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Papers: 10.1371/journal.pcbi.1009317

https://doi.org/10.1371/journal.pcbi.1009317

Meta-analysis of transcriptomic data reveals clusters of consistently deregulated gene and disease ontologies in Down syndrome

Cited by: 11
Author(s): Ilario De Toma, Cesar Sierra, Mara Dierssen
Published: over 4 years ago

Software Mentions 14

bioconductor: biomaRt
Interface to BioMart databases (i.e. Ensembl)
Papers that mentioned: 446
Very Likely Science (100)
bioconductor: clusterProfiler
A universal enrichment tool for interpreting omics data
Papers that mentioned: 2,223
Very Likely Science (75)
bioconductor: DESeq2
Differential gene expression analysis based on the negative binomial distribution
Papers that mentioned: 9,583
Very Likely Science (100)
bioconductor: limma
Linear Models for Microarray Data
Papers that mentioned: 7,776
Very Likely Science (78)
bioconductor: STRINGdb
STRINGdb - Protein-Protein Interaction Networks and Functional Enrichment Analysis
Papers that mentioned: 82
Very Likely Science (100)
bioconductor: TissueEnrich
Tissue-specific gene enrichment analysis
Papers that mentioned: 18
Very Likely Science (100)
cran: eulerr
Area-Proportional Euler and Venn Diagrams with Ellipses
Papers that mentioned: 47
Very Likely Science (99)
cran: ggplot2
Create Elegant Data Visualisations Using the Grammar of Graphics
Papers that mentioned: 11,441
Very Likely Science (100)
cran: igraph
Network Analysis and Visualization
Papers that mentioned: 1,555
Very Likely Science (100)
cran: poweRlaw
Analysis of Heavy Tailed Distributions
Papers that mentioned: 33
Very Likely Science (100)
cran: STAR
Spike Train Analysis with R
Papers that mentioned: 5,759
Very Likely Science (100)
cran: statmod
Statistical Modeling
Papers that mentioned: 55
Very Likely Science (93)
cran: tagcloud
Tag Clouds
Papers that mentioned: 2
Very Likely Science (75)
pypi: igraph
High performance graph data structures and algorithms
Papers that mentioned: 1,555
Very Likely Science (100)