Tag: PAM50
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How to Analyze RNAseq Data for Absolute Beginners Part 6: A Comprehensive Guide for Cancer Subtype Prediction
Meta Description: Learn how to predict cancer subtypes using RNA-seq data through practical implementations of PAM50, genefu, and GSVA methods. Perfect for bioinformaticians and computational biologists working with gene expression data. Video Tutorial Introduction Cancer subtype prediction from RNA-seq data is crucial for personalized medicine and treatment optimization. This tutorial, part 6 in our RNA-seq…
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Recent Posts
- How to Analyze RNAseq Data for Absolute Beginners Part 20: Comparing limma, DESeq2, and edgeR in Differential Expression Analysis
- How to Analyze RNAseq Data for Absolute Beginners Part 19: Understanding RNA-Seq Gene Expression Normalization
- How to Analyze RNAseq Data for Absolute Beginners Part 18: Analyzing Viral Gene Expression in Host RNA-seq Data
- How to Analyze RNAseq Data for Absolute Beginners Part 17: Viral Sequence Detection
Tags
Alternative Splicing Analysis Cancer cell-type composition CIBERSORTx circRNA-seq circular RNA Differential Expression Fusion Gene Detection gene expression immune cell profiling Isoform limma microRNA miRNA miRNA-seq NCBI GEO Normalization PAM50 Quantification RNA Editing Salmon small RNA smRNA smRNA-seq TPM Transcript UMI Virus Virus-Host Virus Gene Expression