Evidence map›Paper›PMID 27454532›Full record

ArticleBMC bioinformatics2016

OMWare: a tool for efficient assembly of genome-wide physical maps.

Aaron R Sharp, Joshua A Udall

Abstract read
In one paragraph

Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Advances in optical mapping for genomic research.Computational and structural biotechnology journal · 2020
    Review
  2. The State of "Frontiers in genetics · 2018
    Review
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

2 authors.

Aaron R SharpCollege of Life Sciences, Brigham Young University, Provo, UT, 84602-2400, USA. sharp.aaron.r@gmail.com.
Joshua A UdallCollege of Life Sciences, Brigham Young University, Provo, UT, 84602-2400, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPhysical mapping of DNA with restriction enzymes allows for the characterization and assembly of much longer molecules than is feasible with sequencing. However, assemblies of physical map data are sensitive to input parameters, which describe noise inherent in the data collection process. One possible way to determine the parameter values that best describe a dataset is by trial and error.

resultsHere we present OMWare, a tool that efficiently generated 405 de novo map assemblies of a single datasets collected from the cotton species Gossypium raimondii. The assemblies were generated using various input parameter values, and were completed more efficiently by re-using compatible intermediate results. These assemblies were assayed for contiguity, internal consistency, and accuracy.

conclusionsResulting assemblies had variable qualities. Although highly accurate assemblies were found, contiguity and internal consistency metrics were poor predictors of accuracy.

Indexed as

Genome, PlantSoftwareData AccuracyGossypiumPhysical Chromosome MappingSequence Analysis, DNA

Identifiers

PMID27454532
PMCPMC4965707

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.