Evidence map›Paper›PMID 40707727›Full record

ArticleCommunications biology2025

Correcting errors in PCR-derived libraries for rare allele detection by reconstructing parental and daughter strand information.

Hyeonseob Lim, Soyeong Jun, Taehoon Kim, Ji Hyun Lee, Duhee Bang

Abstract read
In one paragraph

Article in Communications biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Hyeonseob Lim *Department of Chemistry, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.ORCID http://orcid.org/0000-0002-9470-4142
Soyeong Jun *Department of Chemistry, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.ORCID http://orcid.org/0000-0001-8419-7098
Taehoon KimDepartment of Chemistry, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.ORCID http://orcid.org/0009-0008-3596-4412
Ji Hyun LeeDepartment of Clinical Pharmacology and Therapeutics, College of Medicine, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul, 02447, Republic of Korea. hyunihyuni@khu.ac.kr.ORCID http://orcid.org/0000-0003-3640-2928
Duhee BangDepartment of Chemistry, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea. duheebang@yonsei.ac.kr.ORCID http://orcid.org/0000-0001-8775-9877

Funding

National Research Foundation of Korea (NRF) 2021R1A2C2008490
6 · The paper itself

Abstract

Molecular barcoding methods enable high-sensitivity detection of circulating tumor DNA that is rarely present in liquid biopsy samples. Many methods involve ligation of molecular barcodes to DNA prior to hybridization capture, enabling recovery of starting molecules. Development of polymerase chain reaction (PCR)-based methods could facilitate more cost- and labor- effective detection; however, tracking molecular identity can be difficult, as new barcodes overwrite old barcodes in each cycle. Here, we present a sensitive genotyping method based on a peer-to-peer network-derived identifier for error reduction in amplicon sequencing (SPIDER-seq) and enable molecular identity tracking with PCR-derived libraries using overwritten barcodes. SPIDER-seq detected mutations at frequences as low as 0.125% after only two consecutive general PCR cycles and systematically analyzed the error pattern in the peer-to-peer network. Our method could facilitate the rapid detection of mutations associated with various cancers.

Indexed as

AllelesCirculating Tumor DNAGene LibraryPolymerase Chain ReactionHumansMutationCirculating Tumor DNA

Identifiers

PMID40707727
PMCPMC12290108

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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.