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Yanyan Han

Bio: Yanyan Han is an academic researcher from Jinan University. The author has contributed to research in topics: Cancer & Antigen. The author has an hindex of 1, co-authored 2 publications receiving 8173 citations.
Topics: Cancer, Antigen, Antibody, T cell, Tumor antigen

Papers
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Journal ArticleDOI
TL;DR: An R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters and can be easily extended to other species and ontologies is presented.
Abstract: Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters The analysis module and visualization module were combined into a reusable workflow Currently, clusterProfiler supports three species, including humans, mice, and yeast Methods provided in this package can be easily extended to other species and ontologies The clusterProfiler package is released under Artistic-20 License within Bioconductor project The source code and vignette are freely available at http://bioconductororg/packages/release/bioc/html/clusterProfilerhtml

16,644 citations

Book ChapterDOI
Yanyan Han1, Qing-Yu He1
01 Jan 2013
TL;DR: Cancer immunotherapies discussed in this chapter refer to therapeutic monoclonal antibodies, adoptive T cell therapy, and therapeutic vaccines to overcome the immune suppression environment of cancer patients as well as the unexpected side effects.
Abstract: Cancer is still one of the leading causes of death at present. The development of immunotherapies based on the identification of tumor antigens provides a promising option of cancer therapy. Tumor antigens are the targets that could be recognized by T cells or antibodies and thus elicit immune response in cancer patients. Since tumor antigens are exclusively expressed or over expressed on tumor cells, the immune responses against tumor antigens would only destroy tumor cells but not normal cells. Cancer immunotherapies discussed in this chapter refer to therapeutic monoclonal antibodies, adoptive T cell therapy, and therapeutic vaccines. With the superiority of high specificity, cancer immunotherapies may act as a personalized treatment against cancer to overcome the immune suppression environment of cancer patients as well as the unexpected side effects.

Cited by
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Journal ArticleDOI
TL;DR: An updated version of the popular Bioconductor package, clusterProfiler 4.0, which provides a universal interface for functional enrichment analysis in thousands of organisms based on internally supported ontologies and pathways as well as annotation data provided by users or derived from online databases.
Abstract: Functional enrichment analysis is pivotal for interpreting high-throughput omics data in life science. It is crucial for this type of tool to use the latest annotation databases for as many organisms as possible. To meet these requirements, we present here an updated version of our popular Bioconductor package, clusterProfiler 4.0. This package has been enhanced considerably compared with its original version published 9 years ago. The new version provides a universal interface for functional enrichment analysis in thousands of organisms based on internally supported ontologies and pathways as well as annotation data provided by users or derived from online databases. It also extends the dplyr and ggplot2 packages to offer tidy interfaces for data operation and visualization. Other new features include gene set enrichment analysis and comparison of enrichment results from multiple gene lists. We anticipate that clusterProfiler 4.0 will be applied to a wide range of scenarios across diverse organisms.

2,448 citations

Journal ArticleDOI
TL;DR: UNLABELLED ChIPseeker is an R package for annotating ChIP-seq data analysis and provides functions to visualize ChIP peaks coverage over chromosomes and profiles of peaks binding to TSS regions.
Abstract: Summary: ChIPseeker is an R package for annotating ChIP-seq data analysis. It supports annotating ChIP peaks and provides functions to visualize ChIP peaks coverage over chromosomes and profiles of peaks binding to TSS regions. Comparison of ChIP peak profiles and annotation are also supported. Moreover, it supports evaluating significant overlap among ChIP-seq datasets. Currently, ChIPseeker contains 15 000 bed file information from GEO database. These datasets can be downloaded and compare with user’s own data to explore significant overlap datasets for inferring co-regulation or transcription factor complex for further investigation. Availability and implementation: ChIPseeker is released under Artistic-2.0 License. The source code and documents are freely available through Bioconductor (http://www.bioconductor.org/pack

2,130 citations

Journal ArticleDOI
TL;DR: Single-cell transcriptome and T cell receptor analysis of bronchoalveolar lavage fluid suggests enrichment of proinflammatory macrophages in patients with severe COVID-19 and the presence of clonally expanded CD8 + T cells in Patients with moderate CO VID-19.
Abstract: Respiratory immune characteristics associated with Coronavirus Disease 2019 (COVID-19) severity are currently unclear. We characterized bronchoalveolar lavage fluid immune cells from patients with varying severity of COVID-19 and from healthy people by using single-cell RNA sequencing. Proinflammatory monocyte-derived macrophages were abundant in the bronchoalveolar lavage fluid from patients with severe COVID-9. Moderate cases were characterized by the presence of highly clonally expanded CD8+ T cells. This atlas of the bronchoalveolar immune microenvironment suggests potential mechanisms underlying pathogenesis and recovery in COVID-19.

1,918 citations

Journal ArticleDOI
TL;DR: Reactome is a manually curated pathway annotation database for unveiling high-order biological pathways from high-throughput data and ReactomePA is an R/Bioconductor package providing enrichment analyses, including hypergeometric test and gene set enrichment analyses.
Abstract: Reactome is a manually curated pathway annotation database for unveiling high-order biological pathways from high-throughput data. ReactomePA is an R/Bioconductor package providing enrichment analyses, including hypergeometric test and gene set enrichment analyses. A functional analysis can be applied to the genomic coordination obtained from a sequencing experiment to analyze the functional significance of genomic loci including cis-regulatory elements and non-coding regions. Comparison among different experiments is also supported. Moreover, ReactomePA provides several visualization functions to produce highly customizable, publication-quality figures. The source code and documents of ReactomePA are freely available through Bioconductor (http://www.bioconductor.org/packages/ReactomePA).

1,048 citations