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1. Human immunoglobulin gene allelic variation impacts germline-targeting vaccine priming

Author

deCamp, Allan C., Corcoran, Martin M., Fulp, William J., Willis, Jordan R., Cottrell, Christopher A., Bader, Daniel L. V., Kalyuzhniy, Oleksandr, Leggat, David J., Cohen, Kristen W., Hyrien, Ollivier, Menis, Sergey, Finak, Greg, Ballweber-Fleming, Lamar, Srikanth, Abhinaya, Plyler, Jason R., Rahaman, Farhad, Lombardo, Angela, Philiponis, Vincent, Whaley, Rachael E., Seese, Aaron, Brand, Joshua, Ruppel, Alexis M., Hoyland, Wesley, Mahoney, Celia R., Cagigi, Alberto, Taylor, Alison, Brown, David M., Ambrozak, David R., Sincomb, Troy, Mullen, Tina-Marie, Maenza, Janine, Kolokythas, Orpheus, Khati, Nadia, Bethony, Jeffrey, Roederer, Mario, Diemert, David, Koup, Richard A., Laufer, Dagna S., McElrath, Juliana M., McDermott, Adrian B., Karlsson Hedestam, Gunilla B., and Schief, William R.

Published
2024
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4. Selective Clustering Annotated using Modes of Projections

Author

Greene, Evan, Finak, Greg, and Gottardo, Raphael

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning
Abstract

Selective clustering annotated using modes of projections (SCAMP) is a new clustering algorithm for data in $\mathbb{R}^p$. SCAMP is motivated from the point of view of non-parametric mixture modeling. Rather than maximizing a classification likelihood to determine cluster assignments, SCAMP casts clustering as a search and selection problem. One consequence of this problem formulation is that the number of clusters is $\textbf{not}$ a SCAMP tuning parameter. The search phase of SCAMP consists of finding sub-collections of the data matrix, called candidate clusters, that obey shape constraints along each coordinate projection. An extension of the dip test of Hartigan and Hartigan (1985) is developed to assist the search. Selection occurs by scoring each candidate cluster with a preference function that quantifies prior belief about the mixture composition. Clustering proceeds by selecting candidates to maximize their total preference score. SCAMP concludes by annotating each selected cluster with labels that describe how cluster-level statistics compare to certain dataset-level quantities. SCAMP can be run multiple times on a single data matrix. Comparison of annotations obtained across iterations provides a measure of clustering uncertainty. Simulation studies and applications to real data are considered. A C++ implementation with R interface is $\href{https://github.com/RGLab/scamp}{available\ online}$., Comment: Submitted for journal review (JMLR) on July 21, 2018

Published
2018

7. Pooled-Peptide Epitope Mapping Strategies Are Efficient and Highly Sensitive: An Evaluation of Methods for Identifying Human T Cell Epitope Specificities in Large-Scale HIV Vaccine Efficacy Trials.

Author

Fiore-Gartland, Andrew, Manso, Bryce, Friedrich, David, Gabriel, Erin, Finak, Greg, Moodie, Zoe, Hertz, Tomer, De Rosa, Stephen, Frahm, Nicole, Gilbert, Peter, and McElrath, M

Subjects
AIDS Vaccines, Adolescent, Adult, CD8-Positive T-Lymphocytes, Clinical Trials as Topic, Cohort Studies, Double-Blind Method, Enzyme-Linked Immunospot Assay, Epitope Mapping, Epitopes, T-Lymphocyte, Female, Humans, Male, Middle Aged, Peptides, Reproducibility of Results, Research Design, Sensitivity and Specificity, Young Adult
Abstract

The interferon gamma, enzyme-linked immunospot (IFN-γ ELISpot) assay is widely used to identify viral antigen-specific T cells is frequently employed to quantify T cell responses in HIV vaccine studies. It can be used to define T cell epitope specificities using panels of peptide antigens, but with sample and cost constraints there is a critical need to improve the efficiency of epitope mapping for large and variable pathogens. We evaluated two epitope mapping strategies, based on group testing, for their ability to identify vaccine-induced T-cells from participants in the Step HIV-1 vaccine efficacy trial, and compared the findings to an approach of assaying each peptide individually. The group testing strategies reduced the number of assays required by >7-fold without significantly altering the accuracy of T-cell breadth estimates. Assays of small pools containing 7-30 peptides were highly sensitive and effective at detecting single positive peptides as well as summating responses to multiple peptides. Also, assays with a single 15-mer peptide, containing an identified epitope, did not always elicit a response providing validation that 15-mer peptides are not optimal antigens for detecting CD8+ T cells. Our findings further validate pooling-based epitope mapping strategies, which are critical for characterizing vaccine-induced T-cell responses and more broadly for informing iterative vaccine design. We also show ways to improve their application with computational peptide:MHC binding predictors that can accurately identify the optimal epitope within a 15-mer peptide and within a pool of 15-mer peptides.

