Model group Models Authors Contributed by Type Cite as License Tags
Model group Models Authors Contributed by Type Cite as License Tags
AttentiveChrome 55 Ritambhara Singh et al. Jack Lanchantin et al. pytorch https://doi.org:/10.1101/329334 MIT
BPNet-OSKN 1 Žiga Avsec et al. Ziga Avsec None https://doi.org/10.1101/737981 MIT
Basenji 1 David R. Kelley et al. Ziga Avsec tensorflow https://doi.org/10.1101/gr.227819.117 Apache License v2 RNA expression, Histone modification, DNA accessibility
Basset 1 David R. Kelley et al. Roman Kreuzhuber pytorch https://doi.org/10.1101/gr.200535.115 MIT DNA accessibility
CleTimer 2 Leohnard Wachutka et al. Leohnard Wachutka et al. None Apache License v2 RNA splicing
CpGenie 51 Haoyang Zeng et al. Roman Kreuzhuber custom, keras https://doi.org/10.1093/nar/gkx177 Apache License v2 DNA methylation
DeepBind 927 Babak Alipanahi et al. Johnny Israeli keras https://doi.org/10.1038/nbt.3300 BSD 3-Clause DNA binding
DeepCpG_DNA 5 Christof Angermueller et al. Roman Kreuzhuber keras https://doi.org/10.1186/s13059-017-1189-z
https://doi.org/10.5281/zenodo.1094823
MIT DNA methylation
DeepSEA 3 Jian Zhou et al. Roman Kreuzhuber None, pytorch https://doi.org/10.1038/s41588-018-0160-6
https://doi.org/10.1038/nmeth.3547
Non-comercial, CC-BY 3.0 Histone modification, DNA binding, DNA accessibility
Divergent421 1 Nancy Xu Nancy Xu None MIT DNA accessibility
FactorNet 30 Daniel Quang et al. Ziga Avsec keras https://doi.org/10.1101/151274 MIT DNA binding
HAL 1 Alexander B. Rosenberg et al. Jun Cheng et al. None https://doi.org/10.1016/j.cell.2015.09.054 MIT RNA splicing
KipoiSplice 2 Žiga Avsec et al. Ziga Avsec et al. sklearn https://doi.org/10.1101/375345 MIT RNA splicing
MMSplice 10 Jun Cheng et al. Jun Cheng et al. custom, keras MIT RNA splicing
MPRA-DragoNN 2 Rajiv Movva et al. Rajiv Movva, Surag Nair None https://doi.org/10.1101/393926 MIT
MaxEntScan 2 Gene Yeo et al. Jun Cheng et al. None https://doi.org/10.1089/1066527041410418 MIT RNA splicing
Optimus_5Prime 1 Paul J. Sample et al. Ban Wang None https://doi.org/10.1101/310375 MIT Translation
SeqVec 3 Michael Heinzinger et al. Michael Heinzinger, Ahmed Elnaggar et al. None https://doi.org/10.1101/614313
https://doi.org:/10.1101/614313
MIT
SiSp 1 Stephanie M. Linker et al. Lara Urban keras https://doi.org/10.1101/328138 MIT RNA splicing
deepTarget 1 Byunghan Lee et al. Ziga Avsec None https://arxiv.org/pdf/1603.09123.pdf GPL-v3 RNA binding
extended_coda 1 Pang Wei Koh et al. Johnny Israeli keras https://doi.org/10.1093/bioinformatics/btx243 MIT Histone modification
labranchor 1 Joseph M. Paggi et al. Jun Cheng keras https://doi.org/10.1101/185868 CC BY-NC 4.0 RNA splicing
lsgkm-SVM 322 Dongwon Lee Roman Kreuzhuber None https://doi.org/10.1093/bioinformatics/btw142 MIT
pwm_HOCOMOCO 600 Ivan V. Kulakovskiy et al. Ziga Avsec keras https://doi.org/10.1093/nar/gkv1249 MIT DNA binding
rbp_eclip 112 Žiga Avsec et al. Ziga Avsec keras https://doi.org/10.1093/bioinformatics/btx727 MIT RNA binding

Kipoi models

CircleCI DOI

This repository hosts predictive models for genomics and serves as a model source for Kipoi. Each folder containing model.yaml is considered to be a single model.

Contributing models

  1. Install kipoi:

    pip install kipoi

  2. Run kipoi ls. This will checkout the kipoi/models repo to ~/.kipoi/models)

  3. Follow the instructions on contributing/Getting started.

Using models (to predict, score variants, build new models)

To explore available models, visit http://kipoi.org/models. See kipoi/README.md and docs/using getting started for more information on how to programatically access the models from this repository using CLI, python or R.

Configuring local storage location

This model source (https://github.com/kipoi/models) is included in the Kipoi config file (~/.kipoi/config.yaml) by default:

# ~/.kipoi/config.yaml
model_sources:
    kipoi:
        type: git-lfs
        remote_url: [email protected]:kipoi/models.git
        local_path: ~/.kipoi/models/
        auto_update: True

If you wish to keep the models stored elsewhere, edit the local_path accordingly.