ler totalmente TRANSCRIPTOMICS AND STATISTICAL ANALYSIS (English Edition)

**The missing bridge between the bench and the statistics.** > > You extracted the RNA, you received the count matrix... now what? This book takes complete beginners and walks them, module by module, all the way to the full analysis of an RNA-seq experiment — with the rigor of someone who publishes and the patience of someone who teaches. > > You will learn: > > - The essential biology: from the central dogma to gene expression; > - Statistics from scratch: what a p-value is (and what it is NOT), type I/II errors, FDR, and the Benjamini-Hochberg procedure calculated step by step; > - Experimental design: biological replicates, batch effects, and confounding; > - DESeq2 in practice, with an R script commented line by line; > - GO/KEGG enrichment with clusterProfiler (ORA and GSEA); > - RT-qPCR validation: the ΔΔCt method, geNorm, Pfaffl, and the MIQE 2.0 guidelines (2025); > - Installing R and RStudio from zero — and using artificial intelligence ethically to get unstuck. > > Every module offers clear objectives, everyday analogies, fully worked numerical examples, original illustrations, and exercises with a commented answer key — all driven by a real case study: the human macrophage's response to *Leishmania braziliensis* infection, one of the WHO's priority neglected tropical diseases. > > Ideal for undergraduate and graduate students in biomedical science, biology, pharmacy, and related fields who need to master RNA-seq and statistics for a thesis, a dissertation, or a first paper.

1. RNA-seq data analysis 2. bioinformatics for beginners 3. DESeq2 R tutorial 4. statistics for biology students 5. differential gene expression 6. qPCR validation MIQE 7. R RStudio bioinformatics course

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