Interesting links
Here are some interesting links for you! Enjoy your stay :)Pages
- #5439 (no title)
- 2019 Retreat Gallery
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- W3: Intro to R and Data Visualization
- Annual QCBio Retreats
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- W4: Galaxy for NGS Data Analysis
- Education
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- UCLA Galaxy
- W5a: RNA-seq I Analysis – Measuring gene expressions from RNA-seq data
- Recent Publications
- W5b: RNA-Seq II Analysis – Differential gene expression and pathway analysis
- Resources
- ChIP-seq Analysis
- FAQ
- RNA-seq III Analysis – De novo transcriptome assembly using Trinity
- W6: BS-Seq DNA Methylation Analysis with Hoffman2 and R
- W7: Accelerating Research with Automation
- W8: Variant Calling with GATK
- W9: Intro to Python
- Intro to Hi-C
- W10: Mathematical Modeling of Cell Signaling
- W11: Metagenomics Analysis with Python and R
- W12: Intro to MATLAB
- Intro to Phylogenetics
- W13: Genetic Analysis (VCF-Plink)
- W14: Intro to Modern Statistics with R
- W15: Bacterial Genomics
- W16: Library Prep for NGS
- W17: Machine Learning with Python
- W18: Advanced Python
- W19: Statistical Rigor in Genomics Data Analysis
- W20: Single-Cell RNA-Seq Analysis with R
- PATRIC Bioinformatics Resource Center Workshop
- W21: Image Processing for Microscopy
- W22: Intro to Cytoscape
- UCSC Genome Browser
- W23: Advanced Cytoscape
- UCSC Genome Browser
- W24: Cancer Genomics
- W25: Models in Population Genetics
- W26: Protein Structure with AlphaFold
- BS-Sequencing
- RAD-Seq Analysis
- W27: Systems biology of metabolism – workflows and resources for multi-omics data integration
- W28: Advanced Data Visualization w/ ggplot2
- W29: Demultiplexing QC/Good Practices — Hidden Surprises and Illumina Sequencing
- W30: Statistical Methods for Enhancing the Rigor in Single-cell RNA-seq Data Analysis
- W31: Spatial Transcriptomics
- W32: GitHub/Docker
- W33: Accessing The Clinical Database: An Introduction to SQL and the DDR
- W34: Automated Machine Learning
- W35: Advanced Statistics: Regression Models and Statistical Rigor
- W36: Multi-Omics Integration and Network/Pathway Analysis using Mergeomics
- W37: Applications of Large Language Models
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