{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import scanpy as sc\n",
"import h5py\n",
"from mofapy2.run.entry_point import entry_point"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# MOFA 2"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load the datasets"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#todo\n",
"gdown.download(\n",
" 'https://drive.google.com/uc?id=1i5Yj7Hh6ZYn9MpJ5hikOqA-SvnYK4zvQ',\n",
" '10xpbmc10k2020-expressions.h5ad'\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"AnnData object with n_obs × n_vars = 10000 × 4000\n",
" obs: 'cell_type'\n",
" layers: 'count'"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"scrna = sc.read('../data/10xpbmc10k-2020/expressions.h5ad')\n",
"scrna"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#todo"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"AnnData object with n_obs × n_vars = 10000 × 40086\n",
" obs: 'cell_type'\n",
" layers: 'binary'"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"scatac = sc.read('../data/10xpbmc10k-2020/peaks.h5ad')\n",
"scatac"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Configure and train the model"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
" #########################################################\n",
" ### __ __ ____ ______ ### \n",
" ### | \\/ |/ __ \\| ____/\\ _ ### \n",
" ### | \\ / | | | | |__ / \\ _| |_ ### \n",
" ### | |\\/| | | | | __/ /\\ \\_ _| ###\n",
" ### | | | | |__| | | / ____ \\|_| ###\n",
" ### |_| |_|\\____/|_|/_/ \\_\\ ###\n",
" ### ### \n",
" ######################################################### \n",
" \n",
" \n",
" \n"
]
}
],
"source": [
"ent = entry_point()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"ent.set_data_options(\n",
" scale_groups = False, \n",
" scale_views = False\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Features names not provided, using default naming convention:\n",
"- feature1_view1, featureD_viewM\n",
"\n",
"Groups names not provided, using default naming convention:\n",
"- group1, group2, ..., groupG\n",
"\n",
"Samples names not provided, using default naming convention:\n",
"- sample1_group1, sample2_group1, sample1_group2, ..., sampleN_groupG\n",
"\n",
"Successfully loaded view='scRNA' group='group0' with N=10000 samples and D=4000 features...\n",
"Successfully loaded view='scATAC' group='group0' with N=10000 samples and D=40086 features...\n",
"\n",
"\n"
]
}
],
"source": [
"ent.set_data_matrix([[scrna.X.A], [scatac.X.A]], views_names=['scRNA', 'scATAC'])"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Model options:\n",
"- Automatic Relevance Determination prior on the factors: True\n",
"- Automatic Relevance Determination prior on the weights: True\n",
"- Spike-and-slab prior on the factors: False\n",
"- Spike-and-slab prior on the weights: True\n",
"Likelihoods:\n",
"- View 0 (scRNA): gaussian\n",
"- View 1 (scATAC): gaussian\n",
"\n",
"\n"
]
}
],
"source": [
"ent.set_model_options(\n",
" factors = 20, \n",
" spikeslab_weights = True, \n",
" ard_factors = True,\n",
" ard_weights = True\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"ent.set_train_options(\n",
" iter = 1000, \n",
" convergence_mode = \"fast\", \n",
" startELBO = 1, \n",
" freqELBO = 1, \n",
" dropR2 = 0.001, \n",
" gpu_mode = False, \n",
" verbose = False, \n",
