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CNN models for epidermal differentiation - Basset style, tensorflow
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| to make models Kipoi compatible, first generated a file of the original | ||
| models with checkpoints - `models_orig.tsv`. | ||
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| this was the input to `run_kipoi_compatibility.py`, which inserted placeholder | ||
| ops into the metagraph. these new graphs were saved to a new dir, and | ||
| confirmed to run with kipoi test. | ||
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| these files were uploaded to zenodo with `upload_zenodo.py`. | ||
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| then the links were put into a new models.tsv table with update_w_zenodo_links.py. | ||
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| these links were then used with the files to generate a folder for each model. | ||
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| testing is done per folder, see script `run_tests.py`. |
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| defined_as: kipoi.model.TensorFlowModel | ||
| args: # arguments of kipoi.model.TensorFlowModel | ||
| input_nodes: "inputs" | ||
| target_nodes: "basset/logits/biases/RMSProp_1" | ||
| checkpoint_path: | ||
| meta: | ||
| url: models.kipoi_compatible/encode-roadmap.basset.clf.testfold-0.model.meta | ||
| md5: 0bb5678c3651564e37fdad5c4b875cd2 | ||
| index: | ||
| url: models.kipoi_compatible/encode-roadmap.basset.clf.testfold-0.model.index | ||
| md5: cf33d8cd0a359a53381d66ee4c762542 | ||
| data: | ||
| url: models.kipoi_compatible/encode-roadmap.basset.clf.testfold-0.model.data-00000-of-00001 | ||
| md5: 2f1d71990db937fb83586dc191863e1a | ||
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| default_dataloader: | ||
| defined_as: kipoiseq.dataloaders.SeqIntervalDl | ||
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| default_args: # Optional arguments to the SeqIntervalDl dataloader | ||
| # See also https://kipoi.org/kipoiseq/dataloaders/#seqintervaldl | ||
| auto_resize_len: 1000 # Automatically resize sequence intervals | ||
| alphabet_axis: 2 | ||
| dummy_axis: 0 # Add a dummy axis. Omit in order not to create dummy_axis. | ||
| alphabet: "ACGT" # Order of letters in 1-hot encoding | ||
| ignore_targets: False # if True, dont return any target variables | ||
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| info: # General information about the model | ||
| authors: | ||
| - name: Daniel Kim | ||
| github: vervacity | ||
| email: [email protected] | ||
| doc: Model predicting accessibility/chromatin marks from sequence | ||
| cite_as: https://doi.org:/... # preferably a doi url to the paper | ||
| trained_on: see README | ||
| license: MIT # Software License - if not set defaults to MIT | ||
| # You can also specify the license in the LICENSE file | ||
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| dependencies: | ||
| conda: # install via conda | ||
| - python=2.7 | ||
| - h5py | ||
| pip: # install via pip | ||
| #- keras>=2.0.4 | ||
| - tensorflow>=1.8 | ||
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| schema: # Model schema. The schema defintion is essential for kipoi plug-ins to work. | ||
| inputs: # input = single numpy array | ||
| shape: (1,1000,4) # array shape of a single sample (omitting the batch dimension) | ||
| doc: input feature description | ||
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| # inputs: # input = dictionary of fields | ||
| # seq: | ||
| # shape: (100,4) | ||
| # doc: input feature description | ||
| # other_track: | ||
| # shape: (50,) | ||
| # doc: input feature description | ||
| targets: | ||
| shape: (1996,) | ||
| doc: model prediction description |
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| model args_meta_url args_meta_md5 args_index_url args_index_md5 args_data_url args_data_md5 | ||
| encode-roadmap.basset.clf.testfold-0 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-0.model.meta 0bb5678c3651564e37fdad5c4b875cd2 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-0.model.index cf33d8cd0a359a53381d66ee4c762542 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-0.model.data-00000-of-00001 2f1d71990db937fb83586dc191863e1a | ||
| encode-roadmap.basset.clf.testfold-1 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-1.model.meta 3b24a69ecd953cb8e341fe134f46e3d9 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-1.model.index 8eaf8751af57976c35f770dc6498148f models.kipoi_compatible/encode-roadmap.basset.clf.testfold-1.model.data-00000-of-00001 499918cb6cd189200cdc8b8107634a4a | ||
