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Python library for plotting Cellphonedb results. Ported from ktplots R package.

Home Page: https://ktplotspy.readthedocs.io/

License: MIT License

Python 100.00%

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forget999 drsei tu-feng hvanphucs bioturing-datalake nine-sarayut maysam-motevasseli yxwucq han-tun

ktplotspy's Issues

potential issue with L-R with all non-significant hits appearing in plot_cpdb

Need to check whether there's something wrong during slicing?

ValueError on plot_cpdb_heatmap with degs_analysis=True

I am trying to run the plot_cpdb_heatmap function on the output of CellPhoneDB method 3. I used the relevant_interactions.txt for the pvals argument as recommended in the R documentation.
Here is the command I used:

kpy.plot_cpdb_heatmap(adata, pvals=pvals, celltype_key = "celltype", degs_analysis=True)

It created this error:

ValueError                                Traceback (most recent call last)
Cell In[8], line 1
----> 1 kpy.plot_cpdb_heatmap(adata, pvals=pvals, celltype_key = "celltype", degs_analysis=True, figsize=(5, 5), title="Sum of significant interactions")

File ~/anaconda3/lib/python3.10/site-packages/ktplotspy/plot/plot_cpdb_heatmap.py:96, in plot_cpdb_heatmap(adata, pvals, celltype_key, degs_analysis, log1p_transform, alpha, linewidths, row_cluster, col_cluster, low_col, mid_col, high_col, cmap, title, return_tables, symmetrical, **kwargs)
     94 count_mat[pd.isnull(count_mat)] = 0
     95 if symmetrical:
---> 96     count_matx = np.triu(count_mat) + np.tril(count_mat.T) + np.tril(count_mat) + np.triu(count_mat.T)
     97     count_matx[np.diag_indices_from(count_matx)] = np.diag(count_mat)
     98     count_matx = pd.DataFrame(count_matx)

ValueError: operands could not be broadcast together with shapes (11,12) (12,11)

I had no problem using Method 2 output without the degs_analysis argument.

How to save figures?

Hi,
How to save figures? I used "plt.savefig()", but it did not work.

plot_cpdb_heatmap exclude same celltype-celltype

potential option to toggle this to help the visualisation? since people are mostly interested in what cell types are talking to other cell types

Add parameters for kpy.plot_cpdb_heatmap

Hi, thanks for your great tool!

I kindly request you to add the parameter 'separator' to your plot functions. Previously, when running cpdb analysis, one may have used a custom separator to separate interacted cell pairs with the 'separator' parameter. The current plot functions do not seem compatible with this feature as they defaultly use '|' as the separator, resulting in errors.

Thanks again!

kpy.plot_cpdb

IndexError: only integers, slices (:), ellipsis (...), numpy.newaxis (None) and i arrays are valid indices

when use the function kpy.plot_cpdb, what does it means?

plot_cpdb KeyError

Hello, thanks for this package to explore cpdb output.

I am facing the following issue with plot_cpdb function:

import ktplotspy as kpy

pp = kpy.plot_cpdb(
        adata = adata,
        cell_type1 = '.',
        cell_type2 = '.', 
        means = means,
        pvals = relevant_interactions,
        celltype_key = "celltype",
        figsize = (7,10),
        max_size = 6,
        highlight_size = 0.75,
        degs_analysis = True,
        standard_scale = True,
    )
pp

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
Input In [42], in <module>
      1 import ktplotspy as kpy
----> 3 pp = kpy.plot_cpdb(
      4         adata = adata,
      5         cell_type1 = '.',
      6         cell_type2 = '.', 
      7         means = means,
      8         pvals = relevant_interactions,
      9         celltype_key = "celltype",
     10         figsize = (7,10),
     11         max_size = 6,
     12         highlight_size = 0.75,
     13         degs_analysis = True,
     14         standard_scale = True,
     15     )
     16 pp

