Basic Polis Pipeline

%pip install --quiet git+https://github.com/patcon/valency-anndata@main

Usage¶

Loading Polis Data¶

import valency_anndata as val

adata = val.datasets.polis.load("https://pol.is/report/r29kkytnipymd3exbynkd")
val.viz.schematic_diagram(adata, diff_from=None)

Data was gathered using the Polis software (see: https://compdemocracy.org/polis
and https://github.com/compdemocracy/polis) and is sub-licensed under CC BY 4.0
with Attribution to The Computational Democracy Project.
The data and more information about how the data was collected can be found at
the following link: https://pol.is/report/r29kkytnipymd3exbynkd

svg

Running Polis Pipelines¶

with val.viz.schematic_diagram(diff_from=adata):
    val.tools.recipe_polis(adata, key_added_pca="X_pca_polis")

/home/runner/work/valency-anndata/valency-anndata/.venv/lib/python3.10/site-packages/scanpy/preprocessing/_pca/__init__.py:226: FutureWarning: Argument `use_highly_variable` is deprecated, consider using the mask argument. Use_highly_variable=True can be called through mask_var="highly_variable". Use_highly_variable=False can be called through mask_var=None
  mask_var_param, mask_var = _handle_mask_var(

svg

val.viz.embedding(adata, basis="pca_polis", color="kmeans_polis")

adata.obs["kmeans_polis"].value_counts()

png

kmeans_polis
0    1627
1     116
Name: count, dtype: int64

Exploring Polis Pipelines¶

with val.viz.schematic_diagram(diff_from=adata):
    val.preprocessing.calculate_qc_metrics(adata, inplace=True)

svg

val.viz.embedding(adata, basis="pca_polis",
    color=["kmeans_polis", "pct_seen", "pct_agree", "pct_pass"],
)

png

Running & Exploring Alternative Pipelines¶

with val.viz.schematic_diagram(diff_from=adata):
    val.tools.pacmap(
        adata,
        key_added="X_pacmap",
        layer="X_masked_imputed_mean",
    )
    val.tools.kmeans(
        adata,
        k_bounds=(2, 9),
        init="polis",
        use_rep="X_pacmap",
        mask_obs="cluster_mask",
        key_added="kmeans_pacmap",
    )

svg

val.viz.embedding(adata, basis="pacmap",
    color=["kmeans_pacmap", "pct_seen", "pct_agree", "pct_pass"],
)

png