Avocado: a multi-scale deep tensor factorization method learns a latent representation of the human epigenome.
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ABSTRACT:
SUBMITTER: Schreiber J
PROVIDER: S-EPMC7104480 | biostudies-literature | 2020 Mar
REPOSITORIES: biostudies-literature
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Avocado: a multi-scale deep tensor factorization method learns a latent representation of the human epigenome.
Schreiber Jacob J Durham Timothy T Bilmes Jeffrey J Noble William Stafford WS
Genome biology 20200330 1
The human epigenome has been experimentally characterized by thousands of measurements for every basepair in the human genome. We propose a deep neural network tensor factorization method, Avocado, that compresses this epigenomic data into a dense, information-rich representation. We use this learned representation to impute epigenomic data more accurately than previous methods, and we show that machine learning models that exploit this representation outperform those trained directly on epigeno ...[more]
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