Evidence map›Paper›PMID 35758819›Full record

ArticleBioinformatics (Oxford, England)2022

The effect of genome graph expressiveness on the discrepancy between genome graph distance and string set distance.

Yutong Qiu, Carl Kingsford

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2022. 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

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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.

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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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

2 authors.

Yutong QiuComputational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15232, USA.
Carl KingsfordComputational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15232, USA.

Funding

Data Discovery: Computational Methods for Searching Short-Read Sequencing Experiments - Administrative SupplementR01GM122935 · NIGMS · CARNEGIE-MELLON UNIVERSITY · PI KINGSFORD, CARLETON LEE · 2017 to 2021
$1.2M
NIGMS NIH HHS R01 GM122935US National Institutes of Health R01GM122935
6 · The paper itself

Abstract

motivationIntra-sample heterogeneity describes the phenomenon where a genomic sample contains a diverse set of genomic sequences. In practice, the true string sets in a sample are often unknown due to limitations in sequencing technology. In order to compare heterogeneous samples, genome graphs can be used to represent such sets of strings. However, a genome graph is generally able to represent a string set universe that contains multiple sets of strings in addition to the true string set. This difference between genome graphs and string sets is not well characterized. As a result, a distance metric between genome graphs may not match the distance between true string sets.

resultsWe extend a genome graph distance metric, Graph Traversal Edit Distance (GTED) proposed by Ebrahimpour Boroojeny et al., to FGTED to model the distance between heterogeneous string sets and show that GTED and FGTED always underestimate the Earth Mover's Edit Distance (EMED) between string sets. We introduce the notion of string set universe diameter of a genome graph. Using the diameter, we are able to upper-bound the deviation of FGTED from EMED and to improve FGTED so that it reduces the average error in empirically estimating the similarity between true string sets. On simulated T-cell receptor sequences and actual Hepatitis B virus genomes, we show that the diameter-corrected FGTED reduces the average deviation of the estimated distance from the true string set distances by more than 250%. AVAILABILITY AND IMPLEMENTATION: Data and source code for reproducing the experiments are available at: https://github.com/Kingsford-Group/gtedemedtest/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

AlgorithmsGenomeGenomicsSequence Analysis, DNASoftware

Identifiers

PMID35758819
PMCPMC9235494

What OpenQuestion holds

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LicenceCC BY
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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.