" seed = 1\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"ent.build()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"######################################\n",
"## Training the model with seed 1 ##\n",
"######################################\n",
"\n",
"\n",
"ELBO before training: -533850218.28 \n",
"\n",
"Iteration 1: time=672.13, ELBO=-49477990.65, deltaELBO=484372227.623 (90.73185906%), Factors=19\n",
"Iteration 2: time=644.57, ELBO=-44371611.02, deltaELBO=5106379.638 (0.95651916%), Factors=18\n",
"Iteration 3: time=610.36, ELBO=-43409403.10, deltaELBO=962207.917 (0.18023930%), Factors=17\n",
"Iteration 4: time=576.94, ELBO=-43123431.40, deltaELBO=285971.703 (0.05356778%), Factors=16\n",
"Iteration 5: time=546.21, ELBO=-42911821.08, deltaELBO=211610.312 (0.03963852%), Factors=15\n",
"Iteration 6: time=514.08, ELBO=-42748260.83, deltaELBO=163560.253 (0.03063785%), Factors=14\n",
"Iteration 7: time=479.70, ELBO=-42631894.62, deltaELBO=116366.212 (0.02179754%), Factors=13\n",
"Iteration 8: time=469.61, ELBO=-42583589.56, deltaELBO=48305.058 (0.00904843%), Factors=13\n",
"Iteration 9: time=469.84, ELBO=-42547079.32, deltaELBO=36510.238 (0.00683904%), Factors=13\n",
"Iteration 10: time=470.84, ELBO=-42514182.09, deltaELBO=32897.227 (0.00616226%), Factors=13\n",
"Iteration 11: time=470.62, ELBO=-42482198.92, deltaELBO=31983.172 (0.00599104%), Factors=13\n",
"Iteration 12: time=466.74, ELBO=-42451101.84, deltaELBO=31097.087 (0.00582506%), Factors=13\n",
"Iteration 13: time=470.71, ELBO=-42421842.04, deltaELBO=29259.792 (0.00548090%), Factors=13\n",
"Iteration 14: time=472.95, ELBO=-42394987.13, deltaELBO=26854.918 (0.00503042%), Factors=13\n",
"Iteration 15: time=468.00, ELBO=-42369993.36, deltaELBO=24993.767 (0.00468179%), Factors=13\n",
"Iteration 16: time=470.95, ELBO=-42346230.99, deltaELBO=23762.368 (0.00445113%), Factors=13\n",
"Iteration 17: time=469.98, ELBO=-42323568.87, deltaELBO=22662.117 (0.00424503%), Factors=13\n",
"Iteration 18: time=471.78, ELBO=-42302199.66, deltaELBO=21369.211 (0.00400285%), Factors=13\n",
"Iteration 19: time=470.26, ELBO=-42282662.37, deltaELBO=19537.296 (0.00365970%), Factors=13\n",
"Iteration 20: time=470.19, ELBO=-42265767.13, deltaELBO=16895.236 (0.00316479%), Factors=13\n",
"Iteration 21: time=470.39, ELBO=-42251645.48, deltaELBO=14121.649 (0.00264525%), Factors=13\n",
"Iteration 22: time=471.96, ELBO=-42239535.55, deltaELBO=12109.932 (0.00226841%), Factors=13\n",
"Iteration 23: time=469.52, ELBO=-42228483.17, deltaELBO=11052.378 (0.00207031%), Factors=13\n",
"Iteration 24: time=471.13, ELBO=-42217788.28, deltaELBO=10694.891 (0.00200335%), Factors=13\n",
"Iteration 25: time=471.05, ELBO=-42207058.05, deltaELBO=10730.230 (0.00200997%), Factors=13\n",
"Iteration 26: time=468.39, ELBO=-42196062.46, deltaELBO=10995.588 (0.00205968%), Factors=13\n",
"Iteration 27: time=471.01, ELBO=-42184652.00, deltaELBO=11410.466 (0.00213739%), Factors=13\n",
"Iteration 28: time=470.86, ELBO=-42172785.10, deltaELBO=11866.900 (0.00222289%), Factors=13\n",
"Iteration 29: time=469.71, ELBO=-42160528.25, deltaELBO=12256.845 (0.00229593%), Factors=13\n",
"Iteration 30: time=469.13, ELBO=-42148063.61, deltaELBO=12464.645 (0.00233486%), Factors=13\n",
"Iteration 31: time=472.42, ELBO=-42135683.79, deltaELBO=12379.819 (0.00231897%), Factors=13\n",
