Evidence map›Paper›PMID 32122303›Full record

ArticleBMC genomics2020

GenomeQC: a quality assessment tool for genome assemblies and gene structure annotations.

Nancy Manchanda, John L Portwood, Margaret R Woodhouse, Arun S Seetharam, Carolyn J Lawrence-Dill, Carson M Andorf, Matthew B Hufford

Abstract read
In one paragraph

Article in BMC genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

54 citing papers in PubMed.

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  11. A complete diploid human genome benchmark for personalized genomics.bioRxiv : the preprint server for biology · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Nancy ManchandaDepartment of Ecology, Evolution and Organismal Biology, Iowa State University, Ames, IA, 50011, USA.
John L PortwoodUSDA-ARS Corn Insects and Crop Genetics Research Unit, Ames, IA, 50011, USA.
Margaret R WoodhouseUSDA-ARS Corn Insects and Crop Genetics Research Unit, Ames, IA, 50011, USA.
Arun S SeetharamGenome Informatics Facility, Iowa State University, Ames, IA, 50011, USA.
Carolyn J Lawrence-DillDepartment of Genetics, Development and Cell Biology, Iowa State University, Ames, IA, 50011, USA.
Carson M AndorfUSDA-ARS Corn Insects and Crop Genetics Research Unit, Ames, IA, 50011, USA.
Matthew B HuffordDepartment of Ecology, Evolution and Organismal Biology, Iowa State University, Ames, IA, 50011, USA. mhufford@iastate.edu.ORCID http://orcid.org/0000-0003-3945-1143

Funding

Agricultural Research Service Project Number 5030-21000-068-00-DSpecific Coorperative Agreement 58-5030-8-064
6 · The paper itself

Abstract

backgroundGenome assemblies are foundational for understanding the biology of a species. They provide a physical framework for mapping additional sequences, thereby enabling characterization of, for example, genomic diversity and differences in gene expression across individuals and tissue types. Quality metrics for genome assemblies gauge both the completeness and contiguity of an assembly and help provide confidence in downstream biological insights. To compare quality across multiple assemblies, a set of common metrics are typically calculated and then compared to one or more gold standard reference genomes. While several tools exist for calculating individual metrics, applications providing comprehensive evaluations of multiple assembly features are, perhaps surprisingly, lacking. Here, we describe a new toolkit that integrates multiple metrics to characterize both assembly and gene annotation quality in a way that enables comparison across multiple assemblies and assembly types.

resultsOur application, named GenomeQC, is an easy-to-use and interactive web framework that integrates various quantitative measures to characterize genome assemblies and annotations. GenomeQC provides researchers with a comprehensive summary of these statistics and allows for benchmarking against gold standard reference assemblies.

conclusionsThe GenomeQC web application is implemented in R/Shiny version 1.5.9 and Python 3.6 and is freely available at https://genomeqc.maizegdb.org/ under the GPL license. All source code and a containerized version of the GenomeQC pipeline is available in the GitHub repository https://github.com/HuffordLab/GenomeQC.

Indexed as

Chromosome MappingComputational BiologyGenomicsHigh-Throughput Nucleotide SequencingHumansMolecular Sequence AnnotationSequence Analysis, DNASoftwareDocker containersGene annotationsGenome assemblyRShinyWeb interface

Identifiers

PMID32122303
PMCPMC7053122

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.