| encode-roadmap.basset.clf.testfold-2 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-2.model.meta 708a9c8d20e2361242b3e63f0df84137 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-2.model.index 0489c73298dbb124ec45b02a2a6f1637 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-2.model.data-00000-of-00001 9127e729f247cb4e7b9973381a69b28e | ||
| encode-roadmap.basset.clf.testfold-3 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-3.model.meta 623f8a17121d98cf8f7993f25d330705 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-3.model.index cbb20d8327c3a0cdc0a708b05ca971cd models.kipoi_compatible/encode-roadmap.basset.clf.testfold-3.model.data-00000-of-00001 fd2997d78156594ea04196a18379e2fc | ||
| encode-roadmap.basset.clf.testfold-4 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-4.model.meta 3be06b38124f68700a423e43935bfe51 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-4.model.index b5c3978cce00de7a1a339a48b7697119 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-4.model.data-00000-of-00001 57508c46ffe33b5580fcd9772a0a7f95 | ||
| encode-roadmap.basset.clf.testfold-5 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-5.model.meta e5ff2b5579dd1ba1e7d1c0ea8a0c4be0 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-5.model.index 5c9451f8a316f6b9d44722b53d210010 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-5.model.data-00000-of-00001 79dde073c01580138d8b6cf50c1cae40 | ||
| encode-roadmap.basset.clf.testfold-6 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-6.model.meta cf060c2b1d4c9125ebec2accd74e298e models.kipoi_compatible/encode-roadmap.basset.clf.testfold-6.model.index fccf24f2e0846d5ea6f3d56f10d0cce2 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-6.model.data-00000-of-00001 e4bc8ce0c499759025499af7b06ec6ee | ||
| encode-roadmap.basset.clf.testfold-7 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-7.model.meta dd863fc91e1e46743efdd52315b84235 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-7.model.index ff03710e1c38f8561877fdc8df600c22 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-7.model.data-00000-of-00001 7b97299be0b9435360b24b3d526c5e60 | ||
| encode-roadmap.basset.clf.testfold-8 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-8.model.meta a7077d7359779958a43168aa8911a3af models.kipoi_compatible/encode-roadmap.basset.clf.testfold-8.model.index 28382fb71004441bfd891f8093272f9a models.kipoi_compatible/encode-roadmap.basset.clf.testfold-8.model.data-00000-of-00001 2e53513b09315728a17dda13997bc16d | ||
| encode-roadmap.basset.clf.testfold-9 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-9.model.meta 3e18c83fbb1cc29eabd5f8f17988d7c0 models.kipoi_compatible/encode-roadmap.basset.clf.testfold-9.model.index 20ddafde1077175ee9fba9fb04e8cacd models.kipoi_compatible/encode-roadmap.basset.clf.testfold-9.model.data-00000-of-00001 c87d589bbf7939c9731b67be8f414959 | ||
| ggr.basset.clf.pretrained.folds.testfold-0 models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-0.model.meta 66dcdd18cd9e8e4560c79bf60c5c9160 models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-0.model.index f7096b63b619eeb90f02ec28340d393b models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-0.model.data-00000-of-00001 af235f9a97e05d674cf9415d681396a0 | ||
| ggr.basset.clf.pretrained.folds.testfold-1 models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-1.model.meta 794fac73c754d5fd88bbcf26b3439c77 models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-1.model.index 49dbd1be34d3320eed34907120bbb5de models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-1.model.data-00000-of-00001 107c14caab90c3a53726d4f9bc9e5263 | ||
| ggr.basset.clf.pretrained.folds.testfold-2 models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-2.model.meta 6018ae7864a8cdd27f2fd3fbcd605b05 models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-2.model.index b97ea67092c63e8408246b8941f590d8 models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-2.model.data-00000-of-00001 e567de2dfe2200fe3beaeb09f78a7f3f | ||
| ggr.basset.clf.pretrained.folds.testfold-3 models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-3.model.meta 97267b947ea33270d7ddb92d5c8b657a models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-3.model.index 141afb11372af5c1995ecee9835c0aa0 models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-3.model.data-00000-of-00001 81bab1510b2ba0b1d5d003dadf1dd3e0 | ||
| ggr.basset.clf.pretrained.folds.testfold-4 models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-4.model.meta 9f39931ce83f26295f21f977e9fa0979 models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-4.model.index e7d3e3bdda1efc774955293ebb66a741 models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-4.model.data-00000-of-00001 12853a4eac1aff2e4c11717b6a597bb4 | ||