Published
2016

8. Table S4 from Single-cell Profiling Uncovers a Muc4-Expressing Metaplastic Gastric Cell Type Sustained by Helicobacter pylori-driven Inflammation

Author

O'Brien, Valerie P., primary, Kang, Yuqi, primary, Shenoy, Meera K., primary, Finak, Greg, primary, Young, William C., primary, Dubrulle, Julien, primary, Koch, Lisa, primary, Rodriguez Martinez, Armando E., primary, Williams, Jeffery, primary, Donato, Elizabeth, primary, Batra, Surinder K., primary, Yeung, Cecilia C.S., primary, Grady, William M., primary, Koch, Meghan A., primary, Gottardo, Raphael, primary, and Salama, Nina R., primary

Published
2023
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9. FIGURE 4 from Single-cell Profiling Uncovers a Muc4-Expressing Metaplastic Gastric Cell Type Sustained by Helicobacter pylori-driven Inflammation

Author

O'Brien, Valerie P., primary, Kang, Yuqi, primary, Shenoy, Meera K., primary, Finak, Greg, primary, Young, William C., primary, Dubrulle, Julien, primary, Koch, Lisa, primary, Rodriguez Martinez, Armando E., primary, Williams, Jeffery, primary, Donato, Elizabeth, primary, Batra, Surinder K., primary, Yeung, Cecilia C.S., primary, Grady, William M., primary, Koch, Meghan A., primary, Gottardo, Raphael, primary, and Salama, Nina R., primary

Published
2023
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10. Figure S2 from Single-cell Profiling Uncovers a Muc4-Expressing Metaplastic Gastric Cell Type Sustained by Helicobacter pylori-driven Inflammation

Author

O'Brien, Valerie P., primary, Kang, Yuqi, primary, Shenoy, Meera K., primary, Finak, Greg, primary, Young, William C., primary, Dubrulle, Julien, primary, Koch, Lisa, primary, Rodriguez Martinez, Armando E., primary, Williams, Jeffery, primary, Donato, Elizabeth, primary, Batra, Surinder K., primary, Yeung, Cecilia C.S., primary, Grady, William M., primary, Koch, Meghan A., primary, Gottardo, Raphael, primary, and Salama, Nina R., primary

Published
2023
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11. FIGURE 3 from Single-cell Profiling Uncovers a Muc4-Expressing Metaplastic Gastric Cell Type Sustained by Helicobacter pylori-driven Inflammation

Author

O'Brien, Valerie P., primary, Kang, Yuqi, primary, Shenoy, Meera K., primary, Finak, Greg, primary, Young, William C., primary, Dubrulle, Julien, primary, Koch, Lisa, primary, Rodriguez Martinez, Armando E., primary, Williams, Jeffery, primary, Donato, Elizabeth, primary, Batra, Surinder K., primary, Yeung, Cecilia C.S., primary, Grady, William M., primary, Koch, Meghan A., primary, Gottardo, Raphael, primary, and Salama, Nina R., primary

Published
2023
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12. FIGURE 6 from Single-cell Profiling Uncovers a Muc4-Expressing Metaplastic Gastric Cell Type Sustained by Helicobacter pylori-driven Inflammation

Author

O'Brien, Valerie P., primary, Kang, Yuqi, primary, Shenoy, Meera K., primary, Finak, Greg, primary, Young, William C., primary, Dubrulle, Julien, primary, Koch, Lisa, primary, Rodriguez Martinez, Armando E., primary, Williams, Jeffery, primary, Donato, Elizabeth, primary, Batra, Surinder K., primary, Yeung, Cecilia C.S., primary, Grady, William M., primary, Koch, Meghan A., primary, Gottardo, Raphael, primary, and Salama, Nina R., primary

Published
2023
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13. Supplementary Methods from Single-cell Profiling Uncovers a Muc4-Expressing Metaplastic Gastric Cell Type Sustained by Helicobacter pylori-driven Inflammation

Author

O'Brien, Valerie P., primary, Kang, Yuqi, primary, Shenoy, Meera K., primary, Finak, Greg, primary, Young, William C., primary, Dubrulle, Julien, primary, Koch, Lisa, primary, Rodriguez Martinez, Armando E., primary, Williams, Jeffery, primary, Donato, Elizabeth, primary, Batra, Surinder K., primary, Yeung, Cecilia C.S., primary, Grady, William M., primary, Koch, Meghan A., primary, Gottardo, Raphael, primary, and Salama, Nina R., primary

Published
2023
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14. FIGURE 2 from Single-cell Profiling Uncovers a Muc4-Expressing Metaplastic Gastric Cell Type Sustained by Helicobacter pylori-driven Inflammation