"Iteration 32: time=472.55, ELBO=-42123697.78, deltaELBO=11986.011 (0.00224520%), Factors=13\n",
"Iteration 33: time=470.89, ELBO=-42112159.98, deltaELBO=11537.797 (0.00216124%), Factors=13\n",
"Iteration 34: time=471.35, ELBO=-42100865.70, deltaELBO=11294.285 (0.00211563%), Factors=13\n",
"Iteration 35: time=471.50, ELBO=-42089578.39, deltaELBO=11287.303 (0.00211432%), Factors=13\n",
"Iteration 36: time=472.12, ELBO=-42078206.48, deltaELBO=11371.912 (0.00213017%), Factors=13\n",
"Iteration 37: time=470.37, ELBO=-42066829.48, deltaELBO=11377.003 (0.00213112%), Factors=13\n",
"Iteration 38: time=469.49, ELBO=-42055590.44, deltaELBO=11239.036 (0.00210528%), Factors=13\n",
"Iteration 39: time=471.74, ELBO=-42044576.40, deltaELBO=11014.049 (0.00206313%), Factors=13\n",
"Iteration 40: time=468.36, ELBO=-42033796.26, deltaELBO=10780.139 (0.00201932%), Factors=13\n",
"Iteration 41: time=471.74, ELBO=-42023245.12, deltaELBO=10551.139 (0.00197642%), Factors=13\n",
"Iteration 42: time=469.84, ELBO=-42012980.58, deltaELBO=10264.537 (0.00192274%), Factors=13\n",
"Iteration 43: time=473.01, ELBO=-42003173.84, deltaELBO=9806.737 (0.00183698%), Factors=13\n",
"Iteration 44: time=472.89, ELBO=-41994123.85, deltaELBO=9049.997 (0.00169523%), Factors=13\n",
"Iteration 45: time=471.10, ELBO=-41986206.96, deltaELBO=7916.884 (0.00148298%), Factors=13\n",
"Iteration 46: time=471.62, ELBO=-41979734.65, deltaELBO=6472.317 (0.00121238%), Factors=13\n",
"Iteration 47: time=470.59, ELBO=-41974790.89, deltaELBO=4943.760 (0.00092606%), Factors=13\n",
"Iteration 48: time=469.32, ELBO=-41971196.35, deltaELBO=3594.538 (0.00067332%), Factors=13\n",
"\n",
"Converged!\n",
"\n",
"\n",
"\n",
"#######################\n",
"## Training finished ##\n",
"#######################\n",
"\n",
"\n"
]
}
],
"source": [
"ent.run()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Saving model in 10xpbmc10k-mofa2.hdf5...\n"
]
}
],
"source": [
"outfile = '10xpbmc10k-mofa2.hdf5'\n",
"ent.save(outfile)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Save results as AnnData"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"f = h5py.File(outfile)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"AnnData object with n_obs × n_vars = 10000 × 13\n",
" obs: 'cell_type'"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"z = np.concatenate([v[:,:] for k, v in f['expectations']['Z'].items()], axis=1).T\n",
"z = sc.AnnData(z)\n",
"\n",
"z.obs_names = scrna.obs_names\n",
"z.obs = scrna.obs\n",
"\n",
"z"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"z.write('../data/integrated/mofa/10xpbmc10k-mofa.h5ad')"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"rm: cannot remove '10xpbmc10k2020-expressions.h5ad': No such file or directory\n",
"rm: cannot remove '10xpbmc10k2020-peaks.h5ad': No such file or directory\n"
]
}
],
"source": [
"!rm '10xpbmc10k2020-expressions.h5ad'\n",
"!rm '10xpbmc10k2020-peaks.h5ad'\n",
"!rm '10xpbmc10k-mofa2.hdf5'"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Visualize results"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"sc.pp.neighbors(z)\n",
"sc.tl.umap(z)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sc.pl.umap(z, color='cell_type')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.9"
}
},
"nbformat": 4,
"nbformat_minor": 4
}