kb_python.report

Module Contents

Functions

dict_to_table(→ plotly.graph_objects.Figure)

Convert a dictionary to a Plot.ly table of key-value pairs.

knee_plot(→ plotly.graph_objects.Figure)

Generate knee plot card.

genes_detected_plot(→ plotly.graph_objects.Figure)

Generate genes detected plot card.

elbow_plot(→ plotly.graph_objects.Figure)

Generate elbow plot card.

pca_plot(→ plotly.graph_objects.Figure)

Generate PCA plot card.

write_report(→ str)

Render the Jupyter notebook report with Jinja2.

execute_report(→ Tuple[str, str])

Execute the report and write the results as a Jupyter notebook and HTML.

render_report(→ Dict[str, str])

Render and execute the report.

Attributes

REPORT_DIR

BASIC_TEMPLATE_PATH

MATRIX_TEMPLATE_PATH

MARGIN

kb_python.report.REPORT_DIR
kb_python.report.BASIC_TEMPLATE_PATH
kb_python.report.MATRIX_TEMPLATE_PATH
kb_python.report.MARGIN
kb_python.report.dict_to_table(d: Dict[str, Any], column_ratio: List[int] = [3, 7], column_align: List[str] = ['right', 'left']) → plotly.graph_objects.Figure

Convert a dictionary to a Plot.ly table of key-value pairs.

Parameters

  • d – Dictionary to convert

  • column_ratio – Relative column widths, represented as a ratio, defaults to [3, 7]

  • column_align – Column text alignments, defaults to [‘right’, ‘left’]

Returns

Figure

kb_python.report.knee_plot(n_counts: List[int]) → plotly.graph_objects.Figure

Generate knee plot card.

Parameters

n_counts – List of UMI counts

Returns

Figure

kb_python.report.genes_detected_plot(n_counts: List[int], n_genes: List[int]) → plotly.graph_objects.Figure

Generate genes detected plot card.

Parameters

  • n_counts – List of UMI counts

  • n_genes – List of gene counts

Returns

Figure

kb_python.report.elbow_plot(pca_variance_ratio: List[float]) → plotly.graph_objects.Figure

Generate elbow plot card.

Parameters

pca_variance_ratio – List PCA variance ratios

Returns

Figure

kb_python.report.pca_plot(pc: numpy.ndarray) → plotly.graph_objects.Figure

Generate PCA plot card.

Parameters

pc – Embeddings

Returns

Figure

kb_python.report.write_report(stats_path: str, info_path: str, inspect_path: str, out_path: str, matrix_path: Optional[str] = None, barcodes_path: Optional[str] = None, genes_path: Optional[str] = None, t2g_path: Optional[str] = None) → str

Render the Jupyter notebook report with Jinja2.

Parameters

  • stats_path – Path to kb stats JSON

  • info_path – Path to run_info.json

  • inspect_path – Path to inspect.json

  • out_path – Path to Jupyter notebook to generate

  • matrix_path – Path to matrix

  • barcodes_path – List of paths to barcodes.txt

  • genes_path – Path to genes.txt, defaults to None

  • t2g_path – Path to transcript-to-gene mapping

Returns

Path to notebook generated

kb_python.report.execute_report(execute_path: str, nb_path: str, html_path: str) → Tuple[str, str]

Execute the report and write the results as a Jupyter notebook and HTML.

Parameters

  • execute_path – Path to Jupyter notebook to execute

  • nb_path – Path to Jupyter notebook to generate

  • html_path – Path to HTML to generate

Returns

Tuple containing executed notebook and HTML

kb_python.report.render_report(stats_path: str, info_path: str, inspect_path: str, nb_path: str, html_path: str, matrix_path: Optional[str] = None, barcodes_path: Optional[str] = None, genes_path: Optional[str] = None, t2g_path: Optional[str] = None, temp_dir: str = 'tmp') → Dict[str, str]

Render and execute the report.

Parameters

  • stats_path – Path to kb stats JSON

  • info_path – Path to run_info.json

  • inspect_path – Path to inspect.json

  • nb_path – Path to Jupyter notebook to generate

  • html_path – Path to HTML to generate

  • matrix_path – Path to matrix

  • barcodes_path – List of paths to barcodes.txt

  • genes_path – Path to genes.txt, defaults to None

  • t2g_path – Path to transcript-to-gene mapping

  • temp_dir – Path to temporary directory, defaults to tmp

Returns

Dictionary containing notebook and HTML paths