| ggr.basset.clf.pretrained.folds.testfold-5 models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-5.model.meta 74ba6c7b7a505ade74e5b3ed6bf55f9f models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-5.model.index b451245b241bb982da4d849eb34b4c4f models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-5.model.data-00000-of-00001 e00b4bfbede3ddd1353711f5781627a2 | ||
| ggr.basset.clf.pretrained.folds.testfold-6 models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-6.model.meta fd242cecdc33930243701f0389b2ba5e models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-6.model.index f05f29b0516d13570750e3115e3ec9de models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-6.model.data-00000-of-00001 1f8ad4b104f5cb8b745427c78cf8da75 | ||
| ggr.basset.clf.pretrained.folds.testfold-7 models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-7.model.meta f77284d300cc441bfc47d8758cd1613c models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-7.model.index 7777626f6ef77b939798b1e1054f1417 models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-7.model.data-00000-of-00001 7e09578aaaf13282b69e2b75eb8eacaf | ||
| ggr.basset.clf.pretrained.folds.testfold-8 models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-8.model.meta bea6295aaa0308e534b81b3604b4a9b7 models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-8.model.index 762199800bf1e069dcefc6dda8086d0a models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-8.model.data-00000-of-00001 6d79d9209b244f9e3128369c20469d33 | ||
| ggr.basset.clf.pretrained.folds.testfold-9 models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-9.model.meta 7a6552718b780b00dd9ab04877bccb3f models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-9.model.index 02c89e56a5a97ea38e76b05b07606edc models.kipoi_compatible/ggr.basset.clf.pretrained.folds.testfold-9.model.data-00000-of-00001 c86ae5ecb133c46cdcb1150d42691b87 | ||
| ggr.basset.regr.pretrained.folds.testfold-0 models.kipoi_compatible/ggr.basset.regr.pretrained.folds.testfold-0.model.meta 9185274583bd67ca1bf3f376749dea0a models.kipoi_compatible/ggr.basset.regr.pretrained.folds.testfold-0.model.index 3ddad77aef022cf8246063da16984be4 models.kipoi_compatible/ggr.basset.regr.pretrained.folds.testfold-0.model.data-00000-of-00001 dec73096e14c3f9ff424542a1ab11875 | ||
| ggr.basset.regr.pretrained.folds.testfold-1 models.kipoi_compatible/ggr.basset.regr.pretrained.folds.testfold-1.model.meta 9eff2aa7236d73e24f4b09dc7ee4da35 models.kipoi_compatible/ggr.basset.regr.pretrained.folds.testfold-1.model.index 9eee1096c7b06370fd83a47b8d6ad7f4 models.kipoi_compatible/ggr.basset.regr.pretrained.folds.testfold-1.model.data-00000-of-00001 83431ab9129f960fd5435cb8f73d34bd | ||
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| ggr.basset.regr.pretrained.folds.testfold-3 models.kipoi_compatible/ggr.basset.regr.pretrained.folds.testfold-3.model.meta 60a760c88e13aa0d0453e979c9a2b95e models.kipoi_compatible/ggr.basset.regr.pretrained.folds.testfold-3.model.index 960d7df63e2cdfaa336602ddc1d6dce2 models.kipoi_compatible/ggr.basset.regr.pretrained.folds.testfold-3.model.data-00000-of-00001 9c6d827a455b42d1620bb32254e20025 | ||
| ggr.basset.regr.pretrained.folds.testfold-4 models.kipoi_compatible/ggr.basset.regr.pretrained.folds.testfold-4.model.meta 05786276eb9044e0cc1b8645af24f7b9 models.kipoi_compatible/ggr.basset.regr.pretrained.folds.testfold-4.model.index e3e69db7809d45768819db3a3972ce16 models.kipoi_compatible/ggr.basset.regr.pretrained.folds.testfold-4.model.data-00000-of-00001 a48f6a1d6e47b7fa110a1c794ebd75dc | ||
| ggr.basset.regr.pretrained.folds.testfold-5 models.kipoi_compatible/ggr.basset.regr.pretrained.folds.testfold-5.model.meta aecbc5165666647f2ad9d5113e056156 models.kipoi_compatible/ggr.basset.regr.pretrained.folds.testfold-5.model.index dd56fde6d5dd0078c462c916119392dc models.kipoi_compatible/ggr.basset.regr.pretrained.folds.testfold-5.model.data-00000-of-00001 948789840faf196eff94ee0ecbfb3ad1 | ||
| ggr.basset.regr.pretrained.folds.testfold-6 models.kipoi_compatible/ggr.basset.regr.pretrained.folds.testfold-6.model.meta 7c8c3b9c7f0116c5016c1f8733540c27 models.kipoi_compatible/ggr.basset.regr.pretrained.folds.testfold-6.model.index 4d12f5815fb6b70c53becc57ceab44e7 models.kipoi_compatible/ggr.basset.regr.pretrained.folds.testfold-6.model.data-00000-of-00001 8a7617a187769f1d23011fb24dfdf1a8 | ||
| ggr.basset.regr.pretrained.folds.testfold-7 models.kipoi_compatible/ggr.basset.regr.pretrained.folds.testfold-7.model.meta 71ef1b06ca597efacaed20c56171495f models.kipoi_compatible/ggr.basset.regr.pretrained.folds.testfold-7.model.index ed884985af03ddc3ba3f55ae7112feca models.kipoi_compatible/ggr.basset.regr.pretrained.folds.testfold-7.model.data-00000-of-00001 1e07c75d137934c3f1b6259022b606a8 | ||
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