| type: pytorch | |
| args: | |
| module_file: pretrained_model_reloaded_th.py | |
| module_obj: model | |
| weights: | |
| md5: 4878981d84499eb575abd0f3b45570d3 | |
| url: https://zenodo.org/record/1466068/files/pretrained_model_reloaded_th.pth?download=1 | |
| default_dataloader: | |
| defined_as: kipoiseq.dataloaders.SeqIntervalDl | |
| default_args: | |
| alphabet_axis: 0 | |
| auto_resize_len: 600 | |
| dtype: np.float32 | |
| dummy_axis: 2 | |
| dependencies: | |
| conda: | |
| - python=3.6 | |
| - h5py=2.10.0 | |
| - _pytorch_select=0.2=gpu_0 | |
| - pytorch=1.3.1=cuda100py36h53c1284_0 | |
| - pip=20.3.3 | |
| - pysam=0.15.3 | |
| - cython=0.29.23 | |
| pip: | |
| - kipoiseq | |
| info: | |
| authors: | |
| - github: davek44 | |
| name: David R. Kelley | |
| cite_as: https://doi.org/10.1101/gr.200535.115 | |
| contributors: | |
| - github: krrome | |
| name: Roman Kreuzhuber | |
| trained_on: "From 2,071,886 total sites, 71,886 randomly reserved for testing and 70,000 for validation, leaving 1,930,000 for training." | |
| doc: "This is the Basset model published by David Kelley converted to pytorch by\ | |
| \ Roman Kreuzhuber. It categorically predicts probabilities of accesible genomic\ | |
| \ regions in 164 cell types (ENCODE project and Roadmap Epigenomics Consortium). Data was generated using DNAse-seq. The sequence\ | |
| \ length the model uses as input is 600bp. The input of the tensor has to be (N,\ | |
| \ 4, 600, 1) for N samples, 600bp window size and 4 nucleotides. Per sample, 164\ | |
| \ probabilities of accessible chromatin will be predicted. \n" | |
| license: MIT | |
| name: Basset | |
| tags: | |
| - DNA accessibility | |
| version: 0.1.0 | |
| schema: | |
| inputs: | |
| associated_metadata: ranges | |
| doc: DNA sequence | |
| name: seq | |
| shape: (4,600,1) | |
| special_type: DNASeq | |
| targets: | |
| column_labels: | |
| - target_labels.txt | |
| doc: Probability of accessible chromatin in 164 cell types | |
| name: DHS_probs | |
| shape: (164, ) | |
| test: | |
| expect: | |
| url: https://s3.eu-central-1.amazonaws.com/kipoi-models/predictions/14f9bf4b49e21c7b31e8f6d6b9fc69ed88e25f43/Basset/predictions.h5 | |
| md5: 9df59f9899b27e65ab95426cb9557ad3 |