update documentation

martinjzhang · Mar 2, 2022 · 6511361 · 6511361
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Showing 4 changed files with 6 additions and 5 deletions.
diff --git a/bin/scdrs b/bin/scdrs
@@ -64,7 +64,7 @@ def compute_score(
     adj_prop : str, optional
         Cell group annotation (e.g., cell type) in `adata.obs.columns` used for adjusting 
         for cell group proportions. Cells are inversely weighted by the corresponding 
-        group size.Default is None.
+        group size. Default is None.
     flag_filter_data : bool, optional
         If to apply minimal cell and gene filtering to h5ad_file. Default is True.
     flag_raw_count : bool, optional

diff --git a/docs/index.rst b/docs/index.rst
@@ -100,7 +100,6 @@ Examples
    file_format
    versions
    notebooks/quickstart.ipynb
-   examples
    downloads
 
 
diff --git a/docs/reference_cli.rst b/docs/reference_cli.rst
@@ -109,6 +109,10 @@ out_folder : str
     :code:`<trait>` is from :code:`gs_file` file.
 cov_file : str, optional
     scDRS covariate :code:`.cov` file. Default is :code:`None`.
+adj_prop : str, optional
+    Cell group annotation (e.g., cell type) in :code:`adata.obs.columns` used for adjusting 
+    for cell group proportions. Cells are inversely weighted by the corresponding 
+    group size. Default is :code:`None`.
 flag_filter_data : bool, optional
     If to apply minimal cell and gene filtering to :code:`h5ad_file`. Default is :code:`True`.
 flag_raw_count : bool, optional

diff --git a/scdrs/method.py b/scdrs/method.py
@@ -799,7 +799,7 @@ def downstream_group_analysis(
             mc_z = (score_q95 - v_ctrl_score_q95.mean()) / v_ctrl_score_q95.std()
             df_res.loc[group, ["assoc_mcp", "assoc_mcz"]] = [mc_p, mc_z]
 
-        # Heterogeneity @Kangcheng: could you review
+        # Heterogeneity
         df_rls = test_gearysc(
             adata[cell_list], df_reg.loc[cell_list, :], groupby=group_col
         )
@@ -904,7 +904,6 @@ def downstream_gene_analysis(
 ##############################################################################
 ##################### Subroutines for downstream analysis ####################
 ##############################################################################
-# @Kangcheng: could you review
 def test_gearysc(
     adata: anndata.AnnData,
     df_full_score: pd.DataFrame,
@@ -1028,7 +1027,6 @@ def distribution_match(v, ref):
     return df_rls
 
 
-# @Kangcheng: could you review
 def gearys_c(adata, vals):
     """
     Compute Geary's C statistics for an AnnData.