Evidence map›Paper›PMID 42327171›Full record

ArticlebioRxiv : the preprint server for biology2026

PanKbase Integrated Single-Cell Map: A Comprehensive Atlas of Human Pancreatic Islets.

Ha T H Vu, Han Sun, Parul Kudtarkar, Seth A Sharp, Liza Brusman, Fan Feng, Thomas Bate, Julie A Jurgens, Yiqun Wang, Yuanhao Huang and 25 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. 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

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

35 authors.

Ha T H VuGilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0003-4161-5952
Han SunDepartment of Pediatrics, Stanford School of Medicine, Stanford University, CA, USA.
Parul KudtarkarDepartment of Pediatrics, University of California, San Diego, La Jolla, CA, USA.
Seth A SharpDepartment of Pediatrics, Stanford School of Medicine, Stanford University, CA, USA.
Liza BrusmanDepartment of Pediatrics, University of California, San Diego, La Jolla, CA, USA.
Fan FengDepartment of Medicine, Division of Diabetes, Endocrinology and Metabolism, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Thomas BateDepartment of Medicine, Division of Diabetes, Endocrinology and Metabolism, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Julie A JurgensPrograms in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Yiqun WangGilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Yuanhao HuangGilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Runbo MaoGilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Sierra CorbanDepartment of Pediatrics, University of California, San Diego, La Jolla, CA, USA.
Amanda K HuberGilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0003-0375-8709
Alex ShilinPrograms in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Ying SunDepartment of Pediatrics, University of California, San Diego, La Jolla, CA, USA.
Sara NarayanaswamyDepartment of Pediatrics, University of California, San Diego, La Jolla, CA, USA.
Dongkeun JangPrograms in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Catherine C RobertsonGilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Shristi ShresthaDepartment of Medicine, Division of Diabetes, Endocrinology and Metabolism, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Trang NguyenPrograms in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Patrick SmadbeckPrograms in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Lu ZhangDepartment of Pediatrics, Stanford School of Medicine, Stanford University, CA, USA.
Mackenzie BrandesPrograms in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
PanKbase Consortium
Jason FlannickPrograms in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Noel BurttPrograms in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Shuibing ChenDepartment of Surgery, Weill Cornell Medicine, New York, NY, USA.
Jie LiuGilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Jean-Philippe CartaillerCenter for Stem Cell Biology, Vanderbilt University, Nashville, Tennessee, USA.
Benjamin F VoightDepartment of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Michael L StitzelThe Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
Marcela BrissovaDepartment of Medicine, Division of Diabetes, Endocrinology and Metabolism, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Anna L GloynDepartment of Pediatrics, Stanford School of Medicine, Stanford University, CA, USA.ORCID 0000-0003-1205-1844
Kyle J GaultonDepartment of Pediatrics, University of California, San Diego, La Jolla, CA, USA.
Stephen C J ParkerGilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.

Funding

The Human Islet Distribution Coordinating Center (UC4)UC4DK098085 · NIDDK · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · PI EVANS-MOLINA, CARMELLA, NILAND, JOYCE CAROL · 2012 to 2017
$25.6M
The Human Pancreas Analysis Program for Type 2 DiabetesU01DK123594 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI Robert Babak Faryabi, KLAUS H KAESTNER · 2019 to 2026
$25.0M
Penn integrated Human Pancreas procurement and Analysis ProgramUC4DK112217 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI BETTS, MICHAEL R, FELDMAN, MICHAEL D · 2016 to 2020
$17.8M
PanKbase: a community hub for integrated pancreas knowledgeU24DK138515 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Marcela Brissova, Jean-Philippe Cartailler · 2024 to 2026
$11.3M
An interactive resource to generate and provide integrated knowledge of the human pancreasU24DK138512 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Noel P Burtt, Jason Flannick · 2024 to 2026
$9.6M
Supplement to Integrated Program for Human Pancreas Procurement and AnalysisUC4DK112232 · NIDDK · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ATKINSON, MARK A., POWERS, ALVIN C · 2016 to 2020
$8.4M
Human Pancreas Analysis Program-T2DU01DK123716 · NIDDK · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ATKINSON, MARK A., BOTTINO, RITA · 2019 to 2024
$6.6M
NIDDK NIH HHS U01 DK123594NIDDK NIH HHS U01 DK123716NIDDK NIH HHS U24 DK138512NIDDK NIH HHS U24 DK138515NIDDK NIH HHS UC4 DK098085NIDDK NIH HHS UC4 DK112217NIDDK NIH HHS UC4 DK112232
6 · The paper itself

Abstract

Single-cell RNA sequencing (scRNA-seq) of human pancreatic islet tissue is a powerful tool for investigating type 1 diabetes (T1D). However, individual datasets are limited in size and fragmented across donors, laboratories, and experimental conditions. To address this, we constructed a comprehensive, integrated scRNA-seq atlas of isolated human pancreatic islets by collating publicly available data generated from tissue provided by resources including the Human Pancreas Analysis Program, the Integrated Islet Distribution Program, and Prodo Labs. Systematic quality controls were implemented to select high-quality samples, reads, and cells. During integration, we accounted for important variables such as age, sex, body mass index, origin study, treatments, islet distribution resources, and sequencing chemistry. Our single-cell atlas comprises 191 high-quality samples from 140 donors (59 female, 81 male) across five phenotypic groups: no diabetes (controls, n=69), autoantibody positivity without diabetes (n=12), pre-diabetes (n=11), T1D (n=12), and type 2 diabetes (T2D) (n=36). In total, the atlas contains 448,935 cells, capturing 13 distinct populations, including alpha cells (43.3%) and beta cells (26.8%), as well as groups such as immune cells (0.6%). Publicly available at www.pankbase.org, this atlas provides a platform for hypothesis-driven investigation of diabetes pathophysiology and, given rigorous quality control, is well-suited for downstream machine-learning applications.

Identifiers

PMID42327171
PMCPMC13278015

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.