@article{Beyrend2018,
author = {Beyrend, Guillaume and Stam, Koen and H{\"{o}}llt, Thomas and Ossendrop, Ferry and Arens, Ramon},
journal = {Manuscript submitted for publication},
title = {{Cytofast: An R-based roadmap for quantitative analysis of flow and mass cytometry data to discover immune cell subsets and correlations between groups.}},
year = {2018}
}
@article{Goeman2004,
abstract = {MOTIVATION: This paper presents a global test to be used for the analysis of microarray data. Using this test it can be determined whether the global expression pattern of a group of genes is significantly related to some clinical outcome of interest. Groups of genes may be any size from a single gene to all genes on the chip (e.g. known pathways, specific areas of the genome or clusters from a cluster analysis). RESULT: The test allows groups of genes of different size to be compared, because the test gives one p-value for the group, not a p-value for each gene. Researchers can use the test to investigate hypotheses based on theory or past research or to mine gene ontology databases for interesting pathways. Multiple testing problems do not occur unless many groups are tested. Special attention is given to visualizations of the test result, focussing on the associations between samples and showing the impact of individual genes on the test result. AVAILABILITY: An R-package globaltest is available from http://www.bioconductor.org},
author = {Goeman, Jelle J. and {Van de Geer}, Sara and {De Kort}, Floor and van Houwellingen, Hans C.},
doi = {10.1093/bioinformatics/btg382},
file = {:R$\backslash$:/Para-CIH/CIH Group member folders/Koen/Articles/Goeman et al (2004) global test for groups of genes.pdf:pdf},
isbn = {1367-4803$\backslash$r1460-2059},
issn = {13674803},
journal = {Bioinformatics},
number = {1},
pages = {93--99},
pmid = {14693814},
title = {{A global test for groups of genes: testing association with a clinical outcome}},
volume = {20},
year = {2004}
}
@article{Spitzer2017,
abstract = {Immune responses involve coordination across cell types and tissues. However, studies in cancer immunotherapy have focused heavily on local immune responses in the tumor microenvironment. To investigate immune activity more broadly, we performed an organism-wide study in genetically-engineered cancer models using mass cytometry. We analyzed immune responses in several tissues after immunotherapy by developing intuitive models for visualizing single-cell data with statistical inference. Immune activation was evident in the tumor and systemically shortly after effective therapy was administered. However, during tumor rejection, only peripheral immune cells sustained their proliferation. This systemic response was coordinated across tissues and required for tumor eradication in several immunotherapy models. An emergent population of peripheral CD4 T cells conferred protection against new tumors and was significantly expanded in patients responding to immunotherapy. These studies demonstrate the critical impact of systemic immune responses that drive tumor rejection.},
author = {Spitzer, Matthew H and Carmi, Yaron and Reticker-Flynn, Nathan E and Kwek, Serena S and Madhireddy, Deepthi and Martins, Maria M and Gherardini, Pier Federico and Prestwood, Tyler R and Chabon, Jonathan and Bendall, Sean C and Fong, Lawrence and Nolan, Garry P and Engleman, Edgar G},
doi = {10.1016/j.cell.2016.12.022},
file = {:R$\backslash$:/Para-CIH/CIH Group member folders/Koen/Articles/Spitzer et al (2017) Systemic Immunity is required for effective cancer immunotherapy.pdf:pdf},
journal = {Cell},
number = {168(3)},
pages = {487--502},
title = {{Systemic Immunity is Required for Effective Cancer Immunotherapy HHS Public Access}},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5312823/pdf/nihms842747.pdf},
volume = {26},
year = {2017}
}
