Evidence map›Paper›PMID 39939176›Full record

ArticleGenome research2025

Fast sequence alignment for centromeres with RaMA.

Pinglu Zhang, Yanming Wei, Qinzhong Tian, Quan Zou, Yansu Wang

Abstract read
In one paragraph

Article in Genome research, 2025. 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
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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

5 authors.

Pinglu ZhangInstitute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China.ORCID 0009-0002-1788-3084
Yanming WeiYangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou 324003, Zhejiang, China.ORCID 0000-0003-4843-3350
Qinzhong TianInstitute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China.ORCID 0009-0005-8073-3582
Quan ZouInstitute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China.ORCID 0000-0001-6406-1142
Yansu WangInstitute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China; wangyansu@uestc.edu.cn.ORCID 0000-0003-1274-4958

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The release of the first draft of the human pangenome has revolutionized genomic research by enabling access to complex regions like centromeres, composed of extra-long tandem repeats (ETRs). However, a significant gap remains as current methodologies are inadequate for producing sequence alignments that effectively capture genetic events within ETRs, highlighting a pressing need for improved alignment tools. Inspired by UniAligner, we developed a rare match aligner (RaMA), using rare matches as anchors and two-piece affine gap cost to generate complete pairwise alignment that better captures genetic evolution. RaMA also employs parallel computing and the wavefront algorithm to accelerate anchor discovery and sequence alignment, achieving up to 13.66 times faster processing using only 11% of UniAligner's memory. Downstream analysis of simulated data and the CHM13 and CHM1 higher-order repeat (HOR) arrays demonstrates that RaMA achieves more accurate alignments, effectively capturing true HOR structures. RaMA also introduces two methods for defining reliable alignment regions, further refining and enhancing the accuracy of centromeric alignment statistics.

Indexed as

CentromereSequence AlignmentSoftwareAlgorithmsGenome, HumanHumansSequence Analysis, DNATandem Repeat Sequences

Identifiers

PMID39939176
PMCPMC12047532

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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.