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Learn ChIP-seq Data Analysis Using bioinfo Linux Pipeline

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Abdul Rehman Ikram

2:55:22

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  • 1. Understanding ChIP-seq Principles and Applications and Workflow.mp4
    08:17
  • 1. 1st Step of Chip-Seq Data Analysis.mp4
    03:38
  • 2. 2nd Step of Chip-Seq Data Analysis.mp4
    02:55
  • 3. 3rd Step of Chip-Seq Data Analysis.mp4
    02:45
  • 4. 4th Step of Chip-Seq Data Analysis.mp4
    02:22
  • 5. 5th Step of Chip-Seq Data Analysis.mp4
    02:50
  • 6. 6th Step of Chip-Seq Data Analysis.mp4
    02:24
  • 7. 7th Step of Chip-Seq Data Analysis.mp4
    02:04
  • 8. 8th Step of Chip-Seq Data Analysis.mp4
    03:09
  • 9. Tools Assignment.html
  • 1. Getting Started with Linux for Bioinformatics.mp4
    18:40
  • 2.1 Lecture 01 (1).pdf
  • 2. Hands-On Experience with Basic Linux Commands.mp4
    15:46
  • 3.1 Bioinformatics software.docx
  • 3.2 Bioinformatics tools (1).pptx
  • 3. Bioinformatics Tools Installation.mp4
    09:09
  • 4. E-utilities on Linux.mp4
    16:41
  • 5. Using Linux on Windows WSL.mp4
    05:06
  • 6. Windows Subsystem for Linux assignment.html
  • 1.1 Using SRA ToolKit .txt
  • 1. Downloading the Dataset and Genome.mp4
    14:16
  • 2.1 Pipeline.txt
  • 2. Step 1 Quality Check and Adapter Removal with Fastp.mp4
    10:11
  • 3.1 Pipeline.txt
  • 3. Step 2 Alignment Against Reference Genome with BWA.mp4
    10:38
  • 4.1 Pipeline.txt
  • 4. Step 3 Sorting and Converting SAM to BAM with Samtools.mp4
    07:03
  • 5.1 Pipeline.txt
  • 5. Step 4 Sorting and Indexing BAM Files with Samtools.mp4
    04:32
  • 6.1 Pipeline.txt
  • 6. Step 5 Filtering Reads by Quality with Samtools.mp4
    03:36
  • 7.1 Pipeline.txt
  • 7. Step 6 Peak Calling with MACS2.mp4
    10:01
  • 8.1 Pipeline.txt
  • 8. Step 7 Installing HOMER.mp4
    04:30
  • 9.1 Pipeline.txt
  • 9. Step 8 Annotating Peaks and Motif Discovery with HOMER.mp4
    11:34
  • 1. Course Recap Lecture.mp4
    03:15
  • 1. The Final Quiz.html
  • 2. Final Project.html
  • Description


    Master ChIP-seq Data Analysis: From Quality Control to Peak Annotation and Motif Finding Using Bioinformatics Tools

    What You'll Learn?


    • Understand the Principles of ChIP-seq: Gain a comprehensive understanding of the principles and applications of ChIP-seq technology in biological research.
    • Familiarity with ChIP-seq Workflow: Become proficient in the overall ChIP-seq workflow, from experimental setup to data analysis.
    • Install and Configure Bioinformatics Tools: Learn how to install and configure essential bioinformatics tools required for ChIP-seq data analysis, including Fas
    • Perform Quality Control: Conduct quality checks on raw sequencing data and remove adapters using Fastp.
    • Align Sequencing Reads to Reference Genome: Align sequencing reads to a reference genome using BWA and handle the resulting SAM files.
    • Process and Manage BAM Files: Convert SAM files to BAM format, sort, and index BAM files using Samtools, ensuring efficient data management and analysis.
    • Filter Reads by Mapping Quality: Filter sequencing reads based on mapping quality to retain high-quality data for downstream analysis.
    • Perform Peak Calling: Identify protein-DNA binding sites by performing peak calling using MACS2, and understand the significance of peaks in ChIP-seq data.
    • Annotate Peaks: Annotate identified peaks with genomic features using HOMER, gaining insights into the biological relevance of binding sites.
    • Discover Motifs: Conduct motif analysis using HOMER to identify DNA sequence motifs enriched at binding sites, enhancing the understanding of regulatory element
    • Learn practical and in-demand skills for ChIP-seq data analysis.
    • Gain hands-on experience with essential bioinformatics tools.
    • Prepare for advanced studies or career opportunities in bioinformatics and computational biology.

    Who is this for?


  • Bioinformatics Enthusiasts: Individuals interested in learning bioinformatics and computational biology techniques, specifically focusing on ChIP-seq data analysis.
  • Students and Researchers: Undergraduate and graduate students in biology, genetics, bioinformatics, or related fields who want to gain practical skills in ChIP-seq data analysis.
  • Laboratory Technicians and Scientists: Laboratory professionals and researchers working in molecular biology, genetics, or epigenetics who wish to enhance their data analysis skills and learn how to process and analyze ChIP-seq data.
  • Data Scientists and Computational Biologists: Professionals in data science and computational biology looking to expand their expertise to include ChIP-seq data analysis using bioinformatics pipelines.
  • Bioinformatics Instructors and Educators: Educators and instructors who teach bioinformatics and want to incorporate practical ChIP-seq data analysis techniques into their curriculum.
  • Biotechnology and Pharmaceutical Industry Professionals: Individuals working in biotech or pharmaceutical companies who need to analyze ChIP-seq data as part of their job responsibilities.
  • Self-Learners and Career Changers: Anyone with a passion for bioinformatics and a desire to transition into a career in bioinformatics or computational biology, even if they are starting from scratch.
  • What You Need to Know?


