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Your search keyword '"Jefrey P. Spence"' showing total 2 results
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2 results on '"Jefrey P. Spence"'

1. Publisher Correction: The ENCODE Imputation Challenge: a critical assessment of methods for cross-cell type imputation of epigenomic profiles

Author

Jacob Matthew Schreiber, Carles A. Boix, Jin wook Lee, Hongyang Li, Yuanfang Guan, Chun-Chieh Chang, Jen-Chien Chang, Alex Hawkins-Hooker, Bernhard Schölkopf, Gabriele Schweikert, Mateo Rojas Carulla, Arif Canakoglu, Francesco Guzzo, Luca Nanni, Marco Masseroli, Mark James Carman, Pietro Pinoli, Chenyang Hong, Kevin Y. Yip, Jefrey P. Spence, Sanjit Singh Batra, Yun S. Song, Shaun Mahony, Zheng Zhang, Wuwei Tan, Yang Shen, Yuanfei Sun, Minyi Shi, Jessika Adrian, Richard S. Sandstrom, Nina P. Farrell, Jessica M. Halow, Kristen Lee, Lixia Jiang, Xinqiong Yang, Charles B. Epstein, J. Seth Strattan, Bradley E. Bernstein, Michael P. Snyder, Manolis Kellis, William S. Noble, Anshul Bharat Kundaje, and ENCODE Imputation Challenge Participants

Subjects
Biology (General), QH301-705.5, Genetics, QH426-470
Published
2025
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2. The ENCODE Imputation Challenge: a critical assessment of methods for cross-cell type imputation of epigenomic profiles

Author

Jacob Matthew Schreiber, Carles A. Boix, Jin wook Lee, Hongyang Li, Yuanfang Guan, Chun-Chieh Chang, Jen-Chien Chang, Alex Hawkins-Hooker, Bernhard Schölkopf, Gabriele Schweikert, Mateo Rojas Carulla, Arif Canakoglu, Francesco Guzzo, Luca Nanni, Marco Masseroli, Mark James Carman, Pietro Pinoli, Chenyang Hong, Kevin Y. Yip, Jefrey P. Spence, Sanjit Singh Batra, Yun S. Song, Shaun Mahony, Zheng Zhang, Wuwei Tan, Yang Shen, Yuanfei Sun, Minyi Shi, Jessika Adrian, Richard S. Sandstrom, Nina P. Farrell, Jessica M. Halow, Kristen Lee, Lixia Jiang, Xinqiong Yang, Charles B. Epstein, J. Seth Strattan, Bradley E. Bernstein, Michael P. Snyder, Manolis Kellis, William S. Noble, Anshul Bharat Kundaje, and ENCODE Imputation Challenge Participants

Subjects
Biology (General), QH301-705.5, Genetics, QH426-470
Abstract

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.

Published
2023
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