Evidence map›Paper›PMID 31723420›Full record

ArticleF1000Research2019

A Sequence Distance Graph framework for genome assembly and analysis.

Luis Yanes, Gonzalo Garcia Accinelli, Jonathan Wright, Ben J Ward, Bernardo J Clavijo

Abstract read
In one paragraph

Article in F1000Research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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

5 authors.

Luis YanesEarlham Institute, Norwich, Norfolk, NR4 7UZ, UK.ORCID 0000-0003-1382-0166
Gonzalo Garcia AccinelliEarlham Institute, Norwich, Norfolk, NR4 7UZ, UK.
Jonathan WrightEarlham Institute, Norwich, Norfolk, NR4 7UZ, UK.ORCID 0000-0001-6471-8749
Ben J WardEarlham Institute, Norwich, Norfolk, NR4 7UZ, UK.
Bernardo J ClavijoEarlham Institute, Norwich, Norfolk, NR4 7UZ, UK.

Funding

Biotechnology and Biological Sciences Research Council BB/N009819/1Biotechnology and Biological Sciences Research Council BBS/E/T/000PR9817Biotechnology and Biological Sciences Research Council BBS/E/T/000PR9818
6 · The paper itself

Abstract

The Sequence Distance Graph (SDG) framework works with genome assembly graphs and raw data from paired, linked and long reads. It includes a simple deBruijn graph module, and can import graphs using the graphical fragment assembly (GFA) format. It also maps raw reads onto graphs, and provides a Python application programming interface (API) to navigate the graph, access the mapped and raw data and perform interactive or scripted analyses. Its complete workspace can be dumped to and loaded from disk, decoupling mapping from analysis and supporting multi-stage pipelines. We present the design and implementation of the framework, and example analyses scaffolding a short read graph with long reads, and navigating paths in a heterozygous graph for a simulated parent-offspring trio dataset. SDG  is  freely  available  under  the  MIT  license  at https://github.com/bioinfologics/sdg.

Indexed as

Sequence Analysis, DNASoftwareGenomicsgenome assemblyGenome graph

Identifiers

PMID31723420
PMCPMC6833988

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.