Author

O'Brien, Valerie P., primary, Kang, Yuqi, primary, Shenoy, Meera K., primary, Finak, Greg, primary, Young, William C., primary, Dubrulle, Julien, primary, Koch, Lisa, primary, Rodriguez Martinez, Armando E., primary, Williams, Jeffery, primary, Donato, Elizabeth, primary, Batra, Surinder K., primary, Yeung, Cecilia C.S., primary, Grady, William M., primary, Koch, Meghan A., primary, Gottardo, Raphael, primary, and Salama, Nina R., primary

Published
2023
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15. FIGURE 5 from Single-cell Profiling Uncovers a Muc4-Expressing Metaplastic Gastric Cell Type Sustained by Helicobacter pylori-driven Inflammation

Author

O'Brien, Valerie P., primary, Kang, Yuqi, primary, Shenoy, Meera K., primary, Finak, Greg, primary, Young, William C., primary, Dubrulle, Julien, primary, Koch, Lisa, primary, Rodriguez Martinez, Armando E., primary, Williams, Jeffery, primary, Donato, Elizabeth, primary, Batra, Surinder K., primary, Yeung, Cecilia C.S., primary, Grady, William M., primary, Koch, Meghan A., primary, Gottardo, Raphael, primary, and Salama, Nina R., primary

Published
2023
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16. FIGURE 1 from Single-cell Profiling Uncovers a Muc4-Expressing Metaplastic Gastric Cell Type Sustained by Helicobacter pylori-driven Inflammation

Author

O'Brien, Valerie P., primary, Kang, Yuqi, primary, Shenoy, Meera K., primary, Finak, Greg, primary, Young, William C., primary, Dubrulle, Julien, primary, Koch, Lisa, primary, Rodriguez Martinez, Armando E., primary, Williams, Jeffery, primary, Donato, Elizabeth, primary, Batra, Surinder K., primary, Yeung, Cecilia C.S., primary, Grady, William M., primary, Koch, Meghan A., primary, Gottardo, Raphael, primary, and Salama, Nina R., primary

Published
2023
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17. Data from Single-cell Profiling Uncovers a Muc4-Expressing Metaplastic Gastric Cell Type Sustained by Helicobacter pylori-driven Inflammation

Author

O'Brien, Valerie P., primary, Kang, Yuqi, primary, Shenoy, Meera K., primary, Finak, Greg, primary, Young, William C., primary, Dubrulle, Julien, primary, Koch, Lisa, primary, Rodriguez Martinez, Armando E., primary, Williams, Jeffery, primary, Donato, Elizabeth, primary, Batra, Surinder K., primary, Yeung, Cecilia C.S., primary, Grady, William M., primary, Koch, Meghan A., primary, Gottardo, Raphael, primary, and Salama, Nina R., primary

Published
2023
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18. Data Exploration, Quality Control and Testing in Single-Cell qPCR-Based Gene Expression Experiments

Author

McDavid, Andrew, Finak, Greg, Chattopadyay, Pratip K., Dominguez, Maria, Lamoreaux, Laurie, Ma, Steven S., Roederer, Mario, and Gottardo, Raphael

Subjects
Statistics - Applications, Quantitative Biology - Quantitative Methods, 62F03, 92-02
Abstract

Cell populations are never truly homogeneous; individual cells exist in biochemical states that define functional differences between them. New technology based on microfluidic arrays combined with multiplexed quantitative polymerase chain reactions (qPCR) now enables high-throughput single-cell gene expression measurement, allowing assessment of cellular heterogeneity. However very little analytic tools have been developed specifically for the statistical and analytical challenges of single-cell qPCR data. We present a statistical framework for the exploration, quality control, and analysis of single-cell gene expression data from microfluidic arrays. We assess accuracy and within-sample heterogeneity of single-cell expression and develop quality control criteria to filter unreliable cell measurements. We propose a statistical model accounting for the fact that genes at the single-cell level can be on (and for which a continuous expression measure is recorded) or dichotomously off (and the recorded expression is zero). Based on this model, we derive a combined likelihood-ratio test for differential expression that incorporates both the discrete and continuous components. Using an experiment that examines treatment-specific changes in expression, we show that this combined test is more powerful than either the continuous or dichotomous component in isolation, or a t-test on the zero-inflated data. While developed for measurements from a specific platform (Fluidigm), these tools are generalizable to other multi-parametric measures over large numbers of events., Comment: 9 pages, 5 figures

Published
2012

19. Mixture Models for Single Cell Assays with Applications to Vaccine Studies

Author

Finak, Greg, McDavid, Andrew, Chattopadhyay, Pratip, Dominguez, Maria, De Rosa, Steve, Roederer, Mario, and Gottardo, Raphael

