Tagged: tutorial
11 posts found
How to Make Volcano Plots and MA Plots in R: ggplot2 and EnhancedVolcano
Step-by-step R tutorial for publication-quality volcano plots and MA plots from DESeq2 results. Covers ggplot2 from scratch, ggrepel gene labeling, EnhancedVolcano, and plot interpretation.
PCA and Clustering for RNA-Seq QC in Python: Spot Outliers Before DESeq2
Python tutorial: normalize RNA-seq counts, run PCA with scikit-learn, plot interactively with plotly, build a sample distance heatmap, and detect outliers before differential expression.
Differential Expression Analysis in Python with PyDESeq2: A Complete Tutorial
Run DESeq2 differential expression analysis entirely in Python using PyDESeq2. Learn DeseqDataSet, DeseqStats, apeglm shrinkage, multi-factor designs, and pandas result filtering.
How to Run DESeq2: A Complete Walkthrough from Count Matrix to Results
Step-by-step DESeq2 tutorial in R: build a DESeqDataSet, understand size factors and dispersion, run DESeq(), interpret results columns, apply lfcShrink with apeglm, and filter DEGs.
How to Quantify RNA-Seq Reads with Salmon: Index, Quant, and Import to R
Step-by-step Salmon RNA-seq tutorial: build a decoy-aware index, run salmon quant on paired-end reads, understand quant.sf output, and import into DESeq2 with tximport.
Importing Salmon Output into R: tximeta, tximport, and DESeq2 Setup
Complete R tutorial for importing Salmon quant.sf files with tximeta and tximport. Build a tx2gene table, fix ID mismatch errors, and set up a DESeqDataSet for multi-factor designs.
STAR vs HISAT2 vs Salmon: Which Aligner Should You Use?
STAR does full genome alignment. HISAT2 uses less memory. Salmon skips alignment entirely. Here is what each approach actually means for your RNA-seq results and when each one is the right call.
What Actually Happens to Your RNA Sample Before It Becomes Data
From tissue extraction to FASTQ file: a clear breakdown of RNA-seq library prep, sequencing chemistry, and what goes wrong at each step.
Trimming Adapters with Trimmomatic and fastp: A Side-by-Side Walkthrough
When adapter trimming helps, when it hurts, and how to run Trimmomatic and fastp on RNA-seq data with the parameter choices that actually matter.
How to Run FastQC and MultiQC on Raw RNA-Seq Reads
A hands-on guide to automating RNA-seq QC across dozens of samples using FastQC and MultiQC, with bash and Python scripts for parsing and flagging failures.
Raw Reads to Counts: The Bulk RNA-Seq Pipeline Explained
A practical breakdown of every computational step in bulk RNA-seq: from FASTQ quality control through trimming, alignment, and quantification to your final count matrix.