title: Inference of immune cell composition on the expression profiles of mouse tissue.
abstract: Mice are some of the widely used experimental animal models for studying human diseases. Defining the compositions of immune cell populations in various tissues from experimental mouse models is critical to understanding the involvement of immune responses in various physiological and patho-physiological conditions. However, non-lymphoid tissues are normally composed of vast and diverse cellular components, which make it difficult to quantify the relative proportions of immune cell types. Here we report the development of a computational algorithm, ImmuCC, to infer the relative compositions of 25 immune cell types in mouse tissues using microarray-based mRNA expression data. The ImmuCC algorithm showed good performance and robustness in many simulated datasets. Remarkable concordances were observed when ImmuCC was used on three public datasets, one including enriched immune cells, one with normal single positive T cells, and one with leukemia cell samples. To validate the performance of ImmuCC objectively, thorough cross-comparison of ImmuCC predicted compositions and flow cytometry results was done with in-house generated datasets collected from four distinct mouse lymphoid tissues and three different types of tumor tissues. The good correlation and biologically meaningful results demonstrate the broad utility of ImmuCC for assessing immune cell composition in diverse mouse tissues under various conditions.
authors.affiliation: Center for Systems Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences &Peking Union Medical College, Beijing 100005, Suzhou Institute of Systems Medicine, Suzhou, Jiangsu 215123, China.
authors.forename: Ziyi
authors.initials: Z
authors.lastname: Chen
authors.affiliation: Center for Systems Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences &Peking Union Medical College, Beijing 100005, Suzhou Institute of Systems Medicine, Suzhou, Jiangsu 215123, China.
authors.forename: Anfei
authors.initials: A
authors.lastname: Huang
authors.affiliation: Center for Systems Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences &Peking Union Medical College, Beijing 100005, Suzhou Institute of Systems Medicine, Suzhou, Jiangsu 215123, China.
authors.forename: Jiya
authors.initials: J
authors.lastname: Sun
authors.affiliation: Center for Systems Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences &Peking Union Medical College, Beijing 100005, Suzhou Institute of Systems Medicine, Suzhou, Jiangsu 215123, China.
authors.forename: Taijiao
authors.initials: T
authors.lastname: Jiang
authors.affiliation: Center for Systems Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences &Peking Union Medical College, Beijing 100005, Suzhou Institute of Systems Medicine, Suzhou, Jiangsu 215123, China.
authors.forename: F Xiao-Feng
authors.initials: FX
authors.lastname: Qin
authors.affiliation: Center for Systems Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences &Peking Union Medical College, Beijing 100005, Suzhou Institute of Systems Medicine, Suzhou, Jiangsu 215123, China.
authors.forename: Aiping
authors.initials: A
authors.lastname: Wu
mesh_terms: D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D030541:Databases, Genetic; D005434:Flow Cytometry; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D007938:Leukemia / Q000235:genetics; D008214:Lymphocytes / Q000378:metabolism*; D051379:Mice; D018448:Models, Immunological; D009928:Organ Specificity / Q000235:genetics*