DeepSEA

Categories: Healthcare, Research, Environment & Science | Pricing: Free | Official Website ↗

DeepSEA is a deep learning-based framework for predicting the chromatin effects of sequence alterations with single nucleotide sensitivity.

DeepSEA utilizes deep learning to accurately predict the epigenetic state of a sequence, including transcription factor binding, DNase I sensitivities, and histone marks across multiple cell types. This capability is then used to predict the chromatin effects of sequence variants and prioritize regulatory variants, aiding in genomic research.

Key Features

Deep learning-based predictions
Chromatin effects prediction
Epigenetic state prediction
Transcription factor binding prediction
DNase I sensitivity prediction
Histone mark prediction
Regulatory variant prioritization

Pros

Predicts epigenetic states accurately
Identifies chromatin effects of sequence variants
Prioritizes regulatory variants
Single nucleotide sensitivity
Supports multiple cell types

Cons

Requires specific file formats (VCF, FASTA, BED)
Sequence length constraint for FASTA (1000bp)
BED file difference constraint (1000 or less)
Limited to hg19 coordinates
No explicit mention of user-friendly interface for non-experts

Use Cases

Analyzing genetic sequence alterations
Prioritizing disease-causing regulatory variants
Understanding epigenetic regulation
Predicting protein binding sites on DNA
Investigating chromatin accessibility

Best For

Genomic researchers
Bioinformaticians
Geneticists
Computational biologists

Platforms: web

Watch demo on YouTube ↗

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