Explore a comprehensive bioinformatics course covering a wide range of topics and techniques essential for analyzing biological data. Learn to plot heatmaps in RStudio, identify differentially expressed genes from RNA-Seq samples using Galaxy, perform gene set enrichment analysis, and understand VCF file formats. Master RNA-Seq analysis, including differential gene expression and single-cell RNA-Seq data analysis using the Seurat package. Dive into SAM/BAM file specifications, GEO data analysis in R, and advanced statistical concepts like log2 fold-change and linear mixed models. Discover weighted correlation network analysis (WGCNA), survival analysis on cancer data, and hidden Markov models. Explore object-oriented programming in R, meta-analysis techniques, and protein folding with AlphaFold 2. Gain skills in text mining, TCGA cancer database analysis, and creating complex heatmaps. Investigate scRNA-