ImmCellTyper facilitates systematic mass cytometry data analysis for deep immune profiling
- Centre for Inflammation Biology and Cancer Immunology & Peter Gorer Department of Immunobiology, King's College London, United Kingdom
- School of Cancer and Pharmaceutical Sciences, King’s College London, United Kingdom
- Research Group of Molecular Immunology, Francis Crick Institute, United Kingdom
- Haematology Department, Guy’s Hospital, United Kingdom
- Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Italy
Figures
Figure 1 with 2 supplements
Schematic diagram of BinaryClust framework.
Semi-supervised classification is first performed on selected markers in the user-defined marker expression matrix to classify and annotate major cell types. Population-of-interest can be further …
Figure 1—figure supplement 1
Manual hierarchical gating strategy for main cell linages from human peripheral blood mononuclear cell (PBMC) samples (myeloproliferative neoplasm [MPN] dataset, n = 9).
All FCS files were cleaned up to remove doublets, normalisation beads and debris (please refer to the methods for standard clean-up procedure), and pre-gated for CD45+ leukocytes. (A) Serial …
Figure 1—figure supplement 2
Clean-up procedure of cytometry by time-of-flight (CyTOF) data using Cytobank.
Figure 2 with 1 supplement
Agreement evaluation comparing manual gating and BinaryClust in myeloproliferative neoplasm (MPN) cohort (n = 9).
Manual gating of B cells, CD4 T cells, CD8 T cells, dendritic cells, NK cells, monocytes, and gamma delta T cells were performed by two independent experts using Cytobank, and mean values of the …
Figure 2—figure supplement 1
Agreement evaluation between ImmCellTyper and manual gating in influenza dataset (n = 11).
Manual gating was performed using Cytobank and exported manually. (A) Correlation plots between ImmCellTyper results and manual gating results concerning percentages in CD4 T cells, gamma delta T …
Figure 3 with 1 supplement
Comparison of manual gating (manual1 and manual2), BinaryClust, and flowSOM clustering results in myeloproliferative neoplasm (MPN) cohort (n = 9).
Interaction plots showing the individual measurement (percentage) of each study participant with indicated colours by different methods across main cell lineages (B cells, CD8 T cells, gamma delta T …
Figure 3—figure supplement 1
Boxplots of the indicated cell percentages generated by different methods.
Statistical significance was marked by asterisk. *p < 0.05, **p < 0.01, ***p < 0.001.
Figure 4
Comparison of BinaryClust, flowSOM, and linear discriminant analysis (LDA) on speed.
Bar chart showing runtime (in seconds) of the three methods in three different datasets.
Figure 5 with 1 supplement
Cell type characterisation and visualisation using ImmCellTyper pipeline in myeloproliferative neoplasm (MPN) dataset (n = 9).
(A) Intensity distribution of selected phenotypic markers used for BinaryClust classification, coloured by sample_id. (B) Pre-defined expression classification matrix for the MPN dataset, ‘+’ …
Figure 5—figure supplement 1
Comparison of different clustering methods in MPN cohort.
(A) UMAP plots of normalised expression of indicated markers (CD66b, HLADR, TCRgd, CD20, CD16, and CD161) across 2000 cells per sample in myeloproliferative neoplasm (MPN) dataset. (B) FlowSOM …
Figure 6
Applying ImmCellTyper pipeline on COVID-19 patient dataset (n = 82) published by Chevrier et al., 2021.
(A) Marker intensity distribution of selected phenotypic markers used for BinaryClust classification, coloured by disease severity (n = 22 healthy individuals, 28 mild COVID-19 patients, and 38 …
Figure 7 with 1 supplement
Quantification and statistical analysis comparing the study conditions in COVID-19 dataset (n = 82).
(A) Stacked histogram of main cell type composition per individual generated by BinaryClust, and grouped by study conditions (healthy, mild, and severe). (B) Boxplots representing cell abundance …
Figure 7—figure supplement 1
Expression heatmaps of monocytes and neotrophils in COVID-19 dataset.
Marker expression heatmap of (A) monocytes and (B) neutrophils generated by Phenograph clustering.
Figure 8
Overall schematic outline of the ImmCellTyper workflow with description for each step.
