Pseudotime-dependent genes

spaTrack.filter_gene(adata: AnnData, min_exp_prop: float, hvg_gene: int = 2000) → AnnData[source]

Filter genes by minimum expression proporation and cluster differential expression.

Parameters:

  • adata – An AnnData object.

  • min_exp_prop – Minimum expression proporation.

  • abs_FC – Log2 foldchange in differential expression.

Returns:

The AnnData object formed by filtered genes.

Return type:

AnnData

spaTrack.ptime_gene_GAM(adata: AnnData, core_number: int = 3) → DataFrame[source]

Fit GAM model by formula gene_exp ~ Ptime.

Call GAM_gene_fit() by multi-process computing to improve operational speed.

Parameters:

  • adata – An AnnData object.

  • core_number – Number of processes for caculating.

Returns:

An DataFrame object, each column is one index.

  • pvalue: calculated from GAM

  • R2: a goodness-of-fit measure. larger value means better fit

  • pattern: increase or decrease. drection of gene expression changes across time

  • fdr: BH fdr

Return type:

DataFrame

spaTrack.order_trajectory_genes(adata: AnnData, df_sig_res: DataFrame, cell_number: int)[source]

Split cells sorted by ptime into widonws.

Order genes according number id of the maximum expression window.

Parameters:

  • adata – An AnnData object.

  • df_sig_res – Return dataframe by ptime_gene_GAM() after filtering as significat gene dataframe.

  • cell_number – Cell number within splited window.

Returns:

  • columns:Sortted significant genes expression matrix according to mean expression value in windows

  • index: cell_id

Return type:

DataFrame

spaTrack.plot_trajectory_gene_heatmap(sig_gene_exp_order: DataFrame, smooth_length: int, cmap_name: str = 'twilight_shifted', gene_label_size: int = 30, fig_width=8, fig_height=10)[source]
Parameters:

  • sig_gene_exp_order – Gene ordered expression dataframe.

  • smooth_length – length of smoothing window

  • cmap_name – Color palette

  • fig_width – The width and height of figure

  • fig_height – The width and height of figure

Return type:

A heatmap plot, column-representing cells, row-representing genes.

spaTrack.plot_trajectory_gene(adata: AnnData, gene_name: str, line_width: int = 5, show_cell_type: bool = False, point_size=20) → Axes[source]
Parameters:

  • adata – An AnnData object.

  • gene_name – Gene used to plot.

  • line_width – Widthe of fitting line.

  • show_cell_type – Whether to show cell type in plot.

  • point_size – The size of point

Returns:

An Axes object. X axis indicates pseduotime and y axis indicates gene expression value.

Return type:

Axes