GSCALite: a web server for gene set cancer analysis

Chunjie Liu; Feifei Hu; Meng-Xuan Xia; Leng Han; Qiong Zhang; An‐Yuan Guo

doi:10.1093/bioinformatics/bty411

Abstract

Abstract Summary The availability of cancer genomic data makes it possible to analyze genes related to cancer. Cancer is usually the result of a set of genes and the signal of a single gene could be covered by background noise. Here, we present a web server named Gene Set Cancer Analysis (GSCALite) to analyze a set of genes in cancers with the following functional modules. (i) Differential expression in tumor versus normal, and the survival analysis; (ii) Genomic variations and their survival analysis; (iii) Gene expression associated cancer pathway activity; (iv) miRNA regulatory network for genes; (v) Drug sensitivity for genes; (vi) Normal tissue expression and eQTL for genes. GSCALite is a user-friendly web server for dynamic analysis and visualization of gene set in cancer and drug sensitivity correlation, which will be of broad utilities to cancer researchers. Availability and implementation GSCALite is available on http://bioinfo.life.hust.edu.cn/web/GSCALite/. Supplementary information Supplementary data are available at Bioinformatics online.

Keywords

GeneExpression quantitative trait lociComputational biologyCancerWeb serverBiologyBioinformaticsGeneticsComputer scienceThe InternetWorld Wide WebSingle-nucleotide polymorphism

Affiliated Institutions

Related Publications

GE-mini: a mobile APP for large-scale gene expression visualization

Zefang Tang , Chenwei Li , Karena Zhang +2 more

Abstract Summary The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) projects produced large-scale RNA sequencing data, which provides an opportunity for perfor...

2016 Bioinformatics 34 citations

ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks

Gabriela Bindea , Bernhard Mlecnik , Hubert Hackl +7 more

Abstract Summary: We have developed ClueGO, an easy to use Cytoscape plug-in that strongly improves biological interpretation of large lists of genes. ClueGO integrates Gene Ont...

2009 Bioinformatics 6398 citations

Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression

Urmo Võsa , Annique Claringbould , Harm-Jan Westra +97 more

Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performe...

2021 Nature Genetics 1817 citations

GSDS 2.0: an upgraded gene feature visualization server

Bo Hu , Jinpu Jin , An‐Yuan Guo +3 more

Abstract Summary: Visualizing genes’ structure and annotated features helps biologists to investigate their function and evolution intuitively. The Gene Structure Display Server...

2014 Bioinformatics 4589 citations

PADGE: analysis of heterogeneous patterns of differential gene expression

Li Li , Amitabha Chaudhuri , John Chant +1 more

We have devised a novel analysis approach, percentile analysis for differential gene expression (PADGE), for identifying genes differentially expressed between two groups of het...

2007 Physiological Genomics 19 citations

Publication Info

Year: 2018
Type: article
Volume: 34
Issue: 21
Pages: 3771-3772
Citations: 1291
Access: Closed

External Links

View on DOI.org

Social Impact

Altmetric

GSCALite: a web server for gene set cancer analysis

PlumX Metrics

Social media, news, blog, policy document mentions

Citation Metrics

1291

OpenAlex

Cite This

APA Style

                            
                                
                                    Chunjie Liu, 
                                
                                    Feifei Hu, 
                                
                                    Meng-Xuan Xia
                                
                                et al.
                            
                            (2018). 
                            GSCALite: a web server for gene set cancer analysis. 
                            Bioinformatics
                            , 34
                            (21)
                            , 3771-3772.
                            https://doi.org/10.1093/bioinformatics/bty411
                        

Identifiers

DOI: 10.1093/bioinformatics/bty411