Evidence map›Paper›PMID 30737237›Full record

ArticleGenome research2019

Comprehensive, integrated, and phased whole-genome analysis of the primary ENCODE cell line K562.

Bo Zhou, Steve S Ho, Stephanie U Greer, Xiaowei Zhu, John M Bell, Joseph G Arthur, Noah Spies, Xianglong Zhang, Seunggyu Byeon, Reenal Pattni and 9 more

Open access · bronzeAbstract read
In one paragraph

Article in Genome research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 83 papers.

0numbers the graph read from it
0cells of the map it votes in
83citing 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

83 citing papers in PubMed, 138 citations in OpenAlex.

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  8. Distinguishing causal from tagging enhancers using single-cell multiome data.medRxiv : the preprint server for health sciences · 2026
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23 more citing papers are in PubMed but not listed here.

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

19 authors at 5 institutions in 3 countries.

Bo ZhouDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California 94305, USA.ORCID 0000-0001-6533-7462
Steve S HoDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California 94305, USA.ORCID 0000-0002-6685-774X
Stephanie U GreerDivision of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, California 94305, USA.
Xiaowei ZhuDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California 94305, USA.ORCID 0000-0002-5731-3177
John M BellStanford Genome Technology Center, Stanford University, Palo Alto, California 94304, USA.
Joseph G ArthurDepartment of Statistics, Stanford University, Stanford, California 94305, USA.ORCID 0000-0002-4875-0367
Noah SpiesDepartment of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA.ORCID 0000-0002-6759-9842
Xianglong ZhangDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California 94305, USA.ORCID 0000-0003-0977-5673
Seunggyu ByeonSchool of Computer Science and Engineering, College of Engineering, Pusan National University, Busan 46241, South Korea.ORCID 0000-0001-5128-8495
Reenal PattniDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California 94305, USA.ORCID 0000-0003-4490-731X
Noa Ben-EfraimDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California 94305, USA.
Michael S HaneyDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California 94305, USA.ORCID 0000-0001-7381-4054
Rajini R HaraksinghDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California 94305, USA.ORCID 0000-0002-6644-8874
Giltae SongSchool of Computer Science and Engineering, College of Engineering, Pusan National University, Busan 46241, South Korea.ORCID 0000-0001-8796-4678
Hanlee P JiDivision of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, California 94305, USA.
Dimitri PerrinScience and Engineering Faculty, Queensland University of Technology, Brisbane, QLD 4001, Australia.ORCID 0000-0002-4007-5256
Wing H WongDepartment of Statistics, Stanford University, Stanford, California 94305, USA.
Alexej AbyzovDepartment of Health Sciences Research, Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota 55905, USA.ORCID 0000-0001-5405-6729
Alexander E UrbanDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California 94305, USA.ORCID 0000-0001-9772-933X
Stanford University · USPusan National University · KRMayo Clinic · USNational Institute of Standards and Technology · USQueensland University of Technology · AU

Funding

WHOLE YEAST GENOME TRANSCRIPTIONAL AND FUNCTIONAL GENE MAPS--A FEASIBILITY STUDYP01HG000205 · NHGRI · STANFORD UNIVERSITY · PI DAVIS, RONALD WAYNE, HOWE, ROGER THOMAS · 1990 to 2016
$120.9M
Special EquipmentP50HG007735 · NHGRI · STANFORD UNIVERSITY · PI CHANG, HOWARD Y · 2014 to 2018
$15.2M
Multi-Institutional Training in Genetic/Genomic Approaches to Sleep DisordersT32HL110952 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI CHERVIN, RONALD D, MIGNOT, EMMANUEL J · 2013 to 2022
$5.0M
Statistical Models for Genome Sequencing and AssociationR01HG006137 · NHGRI · UNIVERSITY OF PENNSYLVANIA · PI JI, HANLEE P, ZHANG, NANCY R · 2011 to 2022
$4.3M
Detection of somatic, subclonal and mosaic CNVs from sequencingU24CA220242 · NCI · MAYO CLINIC ROCHESTER · PI ABYZOV, ALEXEJ · 2018 to 2022
$2.6M
Statistical and computational analysis in whole genome sequencing studies.R01HG007834 · NHGRI · STANFORD UNIVERSITY · PI WONG, WING H. · 2014 to 2016
$892k
Interdisciplinary Training Program in Biostatistics and Personalized MedicineT32GM096982 · NIGMS · STANFORD UNIVERSITY · PI OLSHEN, RICHARD ALLEN, SABATTI, CHIARA · 2012 to 2016
$829k
NCI NIH HHS U24 CA220242NHGRI NIH HHS P01 HG000205NHGRI NIH HHS P50 HG007735NHGRI NIH HHS R01 HG006137NHGRI NIH HHS R01 HG007834NHLBI NIH HHS T32 HL110952NIGMS NIH HHS T32 GM096982
6 · The paper itself

Abstract

K562 is widely used in biomedical research. It is one of three tier-one cell lines of ENCODE and also most commonly used for large-scale CRISPR/Cas9 screens. Although its functional genomic and epigenomic characteristics have been extensively studied, its genome sequence and genomic structural features have never been comprehensively analyzed. Such information is essential for the correct interpretation and understanding of the vast troves of existing functional genomics and epigenomics data for K562. We performed and integrated deep-coverage whole-genome (short-insert), mate-pair, and linked-read sequencing as well as karyotyping and array CGH analysis to identify a wide spectrum of genome characteristics in K562: copy numbers (CN) of aneuploid chromosome segments at high-resolution, SNVs and indels (both corrected for CN in aneuploid regions), loss of heterozygosity, megabase-scale phased haplotypes often spanning entire chromosome arms, structural variants (SVs), including small and large-scale complex SVs and nonreference retrotransposon insertions. Many SVs were phased, assembled, and experimentally validated. We identified multiple allele-specific deletions and duplications within the tumor suppressor gene

Indexed as

Genome, HumanHumansK562 CellsKaryotypePolymorphism, GeneticWhole Genome Sequencing

Identifiers

PMID30737237
PMCPMC6396411
OpenAlexW2951759798

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

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.