Single cell RNA sequencing of multiple myeloma II
Updated November 15, 2021To 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.
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Atlas
Analysis Portals
NoneProject Label
HumanBoneMarrowMyelomaSpecies
Homo sapiens
Sample Type
specimens
Anatomical Entity
hematopoietic system
Organ Part
Selected Cell Types
plasma cell
Disease Status (Specimen)
plasma cell myeloma
Disease Status (Donor)
plasma cell myeloma
Development Stage
human adult stage
Library Construction Method
Nucleic Acid Source
single cell
Paired End
false, trueAnalysis Protocol
MultiSampleSmartSeq2_v2.2.6, SmartSeq2SingleSample_v5.1.5, optimus_post_processing_v1.0.0, optimus_v4.2.3File Format
Cell Count Estimate
1.5kDonor Count
3