Magic™ BCR Repertoire Profiling for B Cell Clones Identification

Creative Biolabs offers the unparalleled mass sequencing service to analyze the B cell receptors (BCR) repertoires. Our scientists adopt hierarchical clustering algorithm using single linkage with Hamming distance to identify clones with high conﬁdence. We can provide a fully automated method for clonal grouping. We are proud to introduce this high-quality service to our global customers.

Current Approaches to Identify B Cell Clone

Adaptive immunity is motivated by somatic hypermutation, expansion, and selection of B cell clones. Each clone is the progeny of a single B cell responding to an antigen (Ag), with diverse Ig receptors. Our ability to proﬁle this adaptive immune response has dramatically improved through the application of next-generation sequencing (NGS). Such data provides a window into the microevolutionary dynamics which drives successful immune responses and the dysregulation that occurs with aging or disease. This microevolutionary process known as afﬁnity maturation results in B cells with diverse immunoglobulin (Ig) receptors. Clonal partitioning of adaptive immune receptor repertoire sequencing data is central to a wide range of applications. For example, clone size distributions are the basis for several diversity measures, such as species richness, Shannon entropy, and the Gini-Simpson index. Diseases such as chronic lymphocytic leukemia are characterized by low diversity, which is driven by the dominance of a small number of clones. Identifying clones that include sequences with known Ag speciﬁcities has also been used to reveal novel Ag-speciﬁc sequences. However, despite its importance, the identiﬁcation of sequences that belong to the same B cell clone in these data remains a signiﬁcant challenge. Although several hierarchical clustering-based methods have been proposed, they always result in a signiﬁcant loss of sensitivity. There is no consensus on the best method for grouping Ig sequences into B cell clones. Most current approaches leverage the high diversity of the junction region as a “ﬁngerprint” to identify each B cell clone. However, these algorithms are time consuming, which is computationally intractable for large sequencing datasets.

Fig.1 The hierarchical clustering dendrogram.

B Cell Clones Identification Service in Creative Biolabs

Creative Biolabs has developed an effective strategy to identify B cell clones by BCR repertoire data analysis based on hierarchical clustering. This strategy consists of (1) library preparation, (2) BCR sequencing on our Magic™ platform, and (3) data processing, including distance metrics, analysis of speciﬁcity and sensitivity, and Shannon entropy calculation. The results show that single-linkage hierarchical clustering with nucleotide Hamming distance has excellent performance, with high speciﬁcity and sensitivity.

Key Advantages

Based on hierarchical clustering
Low sample input
High speciﬁcity, sensitivity, and accuracy (all > 99%)
Highly professional Ph.D. level scientists
Competitive and affordable price

With years of research and development experience in the field of immunology, Creative Biolabs has owned a group of scientists who have the distinguished skills in BCR repertoires sequencing. We are proficient in BCR repertoire analysis for B cell clones identification based on hierarchical clustering. We are pleased to offer the best service with the most accurate results for our global customers.

Please contact us for more information and a detailed quote.

Reference

Gupta, N.T.; et al. Hierarchical clustering can identify B cell clones with high confidence in Ig repertoire sequencing data. J Immunol. 2017, 198(6):2489-2499.

All listed services and products are For Research Use Only. Do Not use in any diagnostic or therapeutic applications.

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