ArticleGenome biology2023
The ENCODE Imputation Challenge: a critical assessment of methods for cross-cell type imputation of epigenomic profiles.
Erratum issuedAbstract read
In one paragraph
Article in Genome biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 papers.
0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
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.
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.
Who cites it
14 citing papers in PubMed.
- Context-aware sequence-to-function model of human gene regulation.Nature communications · 2026Article
- m6AConquer: a consistently quantified and orthogonally validated database for the N6-methyladenosine (m6A) epitranscriptome.Nucleic acids research · 2026Article
- mwHIT: accelerated and accurate histone modification imputation using multi-scale window attention.Frontiers in genetics · 2026Article
- Towards personalized epigenomics: learning shared chromatin landscapes and joint de-noising of histone modification assays.NAR genomics and bioinformatics · 2025Article
- Regulatory genome annotation.Nature reviews. Genetics · 2025Article
- Publisher Correction: The ENCODE Imputation Challenge: a critical assessment of methods for cross-cell type imputation of epigenomic profiles.Genome biology · 2025Article
- Machine learning tools for deciphering the regulatory logic of enhancers in health and disease.Frontiers in genetics · 2025Review
- Predicting cell type-specific epigenomic profiles accounting for distal genetic effects.Nature communications · 2024Article
- dHICA: a deep transformer-based model enables accurate histone imputation from chromatin accessibility.Briefings in bioinformatics · 2024Article
- Robust chromatin state annotation.Genome research · 2024Article
- JMnorm: a novel joint multi-feature normalization method for integrative and comparative epigenomics.Nucleic acids research · 2024Article
- Article
- Getting personal with epigenetics: towards individual-specific epigenomic imputation with machine learning.Nature communications · 2023Article
- A generalizable framework to comprehensively predict epigenome, chromatin organization, and transcriptome.Nucleic acids research · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
43 authors.
Jacob Matthew Schreiber *Department of Genetics, Stanford University, Stanford, CA, USA. jmschreiber91@gmail.com.ORCID http://orcid.org/0000-0003-4230-6625
Carles A Boix *Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.
Jin Wook LeeDepartment of Genetics, Stanford University, Stanford, CA, USA.
Hongyang LiDepartment of computational medicine and bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Yuanfang GuanDepartment of computational medicine and bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Chun-Chieh ChangDepartment of Research and Development, DeepSeq.AI, San Francisco, CA, USA.
Jen-Chien ChangRIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
Alex Hawkins-HookerDepartment of Empirical Inference, Max Planck Institute for Intelligent Systems, Stuttgart, Germany.
Bernhard SchölkopfDepartment of Empirical Inference, Max Planck Institute for Intelligent Systems, Stuttgart, Germany.
Gabriele SchweikertSchool of Life Sciences, University of Dundee, Dundee, UK.
Mateo Rojas CarullaDepartment of Empirical Inference, Max Planck Institute for Intelligent Systems, Stuttgart, Germany.
Arif CanakogluDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy.
Francesco GuzzoDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy.
Luca NanniDepartment of Computational Biology, University of Lausanne, Lausanne, Switzerland.
Marco MasseroliDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy.
Mark James CarmanDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy.
Pietro PinoliDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy.
Chenyang HongDepartment of Computer Science and Engineering, The Chinese University of Hong Kong, Sha Tin, Hong Kong.
Kevin Y YipSanford Burnham Prebys Medical Discovery Institute, San Diego, CA, USA.
Jefrey P SpenceDepartment of Genetics, Stanford University, Stanford, CA, USA.
Sanjit Singh BatraDepartment of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, USA.
Yun S SongDepartment of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, USA.
Shaun MahonyDepartment of Biochemistry & Molecular Biology, Center for Eukaryotic Gene Regulation, Pennsylvania State University, University Park, PA, USA.
Zheng ZhangDepartment of Statistics, Pennsylvania State University, University Park, PA, USA.
Wuwei TanDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA.
Yang ShenDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA.
Yuanfei SunDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA.
Minyi ShiDepartment of Genetics, Stanford University, Stanford, CA, USA.
Jessika AdrianDepartment of Genetics, Stanford University, Stanford, CA, USA.
Richard S SandstromAltius Institute, Seattle, WA, USA.
Nina P FarrellEpigenomics Program, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Jessica M HalowAltius Institute, Seattle, WA, USA.
Kristen LeeAltius Institute, Seattle, WA, USA.