Subjects
Statistics - Applications, Statistics - Methodology, 62P10 (Primary) 62F15, 62-02, 92-08 (Secondary)
Abstract

In immunological studies, the characterization of small, functionally distinct cell subsets from blood and tissue is crucial to decipher system level biological changes. An increasing number of studies rely on assays that provide single-cell measurements of multiple genes and proteins from bulk cell samples. A common problem in the analysis of such data is to identify biomarkers (or combinations of thereof) that are differentially expressed between two biological conditions (e.g., before/after vaccination), where expression is defined as the proportion of cells expressing the biomarker or combination in the cell subset of interest. Here, we present a Bayesian hierarchical framework based on a beta-binomial mixture model for testing for differential biomarker expression using single-cell assays. Our model allows inference to be subject specific, as is typically required when accessing vaccine responses, while borrowing strength across subjects through common prior distributions. We propose two approaches for parameter estimation: an empirical-Bayes approach using an Expectation-Maximization algorithm and a fully Bayesian one based on a Markov chain Monte Carlo algorithm. We compare our method against frequentist approaches for single-cell assays including Fisher's exact test, a likelihood ratio test, and basic log-fold changes. Using several experimental assays measuring proteins or genes at the single-cell level and simulated data, we show that our method has higher sensitivity and specificity than alternative methods. Additional simulations show that our framework is also robust to model misspecification. Finally, we also demonstrate how our approach can be extended to testing multivariate differential expression across multiple biomarker combinations using a Dirichlet-multinomial model and illustrate this multivariate approach using single-cell gene expression data and simulations., Comment: 18 pages, 5 figures plus supplementary material

Published
2012

20. Figure S11 from Single-cell profiling uncovers a Muc4-expressing metaplastic gastric cell type sustained by Helicobacter pylori-driven inflammation

Author

O'Brien, Valerie Phoebe, primary, Kang, Yuqi, primary, Shenoy, Meera K, primary, Finak, Greg, primary, Young, William C, primary, Dubrulle, Julien, primary, Koch, Lisa, primary, Rodriguez Martinez, Armando E, primary, Williams, Jeffery, primary, Donato, Elizabeth, primary, Batra, Surinder K., primary, Yeung, Cecilia C.S., primary, Grady, William M, primary, Koch, Meghan A, primary, Gottardo, Raphael, primary, and Salama, Nina R., primary

Published
2023
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21. Data from Single-cell profiling uncovers a Muc4-expressing metaplastic gastric cell type sustained by Helicobacter pylori-driven inflammation

Author

O'Brien, Valerie Phoebe, primary, Kang, Yuqi, primary, Shenoy, Meera K, primary, Finak, Greg, primary, Young, William C, primary, Dubrulle, Julien, primary, Koch, Lisa, primary, Rodriguez Martinez, Armando E, primary, Williams, Jeffery, primary, Donato, Elizabeth, primary, Batra, Surinder K., primary, Yeung, Cecilia C.S., primary, Grady, William M, primary, Koch, Meghan A, primary, Gottardo, Raphael, primary, and Salama, Nina R., primary

Published
2023
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22. Table S8 from Single-cell profiling uncovers a Muc4-expressing metaplastic gastric cell type sustained by Helicobacter pylori-driven inflammation

Author

O'Brien, Valerie Phoebe, primary, Kang, Yuqi, primary, Shenoy, Meera K, primary, Finak, Greg, primary, Young, William C, primary, Dubrulle, Julien, primary, Koch, Lisa, primary, Rodriguez Martinez, Armando E, primary, Williams, Jeffery, primary, Donato, Elizabeth, primary, Batra, Surinder K., primary, Yeung, Cecilia C.S., primary, Grady, William M, primary, Koch, Meghan A, primary, Gottardo, Raphael, primary, and Salama, Nina R., primary

Published
2023
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23. Supplementary Methods from Single-cell profiling uncovers a Muc4-expressing metaplastic gastric cell type sustained by Helicobacter pylori-driven inflammation

Author

O'Brien, Valerie Phoebe, primary, Kang, Yuqi, primary, Shenoy, Meera K, primary, Finak, Greg, primary, Young, William C, primary, Dubrulle, Julien, primary, Koch, Lisa, primary, Rodriguez Martinez, Armando E, primary, Williams, Jeffery, primary, Donato, Elizabeth, primary, Batra, Surinder K., primary, Yeung, Cecilia C.S., primary, Grady, William M, primary, Koch, Meghan A, primary, Gottardo, Raphael, primary, and Salama, Nina R., primary

Published
2023
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24. Single-cell profiling uncovers a Muc4-expressing metaplastic gastric cell type sustained by Helicobacter pylori-driven inflammation

