Use cases

A major goal of EUGENe is to streamline end-to-end DL solutions in regulatory genomics. We want to make common tasks that have been published in the field accessible to a broad user base and in doing so hope to make it easy for users to adapt these solutions to their own data. The table below lists several common DL for regulatory genomics tasks that can be analyzed in an end-to-end fashion with EUGENe:

Task	Examples	Potential insights gained	ETL	Training and evaluation	End-to-end currently available?	Interpretation analyses currently available	Example in EUGENe use cases
Single task regression from a tabular file	DeepBind, ResidualBind	Identification and quantification of motif importance on continuous or binary events (e.g. RBP binding)	Yes	Yes	Yes	Filter interpretation, attribution analysis, evolution, GIA	DeepBind
Single track classification of peak regions from a single bed file	DeepBind	Identification and quantification of motif importance on binary events (e.g. TF binding)	Yes	Yes	Yes	Filter interpretation, attribution analysis, evolution, GIA	Kopp21
Multitask track classification (ChIP, ATAC, DNase, etc.) of peak regions from multiple bed files	DeepSEA, DanQ, Basset, Sei, Satori	Identification and quantification of motif importance on biochemical activity (e.g. TF binding, transcription, DNA accessibility, etc.). Variant effects on biochemical activity	Yes	Yes	Yes	Filter interpretation, attribution analysis, evolution, GIA	Basset
Multitask track regression (ChIP, ATAC, DNase, etc.) at binned or base pair resolution	Basenji, Enformer, BPNet	Identification and quantification of motif importance on biochemical activity (e.g. transcription, DNA accessibility, etc. Variant effects on biochemical activity. CRE syntax rules	Yes	Yes	Yes	Filter interpretation, GIA	BPNet
Single task and multitask CRE activity prediction (both regression and classification (multiclass and multilabel)	DeepSTARR, MPRA-DragoNN	Identification and quantification of motif importance on CRE activity. Variant effects on CRE activity. CRE syntax rules	Yes	Yes	Yes	Filter interpretation, attribution analysis, evolution, GIA	DeepSTARR
Single cell ATAC-seq topic classification (multiclass classification)	DeepMEL, DeepMEL2, DeepFlyBrain	Identification and quantification of cell type specific motif importance. Cell type specific variant effect prediction . Cell type specific CRE syntax	Requires preprocessing with pycisTopic	Yes	Yes, with preprocessing performed by pycisTopic	Filter interpretation, attribution analysis, evolution, GIA	DeepMEL
Single cell ATAC-seq cell accessibility prediction*	scBasset	Single cell analysis (denoising, imputation, clustering, etc.). Identification and quantification of cell type specific motif importance	Requires preprocessing with ScanPy	Yes	Yes, with preprocessing performed by ScanPy	Filter interpretation, attribution analysis, evolution, GIA	scBasset

The final column provides a link to a implementated example of this task in EUGENe’s accompanying “use cases” GitHub repository that are described below. Many of these are works in progress and we welcome contributions from the community to help us expand this list. We envision that this list will grow as the field of regulatory genomics continues to develop and new DL solutions are published.