`larry._analysis._estimate_growth_rates`¶

Module Contents¶

Functions¶

`plot_growth_rates`(→ None)	Parameters:
`_get_plot_vmin_vmax`(adata)
`_background_scatter_UMAP`(ax, X_umap[, c, alpha, s, ...])
`_d2_lineage_cell_idx`(meta_df, d2_mask[, t0, time_key])
`_plot_continuous_highlight_UMAP`(ax, X_umap, subset_idx)
`plot_growth_rate_UMAPs`(adata[, plot_keys, titles, ...])
`_enumerate_time_pairs`(t)	Get pairs of timepoints
`_calculate_growth_rate_from_counts`(→ numpy.ndarray)	Estimate growth rate from clonal lineage counts at multiple timepoints
`estimate_growth_rates`(→ dict)	Estimate growth rate from counts of daughter cells relative to d2 progenitors, across multiple timepoints.

Attributes¶

`__module_name__`
`__author__`
`__email__`

larry._analysis._estimate_growth_rates.__module_name__ = _estimate_growth_rates.py¶

larry._analysis._estimate_growth_rates.__author__¶

larry._analysis._estimate_growth_rates.__email__¶

larry._analysis._estimate_growth_rates.plot_growth_rates(adata: anndata.AnnData, colors: list = ['dodgerblue', 'crimson'], labels: list = ['d4', 'd6']) → None¶: None

larry._analysis._estimate_growth_rates._get_plot_vmin_vmax(adata)¶

larry._analysis._estimate_growth_rates._background_scatter_UMAP(ax, X_umap, c='lightgrey', alpha=0.2, s=1, rasterized=True)¶

larry._analysis._estimate_growth_rates._d2_lineage_cell_idx(meta_df, d2_mask, t0=2, time_key='Time point')¶

larry._analysis._estimate_growth_rates._plot_continuous_highlight_UMAP(ax, X_umap, subset_idx, c='navy', s=5, vmin=None, vmax=None, cax=None, cbar_shrink=0.5)¶

larry._analysis._estimate_growth_rates.plot_growth_rate_UMAPs(adata, plot_keys=['d2_d4', 'd2_d6'], titles=['log(d4/d2) observed growth rate', 'log(d6/d2) observed growth rate'], vmin=None, vmax=None)¶

larry._analysis._estimate_growth_rates._enumerate_time_pairs(t)¶

Get pairs of timepoints

t: unique time points for which there are counts type: list

time_pairs: type: list

larry._analysis._estimate_growth_rates._calculate_growth_rate_from_counts(t0_count: numpy.ndarray, tf_count: numpy.ndarray, t0: float, tf: float, pseudocount: float = 1) → numpy.ndarray¶

Estimate growth rate from clonal lineage counts at multiple timepoints

t0_count: type: np.ndarray
tf_count: type: np.ndarray
t0: type: float
tf: type: float
pseudocount: type: float

growth_rate: type: np.ndarray

Source: https://github.com/gifford-lab/prescient-analysis/blob/master/notebooks/02b-weinreb2020-proliferation.ipynb

larry._analysis._estimate_growth_rates.estimate_growth_rates(adata: anndata.AnnData, pseudocount: int = 1, return_dict: bool = False, plot: bool = True, plot_colors: list = ['dodgerblue', 'crimson'], plot_labels: list = ['d4', 'd6']) → dict¶

Estimate growth rate from counts of daughter cells relative to d2 progenitors, across multiple timepoints.

count_dict

pseudocount

GrowthRateDict

larry._analysis._estimate_growth_rates¶

Module Contents¶

Functions¶

Attributes¶

`larry._analysis._estimate_growth_rates`¶