Tables
Table 1
Precision, recall, F-measure, and ARI of indicated clustering methods.
| Gated population | Counts | Cluster cell counts | True positive | Precision | Recall | F-measure | Average F-measure | ARI | Average ARI | |
|---|---|---|---|---|---|---|---|---|---|---|
| BinaryClust2 | CD4 T cells | 1,270,041 | 1,232,832 | 1,226,712 | 1.00 | 0.97 | 0.98 | 0.93 | 0.95 | 0.91 |
| CD8 T cells | 601,995 | 601,639 | 582,402 | 0.97 | 0.97 | 0.97 | 0.95 | |||
| NK cells | 389,261 | 380,999 | 376,561 | 0.99 | 0.97 | 0.98 | 0.97 | |||
| Monocytes | 576,624 | 625,735 | 568,924 | 0.91 | 0.99 | 0.95 | 0.92 | |||
| B cells | 397,279 | 380,170 | 374,501 | 0.99 | 0.94 | 0.96 | 0.95 | |||
| Dendritic cells | 135,894 | 86,012 | 84,130 | 0.98 | 0.62 | 0.76 | 0.74 | |||
| TCRgd T cells | 87,194 | 73,599 | 73,562 | 1.00 | 0.84 | 0.91 | 0.91 | |||
| flowSOM | CD4 T cells | 1,270,041 | 1,268,929 | 1,226,712 | 0.97 | 0.97 | 0.97 | 0.70 | 0.90 | 0.66 |
| (k = 20) | CD8 T cells | 601,995 | 692,374 | 571,344 | 0.83 | 0.95 | 0.88 | 0.81 | ||
| NK cells | 389,261 | 393,646 | 365,403 | 0.93 | 0.94 | 0.93 | 0.91 | |||
| Monocytes | 576,624 | 792,447 | 568,284 | 0.72 | 0.99 | 0.83 | 0.73 | |||
| B cells | 397,279 | 405,886 | 390,077 | 0.96 | 0.98 | 0.97 | 0.96 | |||
| Dendritic cells | 135,894 | 20,832 | 18,254 | 0.88 | 0.13 | 0.23 | 0.22 | |||
| TCRgd T cells | 87,194 | 19,720 | 4967 | 0.25 | 0.06 | 0.09 | 0.08 | |||
| LDA | CD4 T cells | 634,733 | 665,481 | 632,700 | 0.95 | 1.00 | 0.97 | 0.93 | 0.93 | 0.90 |
| CD8 T cells | 301,138 | 327,469 | 299,309 | 0.91 | 0.99 | 0.95 | 0.92 | |||
| NK cells | 194,470 | 202,110 | 187,259 | 0.93 | 0.96 | 0.94 | 0.92 | |||
| Monocytes | 288,338 | 301,387 | 282,836 | 0.94 | 0.98 | 0.96 | 0.94 | |||
| B cells | 198,582 | 211,090 | 195,908 | 0.93 | 0.99 | 0.96 | 0.94 | |||
| Dendritic cells | 68,152 | 90,456 | 61,785 | 0.68 | 0.91 | 0.78 | 0.75 | |||
| TCRgd T cells | 43,405 | 43,064 | 39,976 | 0.93 | 0.92 | 0.92 | 0.92 |
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ARI, Adjusted Rand Index; LDA, linear discriminant analysis.
