Evidence map›Paper›PMID 29958536›Full record

ArticleBMC research notes2018

GrapHi-C: graph-based visualization of Hi-C datasets.

Kimberly MacKay, Anthony Kusalik, Christopher H Eskiw

Abstract read
In one paragraph

Article in BMC research notes, 2018. 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. Article
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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

3 authors.

Kimberly MacKayDepartment of Computer Science, University of Saskatchewan, 110 Science Place, Saskatoon, SK, S7N 5C9, Canada. kimberly.mackay@usask.ca.ORCID http://orcid.org/0000-0001-6417-725X
Anthony KusalikDepartment of Computer Science, University of Saskatchewan, 110 Science Place, Saskatoon, SK, S7N 5C9, Canada.
Christopher H EskiwDepartment of Food and Bioproduct Science, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK, S7N 5A8, Canada.

Funding

Natural Sciences and Engineering Research Council of Canada RGPIN 37207Natural Sciences and Engineering Research Council of Canada Vanier Canada Graduate Scholarship
6 · The paper itself

Abstract

objectivesHi-C is a proximity-based ligation reaction used to detect regions of the genome that are close in 3D space (or "interacting"). Typically, results from Hi-C experiments (contact maps) are visualized as heatmaps or Circos plots. While informative, these visualizations do not directly represent genomic structure and folding, making the interpretation of the underlying 3D genomic organization obscured. Our objective was to generate a graph-based contact map representation that leads to a more intuitive structural visualization.

resultsNormalized contact maps were converted into undirected graphs where each vertex represented a genomic region and each edge represented a detected (intra- and inter-chromosomal) or known (linear) interaction between two regions. Each edge was weighted by the inverse of the linear distance (Hi-C experimental resolution) or the interaction frequency from the contact map. Graphs were generated based on this representation scheme for contact maps from existing fission yeast datasets. Originally, these datasets were used to (1) identify specific principles influencing fission yeast genome organization and (2) uncover changes in fission yeast genome organization during the cell cycle. When compared to the equivalent heatmaps and/or Circos plots, the graph-based visualizations more intuitively depicted the changes in genome organization described in the original studies.

Indexed as

Datasets as TopicData VisualizationGenomicsChromosome PositioningChromosomesDNAGenomeNucleic Acid ConformationDNAData visualizationGraphsHi-CWhole-genome contact maps

Identifiers

PMID29958536
PMCPMC6025839

What OpenQuestion holds

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Registered trials

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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.