overview

As single cell omics tools become increasingly important for characterizing adaptive immunity, we noted the need for open, easy-to-use software designed specifically for analysis of adaptive immune cells. We built scab to fill this need. It was engineered to use an API that should be familiar to users of scanpy [Wolf18], which is the most widely used Python package for general single cell omics analysis. Beyond the API similarities, scab builds directly on the models and functions introduced by scanpy to create specialized tools that address issues related specifically to the analysis of adaptive immune single cell omics data.

tools

scab provides a range of utilities for all stages of single cell adaptive immune analysis, including data I/O, immune receptor annotation, sample demultiplexing, antigen specificity classification, and clonal lineage assignment. scab also includes a variety of visualization tools designed to facilitate exploratory analyses and generate publication-quality figures.

Additionally, because scab builds on the AnnData objects that are a central component of scanpy, users of scab retain compatibility with the rest of the scanpy ecosystem.

file and data standards

From the start, scab was designed to be compatible with file and data formats that have been accepted as standards in the immunology community. 10x Genomics’ Chromium is the most widely used platform for single cell omics analysis, and scab’s data IO functions are designed to work directly with CellRanger output files without needing any intermediate processing. BCR and TCR annotations conform to the standards of the Adaptive Immune Receptor Repertoire (AIRR) community. Output data files are in the widely used .h5ad format, ensuring interoperability with a wide range of existing and future software.