Author

O'Brien, Valerie Phoebe, primary, Kang, Yuqi, additional, Shenoy, Meera K, additional, Finak, Greg, additional, Young, William C, additional, Dubrulle, Julien, additional, Koch, Lisa, additional, Rodriguez Martinez, Armando E, additional, Williams, Jeffery, additional, Donato, Elizabeth, additional, Batra, Surinder K., additional, Yeung, Cecilia C.S., additional, Grady, William M, additional, Koch, Meghan A, additional, Gottardo, Raphael, additional, and Salama, Nina R., additional

Published
2023
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26. Higher T-Cell Responses Induced by DNA/rAd5 HIV-1 Preventive Vaccine Are Associated With Lower HIV-1 Infection Risk in an Efficacy Trial

Author

Janes, Holly E., Cohen, Kristen W., Frahm, Nicole, De Rosa, Stephen C., Sanchez, Brittany, Hural, John, Magaret, Craig A., Karuna, Shelly, Bentley, Carter, Gottardo, Raphael, Finak, Greg, Grove, Douglas, Shen, Mingchao, Graham, Barney S., Koup, Richard A., Mulligan, Mark J., Koblin, Beryl, Buchbinder, Susan P., Keefer, Michael C., Adams, Elizabeth, Anude, Chuka, Corey, Lawrence, Sobieszczyk, Magdalena, Hammer, Scott M., Gilbert, Peter B., and McElrath, M. Juliana

Published
2017

27. A first-in-human germline-targeting HIV nanoparticle vaccine induced broad and publicly targeted helper T cell responses

Author

Cohen, Kristen W., primary, De Rosa, Stephen C., additional, Fulp, William J., additional, deCamp, Allan C., additional, Fiore-Gartland, Andrew, additional, Mahoney, Celia R., additional, Furth, Sarah, additional, Donahue, Josh, additional, Whaley, Rachael E., additional, Ballweber-Fleming, Lamar, additional, Seese, Aaron, additional, Schwedhelm, Katharine, additional, Geraghty, Daniel, additional, Finak, Greg, additional, Menis, Sergey, additional, Leggat, David J., additional, Rahaman, Farhad, additional, Lombardo, Angela, additional, Borate, Bhavesh R., additional, Philiponis, Vincent, additional, Maenza, Janine, additional, Diemert, David, additional, Kolokythas, Orpheus, additional, Khati, Nadia, additional, Bethony, Jeffrey, additional, Hyrien, Ollivier, additional, Laufer, Dagna S., additional, Koup, Richard A., additional, McDermott, Adrian B., additional, Schief, William R., additional, and McElrath, M. Juliana, additional

Published
2023
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28. Human immunoglobulin gene allelic variation impacts germline-targeting vaccine priming

Author

deCamp, Allan, primary, Corcoran, Martin, additional, Fulp, William, additional, Willis, Jordan, additional, Cottrell, Christopher, additional, Bader, Daniel, additional, Kalyuzhniy, Oleksandr, additional, Leggat, David, additional, Cohen, Kristen, additional, Hyrien, Ollivier, additional, Menis, Sergey, additional, Finak, Greg, additional, Ballweber Fleming, Lamar, additional, Srikanth, Abhinaya, additional, Plyler, Jason, additional, Rahaman, Farhad, additional, Lombardo, Angela, additional, Philiponis, Vincent, additional, Whaley, Rachael, additional, Seese, Aaron, additional, Brand, Joshua, additional, Ruppel, Alexis, additional, Hoyland, Wesley, additional, Mahoney, Celia, additional, Cagigi, Alberto, additional, Taylor, Alison, additional, Brown, David, additional, Ambrozak, David, additional, Sincomb, Troy, additional, MULLEN, Tina-Marie, additional, Maenza, Janine, additional, Kolokythas, Orpheus, additional, Khati, Nadia, additional, Bethony, Jeffrey, additional, Roederer, Mario, additional, Diemert, David, additional, Koup, Richard, additional, Laufer, Dagna, additional, McElrath, M., additional, McDermott, Adrian, additional, Karlsson Hedestam, Gunilla, additional, and Schief, William, additional

Published
2023
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29. Human immunoglobulin gene allelic variation impacts germline-targeting vaccine priming

Author

deCamp, Allan C., Corcoran, Martin M., Fulp, William J., Willis, Jordan R., Cottrell, Christopher A., Bader, Daniel L.V., Kalyuzhniy, Oleksandr, Leggat, David J., Cohen, Kristen W., Hyrien, Ollivier, Menis, Sergey, Finak, Greg, Ballweber-Fleming, Lamar, Srikanth, Abhinaya, Plyler, Jason R., Rahaman, Farhad, Lombardo, Angela, Philiponis, Vincent, Whaley, Rachael E., Seese, Aaron, Brand, Joshua, Ruppel, Alexis M., Hoyland, Wesley, Mahoney, Celia R., Cagigi, Alberto, Taylor, Alison, Brown, David M., Ambrozak, David R., Sincomb, Troy, Mullen, Tina-Marie, Maenza, Janine, Kolokythas, Orpheus, Khati, Nadia, Bethony, Jeffrey, Roederer, Mario, Diemert, David, Koup, Richard A., Laufer, Dagna S., McElrath, Juliana M., McDermott, Adrian B., Hedestam, Gunilla B. Karlsson, and Schief, William R.

