HTSanalyzeR: an R/Bioconductor package for integrated network analysis of high-throughput screens

Wang, Xin; Terfve, Camille; Rose, John C.; Markowetz, Florian

doi:10.1093/bioinformatics/btr028

Cited by 123 publications

(103 citation statements)

References 13 publications

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“…were used. To test msigDB pathway enrichment, the R packages HTSanalyzeR (Wang et al, 2011), GSEABase (Morgan M, Falcon S and Gentleman R. GSEABase: Gene set enrichment data structures and methods. R package version 1.32.0., and gage (Luo et al, 2009) were used.…”

Section: Stars Methodsmentioning

confidence: 99%

Analysis of Transcriptional Variability in a Large Human iPSC Library Reveals Genetic and Non-genetic Determinants of Heterogeneity

et al. 2017

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SUMMARY Variability in induced pluripotent stem cell (iPSC) lines remains a concern for disease modeling and regenerative medicine. We have used RNA sequencing analysis and linear mixed models to examine the sources of gene expression variability in 317 human iPSC lines from 101 individuals. We found that ~50% of genome-wide expression variability is explained by variation across individuals and identified a set of expression quantitative trait loci that contribute to this variation. These analyses coupled with allele specific expression show that iPSCs retain a donor specific gene expression pattern. Network, pathway and key driver analyses showed that Polycomb targets contribute significantly to the non-genetic variability seen within and across individuals, highlighting this chromatin regulator as a likely source of reprogramming-based variability. Our findings therefore shed light on variation between iPSC lines and illustrate the potential for our dataset and other similar large-scale analyses to identify underlying drivers relevant to iPSC applications.

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Section: Stars Methodsmentioning

confidence: 99%

Analysis of Transcriptional Variability in a Large Human iPSC Library Reveals Genetic and Non-genetic Determinants of Heterogeneity

et al. 2017

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“…Gene set enrichment analysis (48) was performed using the HTSAnalyzeR package (49) using a Benjamini & Hochberg corrected p-value cut off of 0.05 to define significant gene sets. Two gene set collections from MSigDB were assessed: (i) curated canonical pathways (c2) to determine whether immune-related gene sets were differentially expressed and (ii) immunologic signatures (c7) reflecting genetic perturbations or differences in cell states (21).…”

Section: Methodsmentioning

confidence: 99%

Immune Escape in Breast Cancer DuringIn Situto Invasive Carcinoma Transition

et al. 2017

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To investigate immune escape during breast tumor progression, we analyzed the composition of leukocytes in normal breast tissues, ductal carcinoma in situ (DCIS), and invasive ductal carcinomas (IDC). We found significant tissue and tumor subtype-specific differences in multiple cell types including T cells and neutrophils. Gene expression profiling of CD45+CD3+ T cells demonstrated a decrease in CD8+ signatures in IDCs. Immunofluorescence analysis showed fewer activated GZMB+CD8+ T cells in IDC than in DCIS, including in matched DCIS recurrent IDC. TCR clonotype diversity was significantly higher in DCIS than in IDCs. Immune checkpoint protein TIGIT expressing T cells were more frequent in DCIS whereas high PD-L1 expression and amplification of CD274 (encoding PD-L1) was only detected in triple negative IDCs. Co-amplification of 17q12 chemokine cluster with ERBB2 subdivided HER2+ breast tumors into immunologically and clinically distinct subtypes. Our results show co-evolution of cancer cells and the immune microenvironment during tumor progression.

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“…R language was used for performing statistical analysis and graphical work . The HTSAnalyzeR package was used to perform gene ontology and pathway analysis . Kaplan‐Meier plots were generated with the survival package, and the log‐rank test was used to compare survival curves.…”

Section: Methodsmentioning

confidence: 99%

Genetic and clinical characterization of B7‐H3 (CD276) expression and epigenetic regulation in diffuse brain glioma

Wang

Zhang

et al. 2018

Cancer Science

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Gliomas are the most common malignant tumors of the brain. Immune checkpoints have been increasingly emphasized as targets for treating malignant tumors. B7‐H3 has been identified as an immune checkpoint that shows potential value for targeting therapies. We set out to characterize the expression pattern and biological function of B7‐H3 in brain gliomas using high‐throughput data obtained from the Chinese Glioma Genome Atlas (CGGA) and the Cancer Genome Atlas (TCGA) projects. B7‐H3 was upregulated more in higher‐grade gliomas than that in lower‐grade gliomas in both CGGA and TCGA datasets. Isocitrate dehydrogenase (IDH) mutation seemed to exert significant influence on B7‐H3 expression in gliomas but led to quite different results between grade II gliomas and higher‐grade gliomas. In addition to IDH, methylation of B7‐H3 promoter and microRNA‐29 family also showed a potential regulatory effect on B7‐H3 expression. Gene ontology analysis revealed that B7‐H3 was associated with mitotic cell cycle, cell proliferation and immune response. Further investigation suggested that B7‐H3 was mostly involved in the Toll‐like receptor signaling pathway. Survival analysis indicated that B7‐H3 was an independent unfavorable prognosticator for glioma patients in both CGGA and TCGA datasets. B7‐H3 expression is regulated by multiple mechanisms and is potentially involved in the T‐cell receptor signaling pathway. Higher B7‐H3 expression indicates a worse prognosis for glioma patients, which warrants further research into the development of inhibitors for targeting this immune checkpoint, but we still need to be cautious about immune checkpoint inhibition for central nervous system tumors.

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HTSanalyzeR: an R/Bioconductor package for integrated network analysis of high-throughput screens

Cited by 123 publications

References 13 publications

Analysis of Transcriptional Variability in a Large Human iPSC Library Reveals Genetic and Non-genetic Determinants of Heterogeneity

Analysis of Transcriptional Variability in a Large Human iPSC Library Reveals Genetic and Non-genetic Determinants of Heterogeneity

Immune Escape in Breast Cancer DuringIn Situto Invasive Carcinoma Transition

Genetic and clinical characterization of B7‐H3 (CD276) expression and epigenetic regulation in diffuse brain glioma

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