File ~/my-conda-envs/sc_Harm/lib/python3.10/site-packages/ktplotspy/plot/plot_cpdb.py:218, in plot_cpdb(adata, cell_type1, cell_type2, means, pvals, celltype_key, degs_analysis, splitby_key, alpha, keep_significant_only, genes, gene_family, custom_gene_family, standard_scale, cluster_rows, cmap_name, max_size, max_highlight_size, default_style, highlight_col, highlight_size, special_character_regex_pattern, exclude_interactions, title, return_table, figsize)
    216 # filter
    217 means_matx = filter_interaction_and_celltype(data=means_mat, genes=query, celltype_pairs=ct_columns)
--> 218 pvals_matx = filter_interaction_and_celltype(data=pvals_mat, genes=query, celltype_pairs=ct_columns)
    219 # reorder the columns
    220 col_order = []

File ~/my-conda-envs/sc_Harm/lib/python3.10/site-packages/ktplotspy/utils/support.py:92, in filter_interaction_and_celltype(data, genes, celltype_pairs)
     75 def filter_interaction_and_celltype(data: pd.DataFrame, genes: List, celltype_pairs: List) -> pd.DataFrame:
     76     """Filter data to interactions and celltypes.
     77 
     78     Parameters
   (...)
     90         Filtered dataframe.
     91     """
---> 92     filtered_data = data[data.interacting_pair.isin(genes)][celltype_pairs]
     93     return filtered_data

File ~/my-conda-envs/sc_Harm/lib/python3.10/site-packages/pandas/core/frame.py:3811, in DataFrame.__getitem__(self, key)
   3809     if is_iterator(key):
   3810         key = list(key)
-> 3811     indexer = self.columns._get_indexer_strict(key, "columns")[1]
   3813 # take() does not accept boolean indexers
   3814 if getattr(indexer, "dtype", None) == bool:

File ~/my-conda-envs/sc_Harm/lib/python3.10/site-packages/pandas/core/indexes/base.py:6113, in Index._get_indexer_strict(self, key, axis_name)
   6110 else:
   6111     keyarr, indexer, new_indexer = self._reindex_non_unique(keyarr)
-> 6113 self._raise_if_missing(keyarr, indexer, axis_name)
   6115 keyarr = self.take(indexer)
   6116 if isinstance(key, Index):
   6117     # GH 42790 - Preserve name from an Index

File ~/my-conda-envs/sc_Harm/lib/python3.10/site-packages/pandas/core/indexes/base.py:6176, in Index._raise_if_missing(self, key, indexer, axis_name)
   6173     raise KeyError(f"None of [{key}] are in the [{axis_name}]")
   6175 not_found = list(ensure_index(key)[missing_mask.nonzero()[0]].unique())
-> 6176 raise KeyError(f"{not_found} not in index")

KeyError: "['thy_TH_processing>@<thy_TH_processing', 'thy_TH_processing>@<mes_CYGB', 'thy_TH_processing>@<thy_Lumen-forming', 'thy_TH_processing>@<end_Arterial', 'thy_TH_processing>@<mes_IGF1R', 'thy_TH_processing>@<mes_SCN7A', 'thy_TH_processing>@<mes_CCL19', 'end_Capillary>@<thy_TH_processing', 'end_Capillary>@<thy_Lumen-forming', 'end_Capillary>@<mes_IGF1R', 'end_Capillary>@<mes_SCN7A', 'thy_Lumen-forming>@<thy_TH_processing', 'thy_Lumen-forming>@<mes_CYGB', 'thy_Lumen-forming>@<thy_Lumen-forming', 'thy_Lumen-forming>@<end_Arterial', 'thy_Lumen-forming>@<mes_IGF1R', 'thy_Lumen-forming>@<mes_SCN7A', 'thy_Lumen-forming>@<mes_CCL19', 'end_Arterial>@<thy_TH_processing', 'end_Arterial>@<thy_Lumen-forming', 'end_Arterial>@<end_Arterial', 'end_Arterial>@<mes_IGF1R', 'end_Arterial>@<mes_CCL19', 'mes_IGF1R>@<thy_TH_processing', 'mes_IGF1R>@<thy_Lumen-forming', 'mes_IGF1R>@<end_Arterial', 'mes_IGF1R>@<mes_IGF1R', 'mes_IGF1R>@<mes_SCN7A', 'mes_IGF1R>@<mes_CCL19', 'mes_SCN7A>@<mes_SCN7A', 'mes_CCL19>@<thy_TH_processing', 'mes_CCL19>@<thy_Lumen-forming', 'mes_CCL19>@<end_Arterial', 'mes_CCL19>@<mes_IGF1R', 'mes_CCL19>@<mes_SCN7A', 'mes_CCL19>@<mes_CCL19', 'end_Cycling>@<end_Cycling', 'end_Cycling>@<mes_Cycling', 'end_Cycling>@<thy_Cycling', 'mes_Cycling>@<end_Cycling', 'mes_Cycling>@<mes_Cycling', 'mes_Cycling>@<thy_Cycling', 'thy_Cycling>@<end_Cycling', 'thy_Cycling>@<mes_Cycling', 'thy_Cycling>@<thy_Cycling'] not in index"

