Single-Cell Whole Genome Analysis in Python.

API

Import scgenome as:

import scgenome

Preprocessing: pp

Data loading and pre-processing functionality.

Data loading

pp.read_dlp_hmmcopy(alignment_results_dir, ...)	Read hmmcopy results from the DLP pipeline.
pp.convert_dlp_hmmcopy(metrics_data, cn_data)	Convert hmmcopy pandas dataframes to anndata
pp.convert_dlp_signals(hscn, metrics_data)	Convert signals pandas dataframes to anndata
pp.read_bam_bin_counts(bins, bams[, excluded])	Count reads in bins from bams
pp.read_snv_genotyping(filename)	Read SNV genotyping into an AnnData

Filtering

pp.filter_cells(adata[, filters, inplace])	Filter poor quality cells based on the filters provided.
pp.calculate_filter_metrics(adata[, ...])	Calculate additional filtering metrics to be used by other filtering methods.

Tools: tl

Any transformation of the data matrix that is not preprocessing. In contrast to a preprocessing function, a tool usually adds an easily interpretable annotation to the data matrix, which can then be visualized with a corresponding plotting function.

Clustering

tl.cluster_cells(adata[, layer_name, ...])	Cluster cells by copy number.
tl.aggregate_clusters_hmmcopy(adata)	Aggregate hmmcopy copy number by cluster to create cluster CN matrix
tl.aggregate_clusters(adata[, agg_X, ...])	Aggregate copy number by cluster to create cluster CN matrix
tl.sort_cells(adata[, layer_name, cell_ids, ...])	Sort cells by hierarchical clustering on copy number values.

Embeddings

tl.compute_umap(adata[, layer_name, ...])	Cluster cells by copy number.
tl.pca_loadings(adata[, layer, ...])	Compute PCA loadings matrix

Generating binned data

tl.create_bins(binsize)	Create a regular binning of the genome
tl.count_gc(bins, genome_fasta[, ...])	Count gc in each bin
tl.mean_from_bigwig(bins, bigwig_file, ...)	Count gc in each bin

Gene regions

tl.read_ensemble_genes_gtf(gtf_filename)	Read an ensembl gtf and extract gene start end
tl.aggregate_genes(adata, genes[, ...])	Aggregate copy number by gene to create gene CN matrix

Phylogenetics

tl.prune_leaves(tree, f)
tl.align_cn_tree(tree, adata)

Anndata Manipulation

tl.ad_concat_cells(adatas)

Concatenate a list of anndata by obs (cells)

Plotting: pl

The plotting module scgenome.pl largely parallels the tl.* and a few of the pp.* functions. For most tools and for some preprocessing functions, you’ll find a plotting function with the same name.

Note

TODO: more plotting functions matching tools

Copy number profiles and heatmaps

pl.plot_cn_profile(adata, obs_id[, ...])	Plot scatter points of copy number across the genome or a chromosome.
pl.plot_cell_cn_matrix(adata[, layer_name, ...])	Plot a copy number matrix
pl.plot_cell_cn_matrix_fig(adata[, ...])	Plot a copy number matrix
pl.plot_gc_reads(adata, obs_id, **kwargs)	Plot scatter points of gc by read count.

Phylogenetics

pl.plot_tree_cn(tree, adata[, ...])

Plot a tree aligned to a CN values matrix heatmap