sciReptor: analysis of single-cell level immunoglobulin repertoires

BMC Bioinformatics

Software

Peter F. Arndt¹  Hedda Wardemann²  Christian E. Busse²  Katharina Imkeller² 

[1] Department for Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, 14195, Berlin, Germany;Division of B Cell Immunology, German Cancer Research Center, Feld 280, 69120, Heidelberg, Germany;

关键词: Single cell;    Antigen receptor repertoire;    Immunoglobulin;    B cell repertoire;   

DOI  :  10.1186/s12859-016-0920-1

 received in 2015-09-04, accepted in 2016-01-29,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundThe sequencing of immunoglobulin (Ig) transcripts from single B cells yields essential information about Ig heavy:light chain pairing, which is lost in conventional bulk sequencing experiments. The previously limited throughput of single-cell approaches has recently been overcome by the introduction of multiple next-generation sequencing (NGS)-based platforms. Furthermore, single-cell techniques allow the assignment of additional data types (e.g. cell surface marker expression), which are crucial for biological interpretation. However, the currently available computational tools are not designed to handle single-cell data and do not provide integral solutions for linking of sequence data to other biological data.ResultsHere we introduce sciReptor, a flexible toolkit for the processing and analysis of antigen receptor repertoire sequencing data at single-cell level. The software combines bioinformatics tools for immunoglobulin sequence annotation with a relational database, where raw data and analysis results are stored and linked. sciReptor supports attribution of additional data categories such as cell surface marker expression or immunological metadata. Furthermore, it comprises a quality control module as well as basic repertoire visualization tools.ConclusionsciReptor is a flexible framework for standardized sequence analysis of antigen receptor repertoires on single-cell level. The relational database allows easy data sharing and downstream analyses as well as immediate comparisons between different data sets.

【 授权许可】

CC BY   
© Imkeller et al. 2016