Justin Meskas
BC Cancer Agency
9 Papers
48 Citations
Justin Meskas is an academic researcher from BC Cancer Agency. The author has contributed to research in topics: Population & Mass cytometry. The author has an hindex of 5, co-authored 7 publications. Previous affiliations of Justin Meskas include BC Cancer Research Centre.
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Papers
flowCL: ontology-based cell population labelling in flow cytometry
Mélanie Courtot,Justin Meskas,Alexander D. Diehl,Radina Droumeva,Raphael Gottardo,Adrin Jalali,Mohammad Jafar Taghiyar,Holden T. Maecker,J. Philip McCoy,Alan Ruttenberg,Richard H. Scheuermann,Richard H. Scheuermann,Ryan R. Brinkman +12 more
TL;DR: By providing automated labelling of cell populations based on their immunophenotype, flowCL allows for unambiguous and reproducible identification of standardized cell types.
ddPCRclust: an R package and Shiny app for automated analysis of multiplexed ddPCR data.
TL;DR: dPCRclust is an R package for automated analysis of data from Bio‐Rad's droplet digital PCR systems (QX100 and QX200) that can automatically analyze and visualize multiplexed ddPCR experiments with up to four targets per reaction.
flowCut — An R package for precise and accurate automated removal of outlier events and flagging of files based on time versus fluorescence analysis
TL;DR: FlowCut as mentioned in this paper automatically detects anomaly events and flags files for flow cytometry experiments using R. FlowCut is an R package that detects and removes technical artifacts that occur during the data acquisition process of cytometry data and its analysis results.
Mass Cytometry Based Classification of Inter- and Intra-Tumoral Heterogeneity in Diffuse Large B-Cell Lymphoma
Manabu Kusakabe,Xuehai Wang,Guillermo Simkin,Justin Meskas,Chaoran Zhang,Daisuke Ennishi,Robert Kridel,Merrill Boyle,Elizabeth A. Chavez,Stacy Hung,David W. Scott,Christian Steidl,Randy D. Gascoyne,Ryan R. Brinkman,Andrew P. Weng +14 more
TL;DR: Time-of-flight mass cytometry (CyTOF) is used to explore clonal phenotypic substructure in diffuse large B-cell lymphoma (DLBCL), a diagnostic entity notorious for clinical heterogeneity, and finds that novel information can be derived from CyTOF data with important implications for the authors' understanding of both intra- and inter-tumoral heterogeneity in DLBCL.
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