Author: Lei
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How To Analyze ATAC-seq Data For Absolute Beginners Part 1: From FASTQ To Peaks
Introduction: Understanding ATAC-seq At the heart of molecular biology lies a fundamental question: how do cells regulate which genes are expressed and when? One powerful technique to explore this question is Assay for Transposase-Accessible Chromatin sequencing, commonly known as ATAC-seq. This tutorial introduces beginners to the fascinating world of ATAC-seq data analysis using HOMER and…
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How To Analyze ChIP-seq Data For Absolute Beginners Part 5: Mastering Reproducibility With IDR Analysis
Introduction: Why Reproducibility Is Crucial In ChIP-seq Analysis Chromatin Immunoprecipitation followed by high-throughput sequencing (ChIP-seq) has revolutionized our understanding of protein-DNA interactions across the genome. However, like all experimental techniques, ChIP-seq is subject to both technical and biological variability. This variability creates a fundamental challenge: how do we distinguish genuine protein binding events from experimental…
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How To Analyze ChIP-seq Data For Absolute Beginners Part 4: From FASTQ To Peaks With MACS2
Introduction: Expanding Your ChIP-seq Analysis Toolkit Chromatin immunoprecipitation followed by sequencing (ChIP-seq) has revolutionized our understanding of protein-DNA interactions across the genome. In this fourth installment of our ChIP-seq tutorial series, we explore an alternative approach to peak calling using MACS2 (Model-based Analysis of ChIP-Seq), a widely used and statistically robust tool that complements the…
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How To Analyze ChIP-seq Data For Absolute Beginners Part 3: Differential Binding Analysis and Motif Discovery
Introduction: Moving Beyond Basic Peak Calling In our previous tutorials, we walked through the fundamental process of ChIP-seq analysis, from raw sequencing reads to identifying where a protein of interest binds to DNA. While finding these binding sites (peaks) is a crucial first step, it’s often just the beginning of extracting meaningful biological insights from…
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How To Analyze ChIP-seq Data For Absolute Beginners Part 2: Visualizing ChIP-seq Data
Introduction: Why Visualization Is Critical In ChIP-seq Analysis After processing raw ChIP-seq data and identifying protein-DNA binding sites in Part 1, visualization becomes the crucial next step that transforms abstract numerical data into interpretable biological insights. While peak calling identifies where proteins bind to DNA, visualization helps answer questions about how and why these interactions…
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How To Analyze ChIP-seq Data For Absolute Beginners Part 1: From FASTQ To Peaks With HOMER
Introduction: Understanding ChIP-seq At the heart of molecular biology lies a fundamental question: how do cells regulate which genes are expressed and when? One of the most powerful techniques to explore this question is Chromatin Immunoprecipitation followed by sequencing, commonly known as ChIP-seq. This tutorial introduces beginners to the fascinating world of ChIP-seq data analysis…
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HPC Data Management for NGS Analysis: Storage, Transfer, and Sharing Best Practices
Introduction to Data Management on High-Performance Computing Systems High-Performance Computing (HPC) systems have become essential tools for Next-Generation Sequencing (NGS) data analysis. These powerful computing environments allow researchers to process and analyze massive genomic datasets that would be impossible to handle on standard desktop computers. However, working effectively with HPC systems requires understanding how to…
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High Performance Computing (HPC) Job Submission Systems: A Beginner’s Guide to Slurm
Introduction: Understanding High Performance Computing Have you ever tried to run a program on your computer, only to find that it takes hours or even days to complete? Or perhaps you needed to analyze a huge dataset that wouldn’t even fit in your computer’s memory? These are the kinds of problems that High Performance Computing…
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How to Analyze RNAseq Data for Absolute Beginners 21: A Comprehensive Guide to Batch Effects & Covariates Adjustment
Introduction to Batch Effects in RNA-seq Analysis In high-throughput sequencing experiments, batch effects represent one of the most challenging technical hurdles researchers face. These systematic variations arise not from biological differences between samples but from technical factors in the experimental process. Understanding and properly adjusting for batch effects is essential for generating reliable and reproducible…
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How to Analyze RNAseq Data for Absolute Beginners Part 20: Comparing limma, DESeq2, and edgeR in Differential Expression Analysis
Video Tutorial Introduction Differential expression (DE) analysis represents a fundamental step in understanding how genes respond to different biological conditions. When we perform RNA sequencing, we’re essentially taking a snapshot of all the genes that are active (or expressed) in our samples at a given moment. However, the real biological insights come from understanding how…
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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
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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