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cannin/X.csv

Last active October 6, 2022 15:04
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anndata_example.py
import numpy as np
import pandas as pd
import anndata as ad
# Generate example data and build AnnData object
vals = np.random.rand(5, 10).astype('f')
adata = ad.AnnData(vals)
adata
adata.X
adata.obs_names = [f"cell_{i:d}" for i in range(adata.n_obs)]
adata.var_names = [f"gene_symbol_{i:d}" for i in range(adata.n_vars)]
print(adata.obs_names[:3])
tmp = np.random.choice(["cell1", "cell2", "cell3"], size=(adata.n_obs,))
adata.obs["cell_type1_id"] = tmp
adata.obs
tmp = np.random.choice(["cell_type1", "cell_type2", "cell_type3"], size=(adata.n_obs,))
adata.obs["cell_type2_id"] = tmp
adata.obs
tmp = np.random.choice(["G1", "G2", "G3"], size=(adata.n_vars,))
adata.var["gene_type1_id"] = tmp
adata.var
tmp = np.random.choice(["gene_type1", "gene_type2", "gene_type3"], size=(adata.n_vars,))
adata.var["gene_type2_id"] = tmp
adata.var
bdata = adata[adata.obs.cell_type1_id == "cell1"]
bdata
# Write tables
adata.write_csvs("output", skip_data=False)
# Write h5ad format
adata.write(filename="anndata.h5ad")
# Read data
cdata = ad.read_h5ad(filename="anndata.h5ad")
cdata
Raw
obs.csv
cell_type1_id cell_type2_id
cell_0 cell1 cell_type3
cell_1 cell3 cell_type1
cell_2 cell3 cell_type2
cell_3 cell1 cell_type3
cell_4 cell3 cell_type1
Raw
var.csv
gene_type1_id gene_type2_id
gene_symbol_0 G1 gene_type2
gene_symbol_1 G1 gene_type3
gene_symbol_2 G1 gene_type1
gene_symbol_3 G1 gene_type2
gene_symbol_4 G2 gene_type3
gene_symbol_5 G2 gene_type2
gene_symbol_6 G1 gene_type2
gene_symbol_7 G2 gene_type2
gene_symbol_8 G3 gene_type3
gene_symbol_9 G2 gene_type2
Raw
X.csv
0.19100112 0.46828908 0.8881515 0.3272082 0.44101298 0.13238761 0.06625041 0.42884535 0.45125055 0.54849786
0.73450327 0.968179 0.44648758 0.10997138 0.2849175 0.5890882 0.053468592 0.7258484 0.8558861 0.28162476
0.34389842 0.6496306 0.70850253 0.5590548 0.93613046 0.18099453 0.2924698 0.13112783 0.25727338 0.29037902
0.67264825 0.36550987 0.7641897 0.5965308 0.30332556 0.7546757 0.88458216 0.6731449 0.1464198 0.2685193
0.59329206 0.8943774 0.061935168 0.20078066 0.16109781 0.0445861 0.456919 0.34288594 0.4962387 0.3457089
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