  • No prior bioinformatics experience is necessary; the course is beginner-friendly.
  • Basic Understanding of Biology: Familiarity with basic biological concepts, particularly in genetics and molecular biology, is helpful but not required.
  • Introductory Knowledge of Bioinformatics: Basic knowledge of bioinformatics concepts is advantageous, but beginners are welcome.
  • Computer Literacy: Basic computer skills, including file management and software installation.
  • Access to a Computer: A computer (Windows, Mac, or Linux) with internet access for downloading software and datasets.
  • Willingness to Learn: An eagerness to learn new tools and techniques in bioinformatics.
  • Text Editor: Installation of a text editor (e.g., Notepad++, Sublime Text, or VS Code) for viewing and editing scripts.
  • Linux Environment: While not required, having access to a Linux environment or the ability to install and use the Windows Subsystem for Linux (WSL) can enhance the learning experience.
  • More details


    Description

    Unlock the power of ChIP-seq data analysis with our comprehensive course, Learn ChIP-seq Data Analysis Using Bioinfo Linux Pipeline. Whether you're a beginner or looking to expand your bioinformatics skills, this course provides a step-by-step guide to mastering ChIP-seq analysis using essential bioinformatics tools.

    What You'll Learn:

    • Understand the principles and applications of ChIP-seq technology.

    • Perform quality control and adapter removal on raw sequencing data.

    • Align sequencing reads to a reference genome and manage SAM/BAM files.

    • Filter high-quality reads and conduct peak calling to identify protein-DNA binding sites.

    • Annotate peaks with genomic features and discover DNA sequence motifs.

    Course Modules:

    1. Introduction to ChIP-seq: Learn the basics of ChIP-seq technology and its workflow.

    2. Theoretical Foundations and Tools: Explore the key tools and files used in ChIP-seq analysis.

    3. Linux Essentials for Bioinformatics: Get started with Linux commands and learn to use Linux in Windows.

    4. Practical Pipeline Implementation: Gain hands-on experience with each step of the ChIP-seq data analysis pipeline, from quality control to motif finding.

    Intended Learners:

    • Bioinformatics enthusiasts

    • Students and researchers in biology, genetics, or bioinformatics

    • Laboratory technicians and scientists

    • Data scientists and computational biologists

    • Bioinformatics instructors and educators

    • Biotechnology and pharmaceutical industry professionals

    • Self-learners and career changers

    Prerequisites:

    • No prior bioinformatics experience is required.

    • Basic understanding of biology is helpful but not mandatory.

    • Basic computer skills are required.

    Join us to gain practical, in-demand skills in ChIP-seq data analysis. By the end of this course, you'll be proficient in using a bioinformatics Linux pipeline to analyze ChIP-seq data, preparing you for advanced studies or career opportunities in bioinformatics and computational biology.

    Who this course is for:

    • Bioinformatics Enthusiasts: Individuals interested in learning bioinformatics and computational biology techniques, specifically focusing on ChIP-seq data analysis.
    • Students and Researchers: Undergraduate and graduate students in biology, genetics, bioinformatics, or related fields who want to gain practical skills in ChIP-seq data analysis.
    • Laboratory Technicians and Scientists: Laboratory professionals and researchers working in molecular biology, genetics, or epigenetics who wish to enhance their data analysis skills and learn how to process and analyze ChIP-seq data.
    • Data Scientists and Computational Biologists: Professionals in data science and computational biology looking to expand their expertise to include ChIP-seq data analysis using bioinformatics pipelines.
    • Bioinformatics Instructors and Educators: Educators and instructors who teach bioinformatics and want to incorporate practical ChIP-seq data analysis techniques into their curriculum.
    • Biotechnology and Pharmaceutical Industry Professionals: Individuals working in biotech or pharmaceutical companies who need to analyze ChIP-seq data as part of their job responsibilities.
    • Self-Learners and Career Changers: Anyone with a passion for bioinformatics and a desire to transition into a career in bioinformatics or computational biology, even if they are starting from scratch.

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    Abdul Rehman Ikram
    Abdul Rehman Ikram
    Instructor's Courses
    My teaching skills might not be as good as experienced and professional instructors on Udemy who made handsome profits from their courses, but I am sure that I have a sincere passion to teach, to broaden my professional networks, and teach that I love to do in my bioinformatics work.My goal is to help you to understand highly complex biological data and improve your computational skills in the analysis of Genomics, Proteomics, and Transcriptomics DATA using various Bioinformatics Approaches.if you have any queries about any of my work please let me know in my Udemy inbox section I'll be happy to answer all of your questions.That was All Folks!!
    Students take courses primarily to improve job-related skills.Some courses generate credit toward technical certification. Udemy has made a special effort to attract corporate trainers seeking to create coursework for employees of their company.
    • language english
    • Training sessions 24
    • duration 2:55:22
    • Release Date 2024/07/24