we also provide a command line version of CovReport that can be integrated into any bioinformatics pipeline. This flexible tool is now part of routine sequencing analysis at the Department of Medical Genetics at La Timone Hospital (Marseille, France). Availability and implementation: CovReport is available at http://jdotsoft.com/CovReport.php. It is implemented in Java and supported on Windows, Mac OS X and Linux.

show abstract

CoverView: a sequence quality evaluation tool for next generation sequencing data

Cited by 7 publications

References 27 publications

The Quality Sequencing Minimum (QSM): providing comprehensive, consistent, transparent next generation sequencing data quality assurance

The Quality Sequencing Minimum (QSM): providing comprehensive, consistent, transparent next generation sequencing data quality assurance

A new tool CovReport generates easy-to-understand sequencing coverage summary for diagnostic reports

A new tool CovReport generates easy-to-understand sequencing coverage summary for diagnostic reports

Contact Info

Product

Resources

About