Bioinformatics · 2020 · 226 citations · 12 references
Life SciencesBioinformaticsImmunologyCellular ImmunologySingle-cell BioinformaticsTranscriptomicsImmunogenomicsSingle-cell AnalysisSingle-cell Data VisualizationSingle-cell GenomicsSingle-cell IntegrationSingle-cell TranscriptomicsAdaptive Immune RepertoiresBioinformatic PipelinesHigh-throughput Immune Repertoire AnalysisIntegration Of Single-cell DatasetsReceptorsT Cell Receptor SequencingT Cell ReceptorsT-cell Repertoire Analysis
SUMMARY: Advances in single-cell technologies have enabled the investigation of T-cell phenotypes and repertoires at unprecedented resolution and scale. Bioinformatic methods for the efficient analysis of these large-scale datasets are instrumental for advancing our understanding of adaptive immune responses. However, while well-established solutions are accessible for the processing of single-cell transcriptomes, no streamlined pipelines are available for the comprehensive characterization of T-cell receptors. Here, we propose single-cell immune repertoires in Python (Scirpy), a scalable Python toolkit that provides simplified access to the analysis and visualization of immune repertoires from single cells and seamless integration with transcriptomic data. AVAILABILITY AND IMPLEMENTATION: Scirpy source code and documentation are available at https://github.com/icbi-lab/scirpy. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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SciPy 1.0: fundamental algorithms for scientific computing in Python
Nature Methods · 2020 · 37.9K citations · Full text
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