Download-button_s

Experiment Overview

Repository ID: FR-FCM-ZYDW Experiment name: A Beginner's Guide To Analyzing and Visualizing Mass Cytometry Data MIFlowCyt score: 84.00%
Primary researcher: Abby Kimball PI/manager: Eric Clambey Uploaded by: Abby Kimball
Experiment dates: 2016-10-01 - 2018-01-01 Dataset uploaded: Nov 2017 Last updated: Aug 2018
Keywords: [bead-based separation] [mass cytometry] [CyTOF] [CyTOF; mass cytometry; flow cytometry; standardization] [viSNE] [SPADE] [PhenoGraph] [Citrus] [X-shift] [VorteX] [non-small cell lung cancer] [gHV68] Manuscripts: [29255085]
Organizations: University of Colorado, Anschutz Medical Campus, Anesthesiology, Aurora, CO (80045)
Purpose: The purpose of this experiment was to test a consistent dataset with a variety of clustering algorithms (viSNE, SPADE, PhenoGraph, X-shift, and Citrus) designed for high dimensional data.
Conclusion: 1) We have outlined the steps required for successful and optimal analyses with various algorithms. 2) The strengths and weaknesses of algorithms used and a guide to determining which algorithm is most appropriate for a given dataset. 3) Unique biological insights into changes in cellular abundance, expression, and population structure in the experimental context of gHV68 infected murine lungs and murine lungs injected with an orthotopically implanted NSCLC cell line.
Comments: Article can be accessed here: http://www.jimmunol.org/content/200/1/3 PubMed ID: 29255085
Funding: This work was supported by National Institutes of Health Grants R01 CA103632 and R01 CA168558 (to L.F.v.D.) and R01 CA162226 and P50 CA058187 (to R.A.N.), an American Heart Association National Scientist Development grant, the Crohn’s and Colitis Foundation of America, and a Career Enhancement Award from the University of Colorado Lung Cancer SPORE (all to E.T.C.). The Flow Cytometry Shared Resource receives direct funding support from the National Cancer Institute through Cancer Center Support Grant P30CA046934.
Quality control: Posted .fcs files contain raw data, in which samples run with Fluidigm EQ beads. For downstream analysis, as outlined in the accompanying manuscript, data were normalized relative to Fluidigm EQ beads using the Nolan lab Normalizer software downloaded from the Nolan lab Github. DNA+ "singlets" (191Ir+ 193Ir+) that were viable (195Pt-) were gated and analyzed for all downstream analyses. Multiple algorithms were used to analyze the following datasets, most of which provided consistent biological insights. Many different iterations of analyses via the algorithms were performed to ensure optimization and accuracy.


Experiment variables

Conditions
· B6 Clambey LO 110116 B6 lung 2_01.fcs · Clambey LO 110116 B6 lung 3_01.fcs · Clambey LO 110116 B6 lung1_01.fcs · Clambey LO 11022016 B6 lung 4_01.fcs · Clambey LO 11022016 B6 lung 5_01.fcs
· IL10KO Calmbey LO 11022016 IL10 KO lung 3_01.fcs · Clambey LO 110116 IL10KO lung 1_01.fcs · Clambey LO 110116 IL10KO lung 2_01.fcs · Clambey LO 11022016 IL10 KO lung 4_01.fcs

Individuals
· B6 #1 Clambey LO 110116 B6 lung1_01.fcs
· B6 #2 Clambey LO 110116 B6 lung 2_01.fcs
· B6 #3 Clambey LO 110116 B6 lung 3_01.fcs
· B6 #4 Clambey LO 11022016 B6 lung 4_01.fcs
· B6 #5 Clambey LO 11022016 B6 lung 5_01.fcs
· IL10KO #1 Clambey LO 110116 IL10KO lung 1_01.fcs
· IL10KO #2 Clambey LO 110116 IL10KO lung 2_01.fcs
· IL10KO #3 Calmbey LO 11022016 IL10 KO lung 3_01.fcs
· IL10KO #4 Clambey LO 11022016 IL10 KO lung 4_01.fcs

Download FCS Files or login and see the dataset in your inbox for further annotation details.