Complex heatmaps reveal patterns and correlations in multidimensional genomic data

By Zuguang Gu, R. Eils, M. Schlesner. Bioinform., 2016

8,354 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/114d9e30d388fa5b74797b864d092a0ee63e5b27

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In Molecular Biology

Citations in the corpus

Maftools: efficient and comprehensive analysis of somatic variants in cancer (2018, methodology): “…are generated using ComplexHeatmap Bioconductor package, whereas plots generated to display results from analysis modules, such as forest plots, lolli-pop plots, somatic interactions, rainfall plots, among others, are generated using either ggplot2 or base R plot functions (Gu et al. 2016).”
Total replacement of fish meal with black soldier fly (Hermetia illucens) larvae meal does not compromise the gut health of Atlantic salmon (Salmo salar) (2020, methodology): “Plots were generated using ComplexHeatmap (Gu et al., 2016), ggplot2 of the tidyverse and extension packages of ggplot2 including cowplot (Wilke, 2019), ggpubr (Kassambara, 2018) and ggsignif (Ahlmann-Eltze, 2019).”
Tumor cell biodiversity drives microenvironmental reprogramming in liver cancer (2019, methodology): “1) (Gu et al., 2016) was used to show the correlation.”
Make Interactive Complex Heatmaps in R (2021, methodology): “To implement both complex annotation and heatmap visualization, we previously developed an advanced heatmap package ComplexHeatmap (Gu, Eils, and Schlesner 2016).”
VIRIDIC—A Novel Tool to Calculate the Intergenomic Similarities of Prokaryote-Infecting Viruses (2020, methodology): “Fourth, VIRIDIC graphically represents the intergenomic similarity values, the aligned ratios 1 and 2 and the genome length ratios as a heatmap, using the ComplexHeatmap v. 2.5.3 R package (Gu et al. 2016).”
Tumor Microenvironment Characterization in Gastric Cancer Identifies Prognostic and Immunotherapeutically Relevant Gene Signatures (2019, methodology): “OncoPrint used to depict mutation landscape of TCGA-STAD cohort was constructed by ComplexHeatmap R package (52).”
Harnessing protein folding neural networks for peptide–protein docking (2021, methodology): “Visualizations were performed with custom R and Python scripts, using packages ComplexHeatmap 58 , ggplot2 59 , matplotlib 60 , and PupillometryR 61 .”
Severe COVID-19 Is Marked by a Dysregulated Myeloid Cell Compartment (2020, positive): “For visualization of mass cytometry data, cluster minimum-spanning trees were rendered using Cytobank, the ComplexHeatmap package (Gu et al., 2016) was used to display subset phenotypes and GraphPad Prism to generate boxplots of quantitative data.”
TISCH2: expanded datasets and new tools for single-cell transcriptome analyses of the tumor microenvironment (2022, methodology): “For each dataset, the TF enrichment result of each cluster was ranked based on the combined P-value after the normalization and log10 transformations, and the top enriched TFs from different cell type clusters were visualized by heatmap (26).”