any hint what I did wrong ? thanks

Bug Report：Missing rows in plot_cpdb_heatmap()

Hello, I'm using plot_cpdb_heatmap() function to visualize my result from CPDB, and found a cell type row(B cell) is missing in the 9x10 heatmap.
It turns out that B cell in my pvals result have no significant interaction as cpdb target. And I expect a row with 0 interaction rather than just drop it.

    metadata = adata.obs.copy()
    all_intr = pvals.copy()
    labels = metadata[celltype_key]
    intr_pairs = all_intr.interacting_pair
    all_int = all_intr.iloc[:, 12 : all_intr.shape[1]].T
    all_int.columns = intr_pairs
    all_count = all_int.melt(ignore_index=False).reset_index()
    if degs_analysis:
        all_count = all_count[all_count.value == 1]
    else:
        all_count = all_count[all_count.value < alpha]
    count1x = all_count[["index", "interacting_pair"]].groupby("index").agg({"interacting_pair": "count"})
    tmp = pd.DataFrame([x.split("|") for x in count1x.index])

Here is the code, seems it gets "tmp" by the filtered "all_counts", and cell without significant interaction were dropped in the filtered "all_counts".
Thanks for your time!

The function of ktplotspy.plot.plot_cpdb_chord

Hi，
In terms of plotting results of cellphonedb, this is an outstanding job.
However, while using ktplotspy, I am trying to reproduce the effect of plot_cpdb2 in ktplots. Can the ktplotspy.plot.plot_cpdb_chord function in Python achieve such results(Interactions between genes that mark different cells)?

Best，
xhxie

Plot using mtx format (not .h5ad)

Hi,

I'm new to cellphonedb and just run it on a Seurat object in mtx format (as described here):
https://github.com/ventolab/CellphoneDB/blob/master/notebooks/DEGs_calculation/0_prepare_your_data_from_Seurat.ipynb
not in a .h5ad format. If I don't have a .h5ad, how can I define the adata parameter to plot using ktplotspy?

Thank you in advance,

implementation of plot_cpdb3/4 using pyCirclize?

https://moshi4.github.io/pyCirclize/chord_diagram/

Default min p-value can't be scaled according to statistical test

Hi! please refer to this issue: ventolab/CellphoneDB#179
Could you add a parameter result_precision according to cpdb_statistical_analysis_method.call, which is default 3 but can be set to 5 when increasing test number to 1e5? like this:

def plot_cpdb(
    ...
    result_precision: int = 3):
    ...
        if df.at[i, "pvals"] == 0:
            df.at[i, "pvals"] = 1**-result_precision

I'm not sure that if there are other places that need to be changed, Thank you for checking this!

AttributeError: QuadMesh.set() got an unexpected keyword argument 'adata'

Hi, thank you for developing such a great package.
I meet some problems in plotting my data with ktplotspy.
The "adata" file is the one analyzed by cellphnedb. However, it donot work with ktplotspy.
I run the plot like this:

kpy.plot_cpdb_heatmap(
        adata = adata,
        pvals = pvals,
        celltype_key = "cluster_2",
        figsize = (5,5),
        title = "Number of significant interactions",
        symmetrical = False,
    )

It created this error:

AttributeError                            Traceback (most recent call last)
Cell In[19], line 1
----> 1 kpy.plot_cpdb_heatmap(
      2         adata = adata,
      3         pvals = pvals,
      4         celltype_key = "cluster_2",
      5         figsize = (5,5),
      6         title = "Number of significant interactions",
      7         symmetrical = False,
      8     )

