ImmuCycReg-framework

The code repository is for paper: Integration of single sample and population analysis for understanding Immune evasion mechanisms of lung cancer.

Workflow

DATA links:

🔸 Processed data from this study are available in the reproducibility GitHub repository: https://github.com/mengxu98/ImmuCycReg-framework/tree/main/data

🔸 The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) datasets were downloaded from figshare: https://figshare.com/articles/dataset/Data_record_1/5330539 https://figshare.com/articles/dataset/Data_record_2/5330575 https://figshare.com/articles/dataset/Data_record_3/5330593

🔸 Transposase-Accessible Chromatin with high throughput sequencing (ATAC-seq) was downloaded from UCSC-Xena: https://tcgaatacseq.s3.us-east-1.amazonaws.com/download/TCGA_ATAC_peak_Log2Counts_dedup_sample.gz https://tcgaatacseq.s3.us-east-1.amazonaws.com/download/TCGA_ATAC_peak.all.probeMap

🔸 Copy number variations (CNV) dataset was downloaded from GISTIC2.0: https://hgdownload.soe.ucsc.edu/goldenPath/hg38/bigZips/genes/hg38.ncbiRefSeq.gtf.gz

🔸 Genome annotation file was downloaded from hg38.ensGene.gtf: ftp://hgdownload.soe.ucsc.edu/goldenPath/hg38/bigZips/

The input data:

🔸 The TCGA RNA-seq is necessary

🔸 The ATAC-seq is necessary

🔸 The CNV data is not required

The results provide in Supplementary Data:

https://github.com/mengxu98/ImmuCycReg-framework/tree/main/data/Supplementary%20Data

The environment and softwares required:

R 4.1.2
NMF==0.24.0
DESeq2==1.32.0
L0Learn==2.0.3
e1071==1.7-11
glmnet==4.1-4
timeROC==0.4
rms==6.3-0
survival==3.3-1
ggplot2==3.3.6

bedtools v2.27.167
PROMO: http://alggen.lsi.upc.es/cgi-bin/promo_v3/promo/promoinit.cgi?dirDB=TF_8.3

Cytoscape 3.8.2
ClueGo v2.5.9
JAVA v18.0.1.1
GeneNetWeaver: http://gnw.sourceforge.net/

Acknowledge

Note!!! If during the process of using these codes for reproduction, you find that the results are not exactly the same as described in the paper, which is a normal situation and may be caused by the machine, software version, and constantly revised code.

Cite

Li, X., Meng, X., Chen, H. et al. Integration of single sample and population analysis for understanding immune evasion mechanisms of lung cancer. npj Syst Biol Appl 9, 4 (2023). https://doi.org/10.1038/s41540-023-00267-8

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