pyvdj 0.1.0

V(D)J sequencing data analysis

pyVDJ

V(D)J sequencing data analysis

This package adds 10x Genomics V(D)J sequencing data to an AnnData object's .uns part, and also makes annotation columns in .obs. This enables plotting various V(D)J properties and handling mRNA and V(D)J sequencing data together.

Install

pip3 install pyvdj

Usage

import pyvdj
adata = pyvdj.load_vdj(paths, samples, adata)
adata = pyvdj.vdj_add_obs(adata, obs=['is_clone'])

For a detailed description, see the tutorial.

Details

The package has 3 main functions that

• read metrics_summary.csv files into a pandas dataframe.
• load filtered_contig_annotations.csv files into an AnnData object.
• create annotations in the AnnData object.

Read metrics

The read10xsummary function requires a list of paths to metrics_summary.csv files, and optionally a dictionary of path:samplename. It returns a dataframe of the metrics.

Load V(D)J data

The load_vdj function loads 10x V(D)J sequencing data (filtered_contig_annotations.csv files) into an AnnData object's .uns['pyvdj'] slot, and returns the object. The adata.uns['pyvdj'] slot is a dictionary with the following elements:

• 'df': a dataframe containing V(D)J data
• 'obs_col': the anndata.obs columname of matching cellnames.
• 'samples': a dictionary of filename:samplename

More entries will be added in the future. If an anndata object is not supplied, the function returns the dictionary.

Arguments:

• paths: list of paths to filtered_contig_annotations.csv files.
• samples: a dictionary of path:samplename.
• adata: the AnnData object.
• add_obs: whether to add some default .obs metadata columns.

Add annotations

The adata.uns['pyvdj']['df'] is a pandas dataframe of the V(D)J data, with two additional columns that contain unique cell barcode and clonotype labels. These are generated using the user-supplied sample names: cellbarcode + '_' + samplename and clonotype + '_' + samplename.

These unique cell names are used to match the V(D)J cells to the AnnData .X cells, using adata.obs['vdj_obs']. The user has to prepare this column using the cell barcodes and the sample names.

The add_obs function can add the following annotations:

• 'has_vdjdata': does the cell have V(D)J sequencing data?
• 'clonotype': add clonotype name
• 'is_clone': does it have a clone?
• 'is_productive': are all chains productive?
• 'chains': adds a boolean column for each chain
• 'genes': adds a boolean column for each constant gene

More will be added in the future.

Dependencies

The package has been developed on data prepared with Cell Ranger v2.1.1 (Chemistry: Single Cell V(D)J; V(D)J Reference: GRCh38-alts-ensembl) and has been tested with the following Python package versions:

pandas 0.24.2
anndata 0.6.21
scanpy 1.4.3