Usage principles

Import scirpy as

import scanpy as sc
import scirpy as ir

Workflow

Scirpy is an extension to Scanpy and adheres to its workflow principles:

• The API is divided into preprocessing (pp), tools (tl), and plotting (pl).

• All functions work on AnnData objects.

• The AnnData instance is modified inplace, unless the functions is called with the keyword argument inplace=False.

We decided to handle a few minor points differenlty to Scanpy:

• Plotting functions with inexpensive computations (e.g. scirpy.pl.clonal_expansion()) call the corresponding tool (scirpy.tl.clonal_expansion()) on-the-fly and don’t store the results in the AnnData object.

• All plotting functions, by default, return a Axes object, or a list of such.

Data structure

For instructions how to load data into scirpy, see Loading TCR data with scirpy.

Scirpy leverages the AnnData data structure which combines a gene expression matrix (.X), gene-level annotations (.var) and cell-level annotations (.obs) into a single object. AnnData forms the basis for the Scanpy analysis workflow for single-cell transcriptomics data.

Image by F. Alex Wolf.

Scirpy adds the following TCR-related columns to AnnData.obs:

• has_tcr: True for all cells with a T-cell receptor

• TRA_1_<attr>/TRA_2_<attr>: columns related to the primary and secondary TCR-alpha chain

• TRB_1_<attr>/TRB_2_<attr>: columns related to the primary and secondary TCR-beta chain

Where <attr> is any of:

• c_gene, v_gene, d_gene, j_gene: The gene symbols of the respective genes

• cdr3 and cdr3_nt: The amino acoid and nucleotide sequences of the CDR3 regions

• junction_ins: The number of nucleotides inserted in the VD + DJ junctions or the VJ junction, respectively.