ChIP-Seq Courses and Certifications

ChIP-seq with Bioconductor in R

Learn how to analyse and interpret ChIP-seq data with the help of Bioconductor using a human cancer dataset.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Analyzing Genomic Data in R

Start exploring the world of computational biology with essential Bioconductor packages and workflows for next-generation sequencing data analysis.

• DataCamp
• 16 hours
• Self-Paced
• Free Trial Available

Computational Genomics Summer Institute CGSI

Selecting Between-sample ChIP-Seq Normalization Methods - Assumptions and Implications

Explore ChIP-seq normalization methods, their assumptions, and impact on differential binding analysis. Learn to select appropriate techniques for accurate genomic data interpretation.

• YouTube
• 44 minutes
• Self-Paced
• Free Video

Statistics for Genomic Data Science

378 ratings at Coursera

An introduction to the statistics behind the most popular genomic data science projects. This is the sixth course in the Genomic Big Data Science Specialization from Johns Hopkins University.

• Coursera
• 9-10 hours
• Self-Paced
• Paid Course

Credential

Data Analysis for Genomics

Unlock genomics' potential: Analyze and interpret high-throughput data using R and Bioconductor. Master key concepts through coding, from basic to advanced techniques in functional genomics and data visualization.

• edX
• 13 weeks, 2-4 hours/week
• Self-Paced
• $657.00
• 3 courses

Fred Hutchinson Cancer Center

Researcher's guide to DNA sequencing data

Comprehensive guide to DNA sequencing methods, covering WGS, WXS, methylation, chromatin analysis, and microarrays, with focus on experimental design and data interpretation.

• Coursera
• 5 hours 30 minutes
• Self-Paced
• Paid Course

High Throughput Sequencing

Comprehensive playlist covering high-throughput sequencing analysis, including RNA-seq, ChIP-Seq, PCA, clustering, and statistical methods for bioinformatics and genomics research.

• YouTube
• 6 hours
• Self-Paced
• Free Video

STAT115 2020

4 ratings

Comprehensive bioinformatics course covering sequencing technologies, RNA-seq analysis, clustering methods, single-cell genomics, epigenetics, GWAS, and cancer genomics. Emphasizes computational techniques and data analysis in modern biology.

• YouTube
• 1 day 5 hours
• Self-Paced
• Free Video

Biological data analysis and visualization with R

Master data analysis and visualization techniques in R for biological datasets, from basic statistics to advanced methods like ChIP-seq analysis, regression models, and machine learning applications.

• Swayam
• 8 weeks
• Self-Paced
• Free Online Course

STAT115 2018

1 rating

Comprehensive exploration of computational biology, covering microarrays, RNA-seq, ChIP-seq, epigenetics, GWAS, cancer genomics, and deep learning, with hands-on data analysis techniques.

• YouTube
• 1 day 5 hours
• Self-Paced
• Free Video

STAT115

Comprehensive lecture series on statistical methods for analyzing genomic data, covering microarrays, RNA-seq, epigenetics, cancer genomics, and more. Focuses on practical applications in bioinformatics and computational biology.

• YouTube
• 1 day 1 hour
• Self-Paced
• Free Video

Animated biology With arpan

Transcription in Eukaryotes - Chromatin-Centric View of RNA Polymerase II Transcripts

Explore eukaryotic transcription through a chromatin-centric lens, focusing on RNA polymerase II transcripts and related processes like mRNA capping and polyadenylation.

• YouTube
• 24 minutes
• Self-Paced
• Free Video

OMGenomics

15 Bioinformatics Project Ideas

Explore 15 hands-on bioinformatics project ideas covering data reproduction, tool benchmarking, web app development, and interactive educational content creation.

• YouTube
• 11 minutes
• Self-Paced
• Free Video

Manolis Kellis

Epigenomics and Hidden Markov Models in Computational Biology - Lecture 5

Explore epigenomics, histone modifications, and DNA profiling techniques. Learn about read mapping, quality control, and Hidden Markov Models for analyzing chromatin states in computational biology.

• YouTube
• 1 hour 24 minutes
• Self-Paced
• Free Video

Computational Genomics Summer Institute CGSI

Epigenomics Data Analysis - A Tutorial

Master essential techniques for analyzing epigenomics data, including ChIP-Seq analysis, histone modification clustering, and transcriptome integration methods for genomic research.

• YouTube
• 35 minutes
• Self-Paced
• Free Video