Subjects
Article
Abstract

Vaccine priming immunogens that activate germline precursors for broadly neutralizing antibodies (bnAbs) have promise for development of precision vaccines against major human pathogens. In a clinical trial of the eOD-GT8 60mer germline-targeting immunogen, higher frequencies of vaccine-induced VRC01-class bnAb-precursor B cells were observed in the high dose compared to the low dose group. Through immunoglobulin heavy chain variable (IGHV) genotyping, statistical modeling, quantification of IGHV1-2 allele usage and B cell frequencies in the naive repertoire for each trial participant, and antibody affinity analyses, we found that the difference between dose groups in VRC01-class response frequency was best explained by IGHV1-2 genotype rather than dose and was most likely due to differences in IGHV1-2 B cell frequencies for different genotypes. The results demonstrate the need to define population-level immunoglobulin allelic variations when designing germline-targeting immunogens and evaluating them in clinical trials.One-Sentence SummaryHuman genetic variation can modulate the strength of vaccine-induced broadly neutralizing antibody precursor B cell responses.

Published
2023

30. Single-cell profiling uncovers aMuc4-expressing metaplastic gastric cell type sustained byHelicobacter pylori-specific inflammation

Author

O’Brien, Valerie P., primary, Kang, Yuqi, additional, Shenoy, Meera K., additional, Finak, Greg, additional, Young, William C., additional, Dubrulle, Julien, additional, Koch, Lisa, additional, Rodriguez Martinez, Armando E., additional, Snow, Jazmine A., additional, Williams, Jeffery, additional, Donato, Elizabeth, additional, Batra, Surinder K., additional, Yeung, Cecilia C.S., additional, Bullman, Susan, additional, Koch, Meghan A., additional, Gottardo, Raphael, additional, and Salama, Nina R., additional

Published
2022
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31. Vaccination induces HIV broadly neutralizing antibody precursors in humans

Author

Leggat, David J., primary, Cohen, Kristen W., additional, Willis, Jordan R., additional, Fulp, William J., additional, deCamp, Allan C., additional, Kalyuzhniy, Oleksandr, additional, Cottrell, Christopher A., additional, Menis, Sergey, additional, Finak, Greg, additional, Ballweber-Fleming, Lamar, additional, Srikanth, Abhinaya, additional, Plyler, Jason R., additional, Schiffner, Torben, additional, Liguori, Alessia, additional, Rahaman, Farhad, additional, Lombardo, Angela, additional, Philiponis, Vincent, additional, Whaley, Rachael E., additional, Seese, Aaron, additional, Brand, Joshua, additional, Ruppel, Alexis M., additional, Hoyland, Wesley, additional, Yates, Nicole L., additional, Williams, LaTonya D., additional, Greene, Kelli, additional, Gao, Hongmei, additional, Mahoney, Celia R., additional, Corcoran, Martin M., additional, Cagigi, Alberto, additional, Taylor, Alison, additional, Brown, David M., additional, Ambrozak, David R., additional, Sincomb, Troy, additional, Hu, Xiaozhen, additional, Tingle, Ryan, additional, Georgeson, Erik, additional, Eskandarzadeh, Saman, additional, Alavi, Nushin, additional, Lu, Danny, additional, Mullen, Tina-Marie, additional, Kubitz, Michael, additional, Groschel, Bettina, additional, Maenza, Janine, additional, Kolokythas, Orpheus, additional, Khati, Nadia, additional, Bethony, Jeffrey, additional, Crotty, Shane, additional, Roederer, Mario, additional, Karlsson Hedestam, Gunilla B., additional, Tomaras, Georgia D., additional, Montefiori, David, additional, Diemert, David, additional, Koup, Richard A., additional, Laufer, Dagna S., additional, McElrath, M. Juliana, additional, McDermott, Adrian B., additional, and Schief, William R., additional

Published
2022
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33. Redistribution of CD8 + T cell subsets in metastatic renal cell carcinoma patients treated with anti‐PD ‐1 therapy

Author

De Biasi, Sara, primary, Guida, Annalisa, additional, Lo Tartaro, Domenico, additional, Fanelli, Martina, additional, Depenni, Roberta, additional, Dominici, Massimo, additional, Finak, Greg, additional, Porta, Camillo, additional, Paolini, Annamaria, additional, Borella, Rebecca, additional, Bertoldi, Carlo, additional, Cossarizza, Andrea, additional, Sabbatini, Roberto, additional, and Gibellini, Lara, additional

