Heatmap is a widely used statistical visualization method on matrix‐like data to reveal similar patterns shared by subsets of rows and columns. In the R programming language, there are many packages ...that make heatmaps. Among them, the ComplexHeatmap package provides the richest toolset for constructing highly customizable heatmaps. ComplexHeatmap can easily establish connections between multisource information by automatically concatenating and adjusting a list of heatmaps as well as complex annotations, which makes it widely applied in data analysis in many fields, especially in bioinformatics, to find hidden structures in the data. In this article, we give a comprehensive introduction to the current state of ComplexHeatmap, including its modular design, its rich functionalities, and its broad applications.
Complex heatmap is a powerful visualization method for revealing associations between multiple sources of information. We have developed an R package named ComplexHeatmap that provides comprehensive functionalities for heatmap visualization. It has been widely used in the bioinformatics community. We give a comprehensive introduction to the current state of ComplexHeatmap in this article.
Highlights
Complex heatmap is a powerful visualization method for revealing associations between multiple sources of information.
We have developed an R package named ComplexHeatmap that provides comprehensive functionalities for heatmap visualization. It has been widely used in the bioinformatics community.
We give a comprehensive introduction to the current state of ComplexHeatmap in this article.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Parallel heatmaps with carefully designed annotation graphics are powerful for efficient visualization of patterns and relationships among high dimensional genomic data. Here we present the ...ComplexHeatmap package that provides rich functionalities for customizing heatmaps, arranging multiple parallel heatmaps and including user-defined annotation graphics. We demonstrate the power of ComplexHeatmap to easily reveal patterns and correlations among multiple sources of information with four real-world datasets.
The ComplexHeatmap package and documentation are freely available from the Bioconductor project: http://www.bioconductor.org/packages/devel/bioc/html/ComplexHeatmap.html
m.schlesner@dkfz.de
Supplementary data are available at Bioinformatics online.
Functional enrichment analysis or gene set enrichment analysis is a basic bioinformatics method that evaluates the biological importance of a list of genes of interest. However, it may produce a long ...list of significant terms with highly redundant information that is difficult to summarize. Current tools to simplify enrichment results by clustering them into groups either still produce redundancy between clusters or do not retain consistent term similarities within clusters. We propose a new method named binary cut for clustering similarity matrices of functional terms. Through comprehensive benchmarks on both simulated and real-world datasets, we demonstrated that binary cut could efficiently cluster functional terms into groups where terms showed consistent similarities within groups and were mutually exclusive between groups. We compared binary cut clustering on the similarity matrices obtained from different similarity measures and found that semantic similarity worked well with binary cut, while similarity matrices based on gene overlap showed less consistent patterns. We implemented the binary cut algorithm in the R package simplifyEnrichment, which additionally provides functionalities for visualizing, summarizing, and comparing the clustering. The simplifyEnrichment package and the documentation are available at https://bioconductor.org/packages/simplifyEnrichment/.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In chronic hepatitis C virus (HCV) infection, exhausted HCV-specific CD8
T cells comprise memory-like and terminally exhausted subsets. However, little is known about the molecular profile and fate ...of these two subsets after the elimination of chronic antigen stimulation by direct-acting antiviral (DAA) therapy. Here, we report a progenitor-progeny relationship between memory-like and terminally exhausted HCV-specific CD8
T cells via an intermediate subset. Single-cell transcriptomics implicated that memory-like cells are maintained and terminally exhausted cells are lost after DAA-mediated cure, resulting in a memory polarization of the overall HCV-specific CD8
T cell response. However, an exhausted core signature of memory-like CD8
T cells was still detectable, including, to a smaller extent, in HCV-specific CD8
T cells targeting variant epitopes. These results identify a molecular signature of T cell exhaustion that is maintained as a chronic scar in HCV-specific CD8
T cells even after the cessation of chronic antigen stimulation.
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GEOZS, IJS, IMTLJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK, ZAGLJ
Glioblastoma frequently exhibits therapy-associated subtype transitions to mesenchymal phenotypes with adverse prognosis. Here, we perform multi-omic profiling of 60 glioblastoma primary tumours and ...use orthogonal analysis of chromatin and RNA-derived gene regulatory networks to identify 38 subtype master regulators, whose cell population-specific activities we further map in published single-cell RNA sequencing data. These analyses identify the oligodendrocyte precursor marker and chromatin modifier SOX10 as a master regulator in RTK I-subtype tumours. In vitro functional studies demonstrate that SOX10 loss causes a subtype switch analogous to the proneural-mesenchymal transition observed in patients at the transcriptomic, epigenetic and phenotypic levels. SOX10 repression in an in vivo syngeneic graft glioblastoma mouse model results in increased tumour invasion, immune cell infiltration and significantly reduced survival, reminiscent of progressive human glioblastoma. These results identify SOX10 as a bona fide master regulator of the RTK I subtype, with both tumour cell-intrinsic and microenvironmental effects.