File ~/miniconda3/envs/cpdb/lib/python3.8/site-packages/ktplotspy/plot/plot_cpdb_heatmap.py:108, in plot_cpdb_heatmap(pvals, degs_analysis, log1p_transform, alpha, linewidths, row_cluster, col_cluster, low_col, mid_col, high_col, cmap, title, return_tables, symmetrical, **kwargs)
    106     colmap = cmap
    107 if not return_tables:
--> 108     g = sns.clustermap(
    109         count_mat,
    110         row_cluster=row_cluster,
    111         col_cluster=col_cluster,
    112         linewidths=linewidths,
    113         tree_kws={"linewidths": 0},
    114         cmap=colmap,
    115         **kwargs
    116     )
    117     if title != "":
    118         g.fig.suptitle(title)

File ~/miniconda3/envs/cpdb/lib/python3.8/site-packages/seaborn/matrix.py:1258, in clustermap(data, pivot_kws, method, metric, z_score, standard_scale, figsize, cbar_kws, row_cluster, col_cluster, row_linkage, col_linkage, row_colors, col_colors, mask, dendrogram_ratio, colors_ratio, cbar_pos, tree_kws, **kwargs)
   1250     raise RuntimeError("clustermap requires scipy to be available")
   1252 plotter = ClusterGrid(data, pivot_kws=pivot_kws, figsize=figsize,
   1253                       row_colors=row_colors, col_colors=col_colors,
   1254                       z_score=z_score, standard_scale=standard_scale,
   1255                       mask=mask, dendrogram_ratio=dendrogram_ratio,
   1256                       colors_ratio=colors_ratio, cbar_pos=cbar_pos)
-> 1258 return plotter.plot(metric=metric, method=method,
   1259                     colorbar_kws=cbar_kws,
   1260                     row_cluster=row_cluster, col_cluster=col_cluster,
   1261                     row_linkage=row_linkage, col_linkage=col_linkage,
   1262                     tree_kws=tree_kws, **kwargs)

File ~/miniconda3/envs/cpdb/lib/python3.8/site-packages/seaborn/matrix.py:1142, in ClusterGrid.plot(self, metric, method, colorbar_kws, row_cluster, col_cluster, row_linkage, col_linkage, tree_kws, **kws)
   1139     yind = np.arange(self.data2d.shape[0])
   1141 self.plot_colors(xind, yind, **kws)
-> 1142 self.plot_matrix(colorbar_kws, xind, yind, **kws)
   1143 return self

File ~/miniconda3/envs/cpdb/lib/python3.8/site-packages/seaborn/matrix.py:1093, in ClusterGrid.plot_matrix(self, colorbar_kws, xind, yind, **kws)
   1091 # Setting ax_cbar=None in clustermap call implies no colorbar
   1092 kws.setdefault("cbar", self.ax_cbar is not None)
-> 1093 heatmap(self.data2d, ax=self.ax_heatmap, cbar_ax=self.ax_cbar,
   1094         cbar_kws=colorbar_kws, mask=self.mask,
   1095         xticklabels=xtl, yticklabels=ytl, annot=annot, **kws)
   1097 ytl = self.ax_heatmap.get_yticklabels()
   1098 ytl_rot = None if not ytl else ytl[0].get_rotation()

File ~/miniconda3/envs/cpdb/lib/python3.8/site-packages/seaborn/matrix.py:459, in heatmap(data, vmin, vmax, cmap, center, robust, annot, fmt, annot_kws, linewidths, linecolor, cbar, cbar_kws, cbar_ax, square, xticklabels, yticklabels, mask, ax, **kwargs)
    457 if square:
    458     ax.set_aspect("equal")
--> 459 plotter.plot(ax, cbar_ax, kwargs)
    460 return ax

File ~/miniconda3/envs/cpdb/lib/python3.8/site-packages/seaborn/matrix.py:306, in _HeatMapper.plot(self, ax, cax, kws)
    303     kws.setdefault("vmax", self.vmax)
    305 # Draw the heatmap
--> 306 mesh = ax.pcolormesh(self.plot_data, cmap=self.cmap, **kws)
    308 # Set the axis limits
    309 ax.set(xlim=(0, self.data.shape[1]), ylim=(0, self.data.shape[0]))

