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

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

April 2023 Genome Biol

Synopsis of Social media discussions

Several posts discuss how the article critically assesses the difficulties in evaluating imputation methods due to factors like data variability and distributional shifts, using words like 'challenges' and 'highlights' to emphasize the study’s significance. The tone balances respect for the thoroughness of the research with recognition of the complex issues in the field, showing both admiration and a desire to understand these advancements deeply.

A
Agreement
 Moderate agreement

Most discussions acknowledge the importance and relevance of the study, with some posts expressing support for its detailed evaluation of imputation methods.

I
Interest
 High level of interest

Posts demonstrate high curiosity, especially with mentions of the publication's years-long effort and the challenges in data evaluation, indicating active engagement.

E
Engagement
 Moderate level of engagement

There is some deep engagement, reflected in comments about methodological challenges, data processing mistakes, and appreciation for the comprehensive analysis.

I
Impact
 Moderate level of impact

While the discussions highlight the significance of understanding imputation methods, there is a moderate perception of immediate high impact, mostly emphasizing ongoing research and future improvements.

Social Mentions

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42 Posts

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Social Features

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Posts referencing the article

Assessing Cross-Cell Type Imputation Methods in Genomics Studies

Assessing Cross-Cell Type Imputation Methods in Genomics Studies

This video reviews 23 methods from the ENCODE Imputation Challenge, exploring the challenges in evaluating imputation performance and highlighting future research directions to enhance genomics data analysis.

Social RTCL TV

July 31, 2023

20 views

  • Arthur Liberzon
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    RT @jmschreiber91: @tangming2005 Making those mistakes or describing them? I've written a few describing them. Mistakes in performing ML g…
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    RT @jmschreiber91: @tangming2005 Making those mistakes or describing them? I've written a few describing them. Mistakes in performing ML g…
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    RT @jmschreiber91: @tangming2005 Making those mistakes or describing them? I've written a few describing them. Mistakes in performing ML g…
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    RT @jmschreiber91: @tangming2005 Making those mistakes or describing them? I've written a few describing them. Mistakes in performing ML g…
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    RT @jmschreiber91: @tangming2005 Making those mistakes or describing them? I've written a few describing them. Mistakes in performing ML g…
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  • Jacob Schreiber
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    @tangming2005 Making those mistakes or describing them? I've written a few describing them. Mistakes in performing ML generally: (1) https://t.co/c5S73P946f (2) https://t.co/04t5ew7CKq Mistakes in data processing: https://t.co/6vt8CTli7j
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    The ENCODE Imputation Challenge: a critical assessment of methods for cross-cell type imputation of epigenomic profiles | Genome Biology https://t.co/jxFqUMdnCY #Bioinformatics https://t.co/ATu0swWNuW
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    April 30, 2023

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    The ENCODE Imputation Challenge: a critical assessment of methods for cross-cell type imputation of epigenomic profiles. #Imputation #Epigenomics #ENCODE #ToolsBenchmarking @GenomeBiology https://t.co/aRIUPsCwar
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    April 29, 2023

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    RT @jmschreiber91: Finally, after ~6 years of work, this is published! https://t.co/6vt8CTli7j Thanks to all my co-authors and the partici…
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    RT @jmschreiber91: Finally, after ~6 years of work, this is published! https://t.co/6vt8CTli7j Thanks to all my co-authors and the partici…
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  • Nathan Skene
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    RT @GenomeBiology: Analysis of the ENCODE Imputation Challenge by @jmschreiber91 @boix_carles & co. @StanfordMed highlights how imputation…
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    April 19, 2023

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  • Joseph D. Janizek
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  • Jacob Schreiber
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    Finally, after ~6 years of work, this is published! https://t.co/6vt8CTli7j Thanks to all my co-authors and the participants of the challenge for seeing this through. https://t.co/1u8ZfmpoWz
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  • Genome Biology
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    Analysis of the ENCODE Imputation Challenge by @jmschreiber91 @boix_carles & co. @StanfordMed highlights how imputation evaluations are challenging & confounded by distributional shifts; and therefore suggest simple steps for overcoming these issues https://t.co/fUOJSiHdRr https://t.co/5DhsJFWvFF
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    April 19, 2023

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    #bioRxiv The ENCODE Imputation Challenge: A critical assessment of methods for cross-cell type imputation of epigenomic profiles #bioinfo https://t.co/CM0kjXlmXj
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    The ENCODE Imputation Challenge: A critical assessment of methods for cross-cell type imputation of epigenomic profiles https://t.co/6EStHzWWzf #biorxiv_bioinfo
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Abstract Synopsis

  • A new approach to genomics experiments involves doing fewer experiments and using computational methods to fill in the gaps, but there are still uncertainties about which imputation methods work best and how to evaluate their performance effectively.* -
  • The study reviews 23 different methods from the ENCODE Imputation Challenge and discovers that assessing these methods is complicated by factors like changes in data collection practices, varying amounts of data, and overlapping evaluation metrics.* -
  • The authors suggest practical solutions to these challenges and highlight promising areas for future research to improve the robustness of imputation methods in genomics.*