To reproduce the bulk RNAseq data analysis described in the paper titled "Trem2 Giant Macrophages: Biomarker of Good Prognosis in SCC," follow the steps below:
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Access the rendered HTML for the analysis and figures at: MGC_Paper_Analysis.
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Data Retrieval:
- Head and neck SCC patients with tongue SCC data were retrieved using TCGAbiolinks.
- Clinical data for the TCGA cohort was obtained from the supplementary material of the paper by Liu et al., 20181. Progression-Free Interval (PFI) and Overall Survival (OS) were used as time points for plotting, as recommended in the same paper.
- Survival plots were constructed using the survival and survminer R packages.
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Data Preprocessing:
- Bulk RNAseq data were normalized using the EDASeq package based on gene length.
- Genes with zero expression in more than 25% of the samples were removed.
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Differential Expression Analysis:
- The DESeq2 package was used for differential expression testing between MGC High and Low patients.
- Volcano plots were constructed using the EnhancedVolcano package.
- The R package clusterprofiler was employed to analyze the Differentially Expressed Genes (DEGs) between different groups.
For detailed code and implementation, refer to the analysis here.
Nine patients were selected for spatial transcriptomics, including 6 MGC high and 3 MGC low cases. Additionally, giant cell-only spots were annotated by a pathologist. The different slides were preprocessed using the Seurat V4 pipeline, Sctransformed, and integrated by RPCA.
For detailed code and implementation, refer to the analysis here.
Footnotes
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Liu J, Lichtenberg T, Hoadley KA, Poisson LM, Lazar AJ, Cherniack AD, Kovatich AJ, Benz CC, Levine DA, Lee AV, Omberg L, Wolf DM, Shriver CD, Thorsson V; Cancer Genome Atlas Research Network; Hu H. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell. 2018 Apr 5;173(2):400-416.e11. doi: 10.1016/j.cell.2018.02.052. PMID: 29625055; PMCID: PMC6066282. ↩