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

🔸 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 TCGA RNA-seq is necessary

🔸 The ATAC-seq is necessary

🔸 The CNV data is not required

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

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/

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.

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