Single cell RNA sequencing of multiple myeloma II

To investigate the relationship between genetic and transcriptional heterogeneity in a context of cancer progression, we devised a computational approach called HoneyBADGER to identify copy number variation and loss-of-heterozygosity in individual cells from single-cell RNA-sequencing data. By combining allele frequency and expression magnitude deviations, HoneyBADGER is able to infer the presence of subclone-specific alterations in individual cells and reconstruct subclonal architecture. Also HoneyBADGER to analyze single cells from a progressive multiple myeloma (MM) patient to identify major genetic subclones that exhibit distinct transcriptional signatures relevant to cancer progression. Overall design: We performed single cell RNA sequencing (RNA-seq) for multiple myeloma from the bone marrow and/or extramedullary sites from 3 patients. Data contain 173 and 1,339 single-cell RNA-seq from Fluidigm C1 and 10x Genomics respectively.

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Ryu D, Kim SJ, Hong Y, Jo A, Kim N, Kim HJ, Lee HO, Kim K, Park WY