Key resources table
| Reagent type (species) or resource | Designation | Source or reference | Identifiers | Additional information |
|---|---|---|---|---|
| Antibody | Maxpar Direct Immune Profiling Assay | Standard Biotools | Cat# 201325 | |
| Antibody | anti-CD95 (RRID:AB_314546, mouse, monoclonal) | Biolegend | Cat# 305607 | 1:200, 1.5 μl |
| Antibody | anti-TIGIT (mouse, monoclonal) | Standard Biotools | Cat# 201406 (Maxpar Direct T cell expansion panel 2) | 1:300, 1 μl |
| Antibody | anti-PD1 (mouse, monoclonal) | Standard Biotools | Cat# 201406 (Maxpar Direct T cell expansion panel 2) | 1:200, 1.5 μl |
| Antibody | anti-ICOS (hamster, monoclonal) | Standard Biotools | Cat# 201406 (Maxpar Direct T cell expansion panel 2) | 1:200, 1.5 μl |
| Antibody | anti-TIM3 (mouse, monoclonal) | Standard Biotools | Cat# 201406 (Maxpar Direct T cell expansion panel 2) | 1:300, 1 μl |
| Antibody | anti-OX40 (mouse monoclonal) | Standard Biotools | Cat# 201406 (Maxpar Direct T cell expansion panel 2) | 1:300, 1 μl |
| Antibody | anti-CXCR4 (mouse, monoclonal) | Standard Biotools | Cat# 201406 (Maxpar Direct T cell expansion panel 2) | 1:300, 1 μl |
| Genetic reagent; Recombinant DNA reagent | Pierce 16% Formaldehyde (methanol-free) | Thermo Fisher | Cat# 28906 | |
| Genetic reagent; Recombinant DNA reagent | Trypan blue solution (0.4%) | Gibco | Cat# 15250-061 | |
| Genetic reagent; Recombinant DNA reagent | Human TruStain FcX | Biolegend | Cat# 422302 | |
| Genetic reagent; Recombinant DNA reagent | EQ Four Element Calibration beads | Standard Biotools | Cat# 201078 |
Appendix 1—table 1
CyTOF antibody panel for MPN cohort.
| Antibody | Clone | Metal tag | Manufacturer |
|---|---|---|---|
| Anti-CD45 | HI30 | 89Y | Standard BioTools |
| Live/dead Indicator | N/A | 103Rh | Standard BioTools |
| Anti-CD95 | DX2 | APC | Biolegend |
| Anti-APC | APC003 | 106Cd | Standard BioTools |
| Anti-CD196 | G034E3 | 141Pr | Standard BioTools |
| Anti-OX40 | ACT35 | 142Nd | Standard BioTools |
| Anti-CD123 | 6H6 | 143Nd | Standard BioTools |
| Anti-CD19 | HIB19 | 144Nd | Standard BioTools |
| Anti-CD4 | RPA-T4 | 145Nd | Standard BioTools |
| Anti-CD8a | RPA-T8 | 146Nd | Standard BioTools |
| Anti-CD11c | Bu15 | 147Sm | Standard BioTools |
| Anti-CD16 | 3G8 | 148Nd | Standard BioTools |
| Anti-CD45RO | UCHL1 | 149Sm | Standard BioTools |
| Anti-CD45RA | HI100 | 150Nd | Standard BioTools |
| Anti-CD161 | HP-3G10 | 151Eu | Standard BioTools |
| Anti-CD194 | L291H4 | 152Sm | Standard BioTools |
| Anti-CD25 | BC96 | 153Eu | Standard BioTools |
| Anti-CD27 | O323 | 154Sm | Standard BioTools |
| Anti-CD57 | HCD57 | 155Gd | Standard BioTools |
| Anti-CD183 | G025H7 | 156Gd | Standard BioTools |
| Anti-CD185 | J252D4 | 158Gd | Standard BioTools |
| Anti-TIM-3 | F38-2E2 | 159Tb | Standard BioTools |
| Anti-CD28 | CD28.2 | 160Gd | Standard BioTools |
| Anti-CD38 | HB-7 | 161Dy | Standard BioTools |
| Anti-CD56 | NCAM16.2 | 163Dy | Standard BioTools |
| Anti-TCRgd | B1 | 164Dy | Standard BioTools |
| Anti-PD-1 | EH12.2H7 | 165Ho | Standard BioTools |
| Anti-CD294 | BM16 | 166Er | Standard BioTools |
| Anti-CD197 | G043H7 | 167Er | Standard BioTools |
| Anti-CD14 | 63D3 | 168Er | Standard BioTools |
| Anti-ICOS | C398.4A | 169Tm | Standard BioTools |
| Anti-CD3 | UCHT1 | 170Er | Standard BioTools |
| Anti-CD20 | 2H7 | 171Yb | Standard BioTools |
| Anti-CD66b | G10F5 | 172Yb | Standard BioTools |
| Anti-HLA-DR | LN3 | 173Yb | Standard BioTools |
| Anti-IgD | IA6-2 | 174Yb | Standard BioTools |
| Anti-CXCR4 | 12G5 | 175Lu | Standard BioTools |
| Anti-CD127 | A019D5 | 176Yb | Standard BioTools |
| Anti-TIGIT | MBSA43 | 209Bi | Standard BioTools |
