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 ATAC-seq Data For Absolute Beginners Part 1: From FASTQ To Peaks
- How To Analyze ChIP-seq Data For Absolute Beginners Part 5: Mastering Reproducibility With IDR Analysis
- How To Analyze ChIP-seq Data For Absolute Beginners Part 4: From FASTQ To Peaks With MACS2
- How To Analyze ChIP-seq Data For Absolute Beginners Part 3: Differential Binding Analysis and Motif Discovery
Tags
Alternative Splicing Analysis batch effects ChIP-seq ComBat-seq Counts covariates adjustment CPM Data Sharing DESeq2 Differential Expression edgeR FPKM gene expression HOMER HPC Isoform limma MACS2 miRNA miRNA-seq mixed linear models Normalization peak calling Quantification Salmon TPM Transcript Virus Virus-Host Virus Gene Expression