File ~/miniconda3/envs/cpdb/lib/python3.8/site-packages/matplotlib/__init__.py:1446, in _preprocess_data.<locals>.inner(ax, data, *args, **kwargs)
   1443 @functools.wraps(func)
   1444 def inner(ax, *args, data=None, **kwargs):
   1445     if data is None:
-> 1446         return func(ax, *map(sanitize_sequence, args), **kwargs)
   1448     bound = new_sig.bind(ax, *args, **kwargs)
   1449     auto_label = (bound.arguments.get(label_namer)
   1450                   or bound.kwargs.get(label_namer))

File ~/miniconda3/envs/cpdb/lib/python3.8/site-packages/matplotlib/axes/_axes.py:6227, in Axes.pcolormesh(self, alpha, norm, cmap, vmin, vmax, shading, antialiased, *args, **kwargs)
   6223     C = C.ravel()
   6225 kwargs.setdefault('snap', mpl.rcParams['pcolormesh.snap'])
-> 6227 collection = mcoll.QuadMesh(
   6228     coords, antialiased=antialiased, shading=shading,
   6229     array=C, cmap=cmap, norm=norm, alpha=alpha, **kwargs)
   6230 collection._scale_norm(norm, vmin, vmax)
   6232 coords = coords.reshape(-1, 2)  # flatten the grid structure; keep x, y

File ~/miniconda3/envs/cpdb/lib/python3.8/site-packages/matplotlib/collections.py:1939, in QuadMesh.__init__(self, coordinates, antialiased, shading, **kwargs)
   1936 self._bbox.update_from_data_xy(self._coordinates.reshape(-1, 2))
   1937 # super init delayed after own init because array kwarg requires
   1938 # self._coordinates and self._shading
-> 1939 super().__init__(**kwargs)
   1940 self.set_mouseover(False)

File ~/miniconda3/envs/cpdb/lib/python3.8/site-packages/matplotlib/_api/deprecation.py:454, in make_keyword_only.<locals>.wrapper(*args, **kwargs)
    448 if len(args) > name_idx:
    449     warn_deprecated(
    450         since, message="Passing the %(name)s %(obj_type)s "
    451         "positionally is deprecated since Matplotlib %(since)s; the "
    452         "parameter will become keyword-only %(removal)s.",
    453         name=name, obj_type=f"parameter of {func.__name__}()")
--> 454 return func(*args, **kwargs)

File ~/miniconda3/envs/cpdb/lib/python3.8/site-packages/matplotlib/collections.py:201, in Collection.__init__(self, edgecolors, facecolors, linewidths, linestyles, capstyle, joinstyle, antialiaseds, offsets, offset_transform, norm, cmap, pickradius, hatch, urls, zorder, **kwargs)
    198 self._offset_transform = offset_transform
    200 self._path_effects = None
--> 201 self._internal_update(kwargs)
    202 self._paths = None

File ~/miniconda3/envs/cpdb/lib/python3.8/site-packages/matplotlib/artist.py:1223, in Artist._internal_update(self, kwargs)
   1216 def _internal_update(self, kwargs):
   1217     """
   1218     Update artist properties without prenormalizing them, but generating
   1219     errors as if calling `set`.
   1220 
   1221     The lack of prenormalization is to maintain backcompatibility.
   1222     """
-> 1223     return self._update_props(
   1224         kwargs, "{cls.__name__}.set() got an unexpected keyword argument "
   1225         "{prop_name!r}")

File ~/miniconda3/envs/cpdb/lib/python3.8/site-packages/matplotlib/artist.py:1197, in Artist._update_props(self, props, errfmt)
   1195             func = getattr(self, f"set_{k}", None)
   1196             if not callable(func):
-> 1197                 raise AttributeError(
   1198                     errfmt.format(cls=type(self), prop_name=k))
   1199             ret.append(func(v))
   1200 if ret:

AttributeError: QuadMesh.set() got an unexpected keyword argument 'adata'

chord diagram implementation

is it simple to just implement from bokeh?

https://www.python-graph-gallery.com/chord-diagram/