manifests/1a/github.com__sandialabs__iterml-for-vocs.json

{
 "format": "oscr-script-manifest/1",
 "repository": "github.com/sandialabs/iterml-for-vocs",
 "url": "https://github.com/sandialabs/IterML-for-VOCs",
 "host": "github.com",
 "commit": "6f8819e3bd61e5270bd34f55716e78eca6de11e7",
 "license": "BSD-3-Clause",
 "license_confirmed_by": "license file LICENSE.md",
 "redistribution": "yes",
 "files": [
  {
   "path": "LICENSE.md",
   "sha256": "e005f5d84e083e0bd482fadd09c49524a358d11d6333b3d72bb071cce6ac0a35",
   "language": "License",
   "lines": 14,
   "truncated": false,
   "block": 6,
   "row": 2013
  },
  {
   "path": "R/binding_interactions.R",
   "sha256": "907a26075b4f1ef91b6fdc257f54138402769fe979bcbd2c35bb71e0d7f6f192",
   "language": "R",
   "lines": 224,
   "truncated": false,
   "block": 8,
   "row": 3877
  },
  {
   "path": "R/combined_features.R",
   "sha256": "69a74b6940dfc16e6ed3df0324773303d48bc205df1a0564ac90a4e9f3446dcd",
   "language": "R",
   "lines": 470,
   "truncated": false,
   "block": 8,
   "row": 4705
  },
  {
   "path": "R/combined_ml.R",
   "sha256": "4414663a1e155b10c1d54453446c9830883247cb5fff72ab638ba43c23190ec4",
   "language": "R",
   "lines": 352,
   "truncated": false,
   "block": 8,
   "row": 4534
  },
  {
   "path": "R/combined_plot.R",
   "sha256": "206579e98d7625ce6475cea4f37bce7426e585e521fbd8dba8933f71c9c57868",
   "language": "R",
   "lines": 153,
   "truncated": false,
   "block": 8,
   "row": 3642
  },
  {
   "path": "R/combined_preprocess.R",
   "sha256": "89fe4aae0b47b21241b54bfd0f44d292325e0344876f095f352e680cfdfe20ba",
   "language": "R",
   "lines": 177,
   "truncated": false,
   "block": 8,
   "row": 3712
  },
  {
   "path": "R/conc_resp.R",
   "sha256": "5dd8ef83f491eb684bd151a75fb0f6ae28fa37749d349d83eeeebf55c85468a2",
   "language": "R",
   "lines": 482,
   "truncated": false,
   "block": 8,
   "row": 4477
  },
  {
   "path": "R/mai_antib_bind.R",
   "sha256": "07dc3f46fd95a38ea814b5a64e13a79a095a9b861766e5cf96bcecf5c8bea5c0",
   "language": "R",
   "lines": 429,
   "truncated": false,
   "block": 8,
   "row": 4735
  },
  {
   "path": "R/mai_antib_model.R",
   "sha256": "691f54e7017b9e2e0270c2d925e4c6f346ce1bbfb909ff890a4b5518134b3730",
   "language": "R",
   "lines": 668,
   "truncated": false,
   "block": 8,
   "row": 4963
  },
  {
   "path": "R/mai_antib_model_REVISION.R",
   "sha256": "22535b6d56c4edf21451d955c7531964a0e3f8aecb453c7186ddc4556f812e43",
   "language": "R",
   "lines": 284,
   "truncated": false,
   "block": 8,
   "row": 4256
  },
  {
   "path": "R/mai_seq_align.R",
   "sha256": "550e868763eb98bf92cdf3812f925c94f568b30d7e6d2c1d8a78b30e340a39bf",
   "language": "R",
   "lines": 17,
   "truncated": false,
   "block": 8,
   "row": 1485
  },
  {
   "path": "R/ml_features.R",
   "sha256": "3807634cc69eeaafa4f06c7af4136c2cabab1f26e681f85f3e1cff20cb030387",
   "language": "R",
   "lines": 206,
   "truncated": false,
   "block": 8,
   "row": 3832
  },
  {
   "path": "R/ml_modeler.R",
   "sha256": "9c3ffed518ba755a02d5593f92e3ba3aadfec5fd167b88f8966c1c1a668d1c2f",
   "language": "R",
   "lines": 228,
   "truncated": false,
   "block": 8,
   "row": 3913
  },
  {
   "path": "R/ml_plot.R",
   "sha256": "d183e90a5bb3440180a98370010e6f5a79ee03fea946b818b22e662228c1c4eb",
   "language": "R",
   "lines": 132,
   "truncated": false,
   "block": 8,
   "row": 3460
  },
  {
   "path": "R/ml_predict.R",
   "sha256": "7ce68eae3c499b1e36b32fc250c65d2ff1ebae8ebb48f2e4101db24239fdf1f1",
   "language": "R",
   "lines": 509,
   "truncated": false,
   "block": 8,
   "row": 4762
  },
  {
   "path": "R/ml_preprocess.R",
   "sha256": "33a2dd1f4d8db7bcb95b6bc7902a92c74be468342d7eb6a9ce6a8e5c24e0e327",
   "language": "R",
   "lines": 119,
   "truncated": false,
   "block": 8,
   "row": 3187
  },
  {
   "path": "R/ml_tuner.R",
   "sha256": "0a4527a420bd98ee6e95e8dd3e1c9bbbf53946b6221507ac4abf28fb98c0a55b",
   "language": "R",
   "lines": 145,
   "truncated": false,
   "block": 8,
   "row": 3540
  },
  {
   "path": "R/score_funs.R",
   "sha256": "64ec39a107f6b4e7813cb31772ec570ad1f94fb9c8576d850369ebc5694226d1",
   "language": "R",
   "lines": 21,
   "truncated": false,
   "block": 8,
   "row": 1398
  },
  {
   "path": "R/site_chooser.R",
   "sha256": "0a6e80f12fe08a9a9514fc01748d4beb724881ba1205fc038a500a2aaa868b97",
   "language": "R",
   "lines": 681,
   "truncated": false,
   "block": 8,
   "row": 5000
  },
  {
   "path": "R/starr_ml.R",
   "sha256": "a78e4011d3fc5de30f14a2473f7fcc4583ad5a50072754f01d940a1776d14bb1",
   "language": "R",
   "lines": 269,
   "truncated": false,
   "block": 8,
   "row": 4139
  },
  {
   "path": "R/var_muts.R",
   "sha256": "85e7e7ca8e3e3c8736467fb4219815dda230da3dbafb901bd7e545f0cdada678",
   "language": "R",
   "lines": 20,
   "truncated": false,
   "block": 8,
   "row": 1452
  },
  {
   "path": "README.md",
   "sha256": "809e55c2f21b1e1c53a026aba03028c5bb5efc89740894eb6beaf07edeac18d7",
   "language": "Text",
   "lines": 248,
   "truncated": false,
   "block": 8,
   "row": 10580
  },
  {
   "path": "python/epistasis_modeler.py",
   "sha256": "3d4fe2b22e6482dff9394e6348819d96f1c43fb89268a60bf375c0a087df273e",
   "language": "Python",
   "lines": 62,
   "truncated": false,
   "block": 6,
   "row": 32956
  }
 ]
}