Category: Transcriptomics
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How to Analyze RNAseq Data for Absolute Beginners Part 10: Isoform Analysis
Video Tutorial If you’ve followed our previous tutorials on RNA-seq analysis, you’re already familiar with gene-level analysis. But genes are far more complex than simple on/off switches – they can produce multiple versions of RNA transcripts through fascinating processes like alternative splicing. These different versions, called isoforms, allow a single gene to create multiple protein…
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How to Analyze RNAseq Data for Absolute Beginners Part 9: RNA Editing Analysis
Video Tutorial RNA editing represents one of the most fascinating mechanisms in molecular biology – a process that introduces targeted changes to RNA sequences after transcription, creating a dynamic transcriptome that diverges from the genome’s blueprint. Through this tutorial, you’ll learn how to analyze RNA editing events from RNA-seq data, uncovering these crucial modifications that…
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How to Analyze RNAseq Data for Absolute Beginners Part 8: Alternative Splicing Analysis
Video Tutorial Introduction The human genome harbors an elegant solution to the challenge of biological complexity. Through alternative splicing (AS), a single gene can orchestrate the production of multiple protein variants, much like a composer creating different melodies from the same set of musical notes. This remarkable mechanism serves as nature’s way of expanding our…
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How to Analyze RNAseq Data for Absolute Beginners Part 7: Unlocking Cell-Type Resolution from Bulk RNA-seq Data With Deconvolution Analysis
Video Tutorial Understanding Bulk RNA-seq Deconvolution Analysis: Unraveling Cellular Complexity In the ever-evolving landscape of molecular biology, bulk RNA sequencing has emerged as a fundamental technology for understanding gene expression patterns. However, like peering through a frosted window, bulk RNA-seq provides only an averaged view of the complex cellular world within our tissues. This challenge…
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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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How to Analyze RNAseq Data for Absolute Beginners Part 5: From DEGs to Pathways – Best Practices
Video Tutorial Introduction After completing the data preparation, statistical testing, and visualization steps, we’re finally ready to explore the biological significance of our RNA sequencing data. As biologists, this is the moment we’ve been waiting for – but how do we make sense of the hundreds or thousands of differentially expressed genes (DEGs) we’ve identified?…
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How to Analyze RNAseq Data for Absolute Beginners Part 4: A Complete Guide to Creating Publication-Ready Figures
Video Tutorial Introduction After identifying differentially expressed genes (DEGs), the next crucial step is visualizing your results effectively. Strong visualizations don’t just make your data look pretty – they transform complex genomic information into clear, interpretable insights that can reveal hidden patterns and biological stories within your data. In this tutorial, you’ll learn how to…
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How to Analyze RNAseq Data for Absolute Beginners Part 3: From Count Table to DEGs – Best Practices
Video Tutorial As we move forward in our RNAseq analysis journey, we’ll be transitioning from the Linux environment to R, a powerful and versatile statistical analysis tool. R is not only a programming language but also a platform widely used in data science, statistical computing, and predictive modeling. Tech giants like Microsoft, Meta, Google, Amazon,…
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How to Analyze RNAseq Data for Absolute Beginners Part 2: From Fastq to Counts – Best Practices
Video Tutorial Introduction The most straightforward way to obtain a count table is to request it directly from your sequencing company or your institution’s sequencing core. This option may involve an additional fee. However, for those eager to learn or save money, let’s walk through the process together. Before we dive in, a quick reminder:…
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How to analyze RNAseq Data for Absolute Beginners Part 1: Environment setup
Video Tutorial Introduction RNA sequencing (RNAseq) has revolutionized the field of transcriptomics, offering unprecedented insights into gene expression patterns across entire genomes. This powerful technique allows researchers to quantify RNA levels, discover novel transcripts, and identify differentially expressed genes under various conditions. Whether you’re studying cancer progression, developmental biology, or environmental responses in organisms, RNAseq…
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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