Published
2022
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35. Transcriptional correlates of malaria in RTS,S/AS01-vaccinated African children: a matched case–control study

Author

Moncunill, Gemma, primary, Carnes, Jason, additional, Chad Young, William, additional, Carpp, Lindsay, additional, De Rosa, Stephen, additional, Campo, Joseph J, additional, Nhabomba, Augusto, additional, Mpina, Maxmillian, additional, Jairoce, Chenjerai, additional, Finak, Greg, additional, Haas, Paige, additional, Muriel, Carl, additional, Van, Phu, additional, Sanz, Héctor, additional, Dutta, Sheetij, additional, Mordmüller, Benjamin, additional, Agnandji, Selidji T, additional, Díez-Padrisa, Núria, additional, Williams, Nana Aba, additional, Aponte, John J, additional, Valim, Clarissa, additional, Neafsey, Daniel E, additional, Daubenberger, Claudia, additional, McElrath, M Juliana, additional, Dobaño, Carlota, additional, Stuart, Ken, additional, and Gottardo, Raphael, additional

Published
2022
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37. Author response: Transcriptional correlates of malaria in RTS,S/AS01-vaccinated African children: a matched case–control study

Author

Moncunill, Gemma, primary, Carnes, Jason, additional, Chad Young, William, additional, Carpp, Lindsay, additional, De Rosa, Stephen, additional, Campo, Joseph J, additional, Nhabomba, Augusto, additional, Mpina, Maxmillian, additional, Jairoce, Chenjerai, additional, Finak, Greg, additional, Haas, Paige, additional, Muriel, Carl, additional, Van, Phu, additional, Sanz, Héctor, additional, Dutta, Sheetij, additional, Mordmüller, Benjamin, additional, Agnandji, Selidji T, additional, Díez-Padrisa, Núria, additional, Williams, Nana Aba, additional, Aponte, John J, additional, Valim, Clarissa, additional, Neafsey, Daniel E, additional, Daubenberger, Claudia, additional, McElrath, M Juliana, additional, Dobaño, Carlota, additional, Stuart, Ken, additional, and Gottardo, Raphael, additional

Published
2021
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38. Thinking Outside the Gate: Single-Cell Assessments in Multiple Dimensions

Author

Kvistborg, Pia, Gouttefangeas, Cécile, Aghaeepour, Nima, Cazaly, Angelica, Chattopadhyay, Pratip K., Chan, Cliburn, Eckl, Judith, Finak, Greg, Hadrup, Sine Reker, Maecker, Holden T., Maurer, Dominik, Mosmann, Tim, Qiu, Peng, Scheuermann, Richard H., Welters, Marij J.P., Ferrari, Guido, Brinkman, Ryan R., and Britten, Cedrik M.

Published
2015
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40. Redistribution of CD8+ T cell subsets in metastatic renal cell carcinoma patients treated with anti‐PD‐1 therapy.

Author

De Biasi, Sara, Guida, Annalisa, Lo Tartaro, Domenico, Fanelli, Martina, Depenni, Roberta, Dominici, Massimo, Finak, Greg, Porta, Camillo, Paolini, Annamaria, Borella, Rebecca, Bertoldi, Carlo, Cossarizza, Andrea, Sabbatini, Roberto, and Gibellini, Lara

Abstract

Renal‐cell carcinoma (RCC) is responsible for the majority of tumors arising from the kidney parenchyma. Although a progressive improvement in median overall survival has been observed after the introduction of anti‐PD‐1 therapy, many patients do not benefit from this treatment. Therefore, we have investigated T cell dynamics to find immune modification induced by anti‐PD‐1 therapy. Here, we show that, after therapy, RCC patients (5 responders and 14 nonresponders) are characterized by a redistribution of different subsets across the memory T cell compartment. [ABSTRACT FROM AUTHOR]

Published
2022
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41. HIV Skews a Balanced Mtb-Specific Th17 Response in Latent Tuberculosis Subjects to a Pro-inflammatory Profile Independent of Viral Load:HIV alters the nature of the Mtb-specific Th17 response

Author

Rakshit, Srabanti, Hingankar, Nitin, Alampalli, Shuba Varshini, Adiga, Vasista, Sundararaj, Bharath K., Sahoo, Pravat Nalini, Finak, Greg, Uday Kumar J, Anto Jesuraj, Dhar, Chirag, D'Souza, George, Virkar, Rashmi Govind, Ghate, Manisha, Thakar, Madhuri R., Paranjape, Ramesh S., De Rosa, Stephen C., Ottenhoff, Tom H.M., and Vyakarnam, Annapurna

Subjects
HIV DNA/RNA, tuberculosis, Long-term-non-progressors, HIV, Th17, ATT, CD8+ T cells, ART, CD4+ T cells, pro-inflammatory
Abstract

This study provides insight on how HIV may drive tuberculosis (TB). Rakshit et al. demonstrate that HIV infection of latent TB subjects profoundly alters specific immune subsets implicated in anti-TB immunity, which is independent of cellular viral burden or secretion of antiviral chemokines.

