Papers: 10.1186/s12967-021-02773-x

https://doi.org/10.1186/s12967-021-02773-x

Multi-omics characterization and validation of invasiveness-related molecular features across multiple cancer types

Cited by: 5
Author(s): Guoshu Bi, Jiaqi Liang, Yuansheng Zheng, Runmei Li, Mengnan Zhao, Yiwei Huang, Cheng Zhan, Songtao Xu, Hong Fan
Published: over 5 years ago

Software Mentions 15

bioconductor: clusterProfiler
A universal enrichment tool for interpreting omics data
Papers that mentioned: 2,223
Very Likely Science (75)
bioconductor: GSVA
Gene Set Variation Analysis for microarray and RNA-seq data
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Very Likely Science (100)
bioconductor: limma
Linear Models for Microarray Data
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Very Likely Science (78)
bioconductor: maftools
Summarize, Analyze and Visualize MAF Files
Papers that mentioned: 288
Very Likely Science (100)
cran: circlize
Circular Visualization
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Very Likely Science (100)
cran: forestplot
Advanced Forest Plot Using 'grid' Graphics
Papers that mentioned: 146
Very Likely Science (85)
cran: ggplot2
Create Elegant Data Visualisations Using the Grammar of Graphics
Papers that mentioned: 11,441
Very Likely Science (100)
cran: ggpubr
'ggplot2' Based Publication Ready Plots
Papers that mentioned: 856
Very Likely Science (75)
cran: igraph
Network Analysis and Visualization
Papers that mentioned: 1,555
Very Likely Science (100)
cran: networkD3
D3 JavaScript Network Graphs from R
Papers that mentioned: 37
Very Likely Science (85)
cran: pheatmap
Pretty Heatmaps
Papers that mentioned: 2,572
Very Likely Science (75)
cran: survminer
Drawing Survival Curves using 'ggplot2'
Papers that mentioned: 1,473
Very Likely Science (75)
pypi: analysis
Source code analysis of Python programs
Papers that mentioned: 2,036
Very Likely Science (90)
pypi: GSVA
Python CLI and module for running the GSVA R bioconductor package with Python Pandas inputs and outputs.
Papers that mentioned: 893
Very Likely Science (100)
pypi: igraph
High performance graph data structures and algorithms
Papers that mentioned: 1,555
Very Likely Science (100)