Lixia JiangDepartment of Genetics, Stanford University, Stanford, CA, USA.
Xinqiong YangDepartment of Genetics, Stanford University, Stanford, CA, USA.
Charles B EpsteinEpigenomics Program, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
J Seth StrattanDepartment of Genetics, Stanford University, Stanford, CA, USA.
Bradley E BernsteinEpigenomics Program, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Michael P SnyderDepartment of Genetics, Stanford University, Stanford, CA, USA.
Manolis KellisComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.
William S NobleDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
Anshul Bharat KundajeDepartment of Genetics, Stanford University, Stanford, CA, USA.
ENCODE Imputation Challenge Participants
Funding
INSTITUTIONAL TRAINING GRANT IN GENOME SCIENCET32HG000044 · NHGRI · STANFORD UNIVERSITY · PI MICHAEL P. SNYDER · 1995 to 2026
$32.2MA Data Coordinating Center for ENCODEU24HG009397 · NHGRI · STANFORD UNIVERSITY · PI CHERRY, J. MICHAEL · 2017 to 2023
$26.0MPRODUCTION CENTER FOR MAPPING REGULATORY REGIONS OF THE HUMAN GENOMEUM1HG009442 · NHGRI · STANFORD UNIVERSITY · PI SNYDER, MICHAEL P. · 2017 to 2021
$20.1MENCODE Mapping Center-A Comprehensive Catalog of DNase I Hypersensitive SitesUM1HG009444 · NHGRI · ALTIUS INSTITUTE FOR BIOMEDICAL SCIENCES · PI STAMATOYANNOPOULOS, JOHN A · 2017 to 2021
$15.9MA Catalog of Cell Types and Genomic Elements in Tissues, Organoids and DiseaseUM1HG009390 · NHGRI · BROAD INSTITUTE, INC. · PI BERNSTEIN, BRADLEY EVAN · 2017 to 2021
$11.0MEDAC: ENCODE Data Analysis CenterU24HG009446 · NHGRI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI GERSTEIN, MARK BENDER, WENG, ZHIPING · 2017 to 2022
$10.4MPredicting context-specific molecular and phenotypic effects of genetic variation through the lens of the cis-regulatory codeU01HG012069 · NHGRI · STANFORD UNIVERSITY · PI Anshul Kundaje · 2021 to 2026
$3.9MMachine Learning for Drug Response PredictionR35GM133346 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Yuanfang Guan · 2019 to 2026
$3.2MUnraveling molecular and system-level mechanisms of human disease-associated protein mutationsR35GM124952 · NIGMS · TEXAS ENGINEERING EXPERIMENT STATION · PI Yang Shen · 2017 to 2026
$2.9MInterpreting non-coding variants using epigenomics, regulatory models, & validation experimentsR01HG008155 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI KELLIS, MANOLIS · 2015 to 2017
$2.3MRobust and efficient statistical inference methods for genomicsR35GM134922 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI SONG, YUN S · 2020 to 2024
$2.0MDeep tensor genomic imputationR01HG011466 · NHGRI · UNIVERSITY OF WASHINGTON · PI NOBLE, WILLIAM STAFFORD · 2021 to 2024
$1.5MNHGRI NIH HHS R01 HG008155NHGRI NIH HHS R01 HG011466NHGRI NIH HHS T32 HG000044NHGRI NIH HHS U01 HG012069NHGRI NIH HHS U24 HG009397NHGRI NIH HHS U24 HG009446NHGRI NIH HHS UM1 HG009390NHGRI NIH HHS UM1 HG009442NHGRI NIH HHS UM1 HG009444NIGMS NIH HHS R35 GM124952NIGMS NIH HHS R35 GM133346NIGMS NIH HHS R35 GM134922
Abstract
A promising alternative to comprehensively performing genomics experiments is to, instead, perform a subset of experiments and use computational methods to impute the remainder. However, identifying the best imputation methods and what measures meaningfully evaluate performance are open questions. We address these questions by comprehensively analyzing 23 methods from the ENCODE Imputation Challenge. We find that imputation evaluations are challenging and confounded by distributional shifts from differences in data collection and processing over time, the amount of available data, and redundancy among performance measures. Our analyses suggest simple steps for overcoming these issues and promising directions for more robust research.
Indexed as
AlgorithmsEpigenomicsGenomics
Identifiers
What Socratic holds
Textmetadata
LicenceCC BY
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 Socratic graph.