Published
2020

43. HIV Skews a Balanced Mtb-Specific Th17 Response in Latent Tuberculosis Subjects to a Pro-inflammatory Profile Independent of Viral Load

Author

Rakshit, Srabanti, primary, Hingankar, Nitin, additional, Alampalli, Shuba Varshini, additional, Adiga, Vasista, additional, Sundararaj, Bharath K., additional, Sahoo, Pravat Nalini, additional, Finak, Greg, additional, Uday Kumar J, Anto Jesuraj, additional, Dhar, Chirag, additional, D’Souza, George, additional, Virkar, Rashmi Govind, additional, Ghate, Manisha, additional, Thakar, Madhuri R., additional, Paranjape, Ramesh S., additional, De Rosa, Stephen C., additional, Ottenhoff, Tom H.M., additional, and Vyakarnam, Annapurna, additional

Published
2020
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47. BCG revaccination boosts adaptive polyfunctional Th1/Th17 and innate effectors in IGRA+ and IGRA– Indian adults

Author

Rakshit, Srabanti, primary, Ahmed, Asma, additional, Adiga, Vasista, additional, Sundararaj, Bharath K., additional, Sahoo, Pravat Nalini, additional, Kenneth, John, additional, D’Souza, George, additional, Bonam, Wesley, additional, Johnson, Christina, additional, Franken, Kees L.M.C., additional, Ottenhoff, Tom H.M., additional, Finak, Greg, additional, Gottardo, Raphael, additional, Stuart, Kenneth D., additional, De Rosa, Stephen C., additional, McElrath, M. Juliana, additional, and Vyakarnam, Annapurna, additional

Published
2019
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48. QUAliFiER: An automated pipeline for quality assessment of gated flow cytometry data

Author

Finak Greg, Jiang Wenxin, Pardo Jorge, Asare Adam, and Gottardo Raphael

Subjects
Flow cytometry, Quality assessment, BioConductor package, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background Effective quality assessment is an important part of any high-throughput flow cytometry data analysis pipeline, especially when considering the complex designs of the typical flow experiments applied in clinical trials. Technical issues like instrument variation, problematic antibody staining, or reagent lot changes can lead to biases in the extracted cell subpopulation statistics. These biases can manifest themselves in non–obvious ways that can be difficult to detect without leveraging information about the study design or other experimental metadata. Consequently, a systematic and integrated approach to quality assessment of flow cytometry data is necessary to effectively identify technical errors that impact multiple samples over time. Gated cell populations and their statistics must be monitored within the context of the experimental run, assay, and the overall study. Results We have developed two new packages, flowWorkspace and QUAliFiER to construct a pipeline for quality assessment of gated flow cytometry data. flowWorkspace makes manually gated data accessible to BioConductor’s computational flow tools by importing pre–processed and gated data from the widely used manual gating tool, FlowJo (Tree Star Inc, Ashland OR). The QUAliFiER package takes advantage of the manual gates to perform an extensive series of statistical quality assessment checks on the gated cell sub–populations while taking into account the structure of the data and the study design to monitor the consistency of population statistics across staining panels, subject, aliquots, channels, or other experimental variables. QUAliFiER implements SVG–based interactive visualization methods, allowing investigators to examine quality assessment results across different views of the data, and it has a flexible interface allowing users to tailor quality checks and outlier detection routines to suit their data analysis needs. Conclusion We present a pipeline constructed from two new R packages for importing manually gated flow cytometry data and performing flexible and robust quality assessment checks. The pipeline addresses the increasing demand for tools capable of performing quality checks on large flow data sets generated in typical clinical trials. The QUAliFiER tool objectively, efficiently, and reproducibly identifies outlier samples in an automated manner by monitoring cell population statistics from gated or ungated flow data conditioned on experiment–level metadata.

Published
2012
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49. New interpretable machine learning method for single-cell data reveals correlates of clinical response to cancer immunotherapy

Author

Greene, Evan, primary, Finak, Greg, additional, D’Amico, Leonard A., additional, Bhardwaj, Nina, additional, Church, Candice D., additional, Morishima, Chihiro, additional, Ramchurren, Nirasha, additional, Taube, Janis M., additional, Nghiem, Paul T., additional, Cheever, Martin A., additional, Fling, Steven P., additional, and Gottardo, Raphael, additional

Published
2019
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