We studied how intratumoral genetic heterogeneity shapes tumor growth and therapy response for isocitrate dehydrogenase (IDH)-wild-type glioblastoma, a rapidly regrowing tumor. We inferred the ...evolutionary trajectories of matched pairs of primary and relapsed tumors based on deep whole-genome-sequencing data. This analysis suggests both a distant origin of de novo glioblastoma, up to 7 years before diagnosis, and a common path of early tumorigenesis, with one or more of chromosome 7 gain, 9p loss, or 10 loss, at tumor initiation. TERT promoter mutations often occurred later as a prerequisite for rapid growth. In contrast to this common early path, relapsed tumors acquired no stereotypical pattern of mutations and typically regrew from oligoclonal origins, suggesting sparse selective pressure by therapeutic measures.
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•We inferred evolutionary trajectories of pairs of primary/relapsed glioblastomas•Chromosome 7 gain, 9p loss, or 10 loss commonly occurred at tumor initiation•TERT promoter mutations often occurred later as a prerequisite for rapid growth•Relapsed tumors typically regrew from oligoclonal origins
By analyzing 21 paired primary and locally relapsed IDH-wild-type glioblastomas (GBM), Körber et al. show that most GBM initiate by gains and losses of specific chromosomes; TERT promoter mutations often occur later as a prerequisite for rapid growth, and relapsed GBM acquire few stereotypical mutations.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Incomplete understanding of the metastatic process hinders personalized therapy. Here we report the most comprehensive whole-genome study of colorectal metastases vs. matched primary tumors. 65% of ...somatic mutations originate from a common progenitor, with 15% being tumor- and 19% metastasis-specific, implicating a higher mutation rate in metastases. Tumor- and metastasis-specific mutations harbor elevated levels of BRCAness. We confirm multistage progression with new components ARHGEF7/ARHGEF33. Recurrently mutated non-coding elements include ncRNAs RP11-594N15.3, AC010091, SNHG14, 3' UTRs of FOXP2, DACH2, TRPM3, XKR4, ANO5, CBL, CBLB, the latter four potentially dual protagonists in metastasis and efferocytosis-/PD-L1 mediated immunosuppression. Actionable metastasis-specific lesions include FAT1, FGF1, BRCA2, KDR, and AKT2-, AKT3-, and PDGFRA-3' UTRs. Metastasis specific mutations are enriched in PI3K-Akt signaling, cell adhesion, ECM and hepatic stellate activation genes, suggesting genetic programs for site-specific colonization. Our results put forward hypotheses on tumor and metastasis evolution, and evidence for metastasis-specific events relevant for personalized therapy.
The R package ecosystem is expanding fast and dependencies among packages are becoming more complex in the ecosystem. In this study, we explored the package dependencies from a new aspect. We applied ...a new metric named “dependency heaviness” which measures the number of additional strong dependencies that a package uniquely contributes to its child or downstream packages. We systematically studied how the dependency heaviness spreads from parent to child packages, and how it further spreads to remote downstream packages in the CRAN/Bioconductor ecosystem. We extracted top packages and key paths that majorly transmit heavy dependencies in the ecosystem. Additionally, the dependency heaviness analysis on the ecosystem has been implemented as a web-based database that provides comprehensive tools for querying dependencies of individual R packages.
•A new metric “dependency heaviness” was applied to the R package ecosystem.•Local and remote dependency transmission was extensively studied.•The complete dependency analysis has been implemented as a web-based database.•The heaviness analysis will help developers create more robust software.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Chemotherapy (CTX) remains the standard of care for most aggressive tumours, including breast cancer (BC). In BC chemotherapeutic regimens, the maximum tolerated dose of cytotoxic drugs is ...administered at regular intervals, and cancer cells can re‐grow or adapt during the resting periods between cycles. The impact of the tumour microenvironment on the fate of cancer cells after CTX remains poorly understood. Here, we show that paracrine signalling from CTX‐treated cancer cells to stromal fibroblasts can drive cancer cell recovery after cytotoxic drug withdrawal. Interferon β1 (IFNβ1) secreted by cancer cells following treatment with high doses of CTX instigates the acquisition of an anti‐viral state in stromal fibroblasts. This state is associated with an expression pattern here referred to as interferon signature (IFNS), which encompasses several interferon‐stimulated genes (ISGs), including numerous pro‐inflammatory cytokine genes. This crosstalk is an important driver of the expansion of BC cells after CTX, and IFNβ1 blockade in tumour cells abrogated their fibroblast‐dependent recovery potential. Analysis of human breast carcinomas supported a link between CTX‐induced IFNS in tumour stroma and poor response to CTX treatment. First, IFNβ1 expression in human breast carcinomas was found to inversely correlate with recurrence free survival (RFS). Second, using laser capture microdissection data sets, we show a higher expression of IFNS in the stromal tumour compartment compared to the epithelial one and this signature was found to be more prominent in more aggressive subtypes of BC (basal‐like), pointing to a pro‐tumorigenic role of this signature. Moreover, IFNS was associated with higher recurrence rates and a worse outcome in BC patients. Our study unravels a novel form of paracrine communication between cancer cells and fibroblasts that ultimately results in CTX resistance. Targeting this axis has the potential to improve CTX outcomes in patients with BC.
Treatment with high doses of chemotherapy leads to the secretion of IFNβ1 into the tumour microenvironment. Exposure of stromal fibroblasts to IFNβ1 induces an anti‐viral, pro‐inflammatory signature associated with the expression of several interferon stimulated genes. This reprogramming drives a pro‐tumorigenic state in fibroblasts that facilitates cancer cell recovery after treatment and promotes cancer relapse in patients with breast cancer.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
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