the paper An immune-related gene prognostic index for head and neck squamous cell carcinoma showed multiple bioinformatics methods in data analysis.
I am going to reproduce all the results in this paper to be familiar with the bioinformatics skills.
The Datasets, containing patients' information, expression profiles and database were published online
DEGs were identified by limma package with Ad.Pvalue < 0.05 & |log2FC| > 0.5
The overlap between aforementioned DEGs and immune-related gene from InnateDB or ImmPort database were acquired
To identify hub genes, WGCNA were performed
Multivariate Cox regression analysis to identify the survival hub genes; Calculate prognostic score by the expression values and coefficient of Cox model
TCGA_HNSC
├── Assay
│ ├── 00.PrecessData
│ │ ├── GSE65858
│ │ └── TCGA_HNSC
│ ├── 01.Differential
│ │ ├── DEA_visualization.Rmd
│ │ ├── DEA_visualization.nb.html
│ │ ├── DifferentialAnalysis.Rmd
│ │ └── DifferentialAnalysis.nb.html
│ └── 02.ImmuneHubGenes
│ ├── HubGenes.Rmd
│ ├── HubGenes.nb.html
│ ├── ImmuneGenes.Rmd
│ └── ImmuneGenes.nb.html
├── README.md
├── Result
│ ├── Differential
│ │ ├── HNSC_limma_ImmuneGene.csv
│ │ └── HNSC_limma_gene.csv
│ ├── Figure
│ │ └── HNSC_volcano.pdf
│ ├── GeneSet
│ └── Profile
│ └── HNSC_ExprSet_ImmuneGene.RDS
└── Study
├── ImmuneRelatedGenes
│ ├── Immport_GeneList.tsv
│ ├── Immport_GeneListGOAnnotation.tsv
│ ├── ImmuneRelatedGenes.tsv
│ ├── Innatedb_curated_genes.tsv
│ ├── gene_mouse2human.tsv
│ ├── get_ImmuneRelatedGenes.pl
│ ├── innatedb_curated_genes.xls
│ └── work.sh
├── RNARelationship
│ ├── raid.v2_rna-rna.txt
│ └── raid.v2_rna-rna.zip
├── Reference
│ └── An Immune-Related Gene Prognostic Index for Head and Neck Squamous Cell Carcinoma.pdf
└── SeqData
├── GSE65858
└── TCGA_HNSC- Hua Zou ([email protected])
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent