BindVAE: Dirichlet variational autoencoders for de novo motif discovery from accessible chromatin

BindVAE: Dirichlet variational autoencoders for de novo motif discovery from accessible chromatin

Abstract We present a novel unsupervised deep learning approach called BindVAE, based on Dirichlet variational autoencoders, for jointly decoding multiple TF binding signals from open chromatin regions. BindVAE can disentangle an input DNA sequence into distinct latent factors that encode cell-type...

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Bibliographic Details
Main Authors: Meghana Kshirsagar, Han Yuan, Juan Lavista Ferres, Christina Leslie
Format: Article
Language:English
Published: BMC 2022-08-01
Series:Genome Biology
Subjects:
ATAC-seq
Transcription factor
Dirichlet
Variational autoencoders
VAE
k-mers
Online Access:https://doi.org/10.1186/s13059-022-02723-w

Internet

https://doi.org/10.1186/s13059-022-02723-w

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