№ files_lp_4_process_3_073638
Comprehensive methods for molecular profiling of breast tumors and survival modeling integrating gene expression, proteomics, and metabolomics datasets.
Year: 2014-2018
Research focus: Breast cancer molecular profiling and survival analysis
Document type: Supplementary methods
Institution: National Cancer Institute, Center for Cancer Research; Affymetrix; Illumina; Qiagen
Techniques: Gene expression profiling, RNA sequencing, mass spectrometry-based proteomics, LASSO Cox regression
Sample type: Human breast tumor tissues and treated cell lines
Number of samples: 61 tumors in discovery set; additional cell line experiments
Data analysis software: R packages (Oligo, limma, DESeq2, survival, glmnet, glmpath, survcomp), Picard, Trimmomatic, TopHat, HTSeq, Proteome Discoverer, SEQUEST HT
Genes analyzed: 28,869 genes
Proteins identified: ~4,000 with ≥2 peptides and ≥15% tissue representation
Metabolites analyzed: 398 metabolites
Treatment conditions: Deoxycholate 20 µM and 50 µM in cell lines
Statistical methods: Wald statistics, Benjamini-Hochberg adjustment, LASSO feature selection, Kaplan-Meier survival analysis, concordance index (C-index)
Clinical variables: Age, race/ethnicity, disease stage and grade, node status, menopausal status, neoadjuvant/hormone/chemotherapy
Price: 8 / 10 USD
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