Evidence map›Paper›PMID 36778393›Full record

ArticlebioRxiv : the preprint server for biology2023

DandD: efficient measurement of sequence growth and similarity.

Jessica K Bonnie, Omar Ahmed, Ben Langmead

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Jessica K BonnieDepartment of Computer Science, Johns Hopkins University.
Omar AhmedDepartment of Computer Science, Johns Hopkins University.
Ben LangmeadDepartment of Computer Science, Johns Hopkins University.

Funding

Methods for sequencing data analysis and archive-scale data science - RenewalR35GM139602 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI Benjamin Thomas Langmead · 2021 to 2026
$5.0M
Personal and panel references for improved alignmentR01HG011392 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI LANGMEAD, BENJAMIN THOMAS · 2020 to 2025
$4.2M
New algorithms and tools for large-scale genomic analysesR01HG012252 · NHGRI · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Aaron R Quinlan · 2022 to 2026
$3.2M
Pre-Doctoral Training Program in Computational MedicineT32GM119998 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI MAC GABHANN, FEILIM C · 2017 to 2021
$1.5M
NHGRI NIH HHS R01 HG011392NHGRI NIH HHS R01 HG012252NIGMS NIH HHS R35 GM139602NIGMS NIH HHS T32 GM119998
6 · The paper itself

Abstract

Genome assembly databases are growing rapidly. The sequence content in each new assembly can be largely redundant with previous ones, but this is neither conceptually nor algorithmically easy to measure. We propose new methods and a new tool called DandD that addresses the question of how much new sequence is gained when a sequence collection grows. DandD can describe how much human structural variation is being discovered in each new human genome assembly and when discoveries will level off in the future. DandD uses a measure called

Identifiers

PMID36778393
PMCPMC9915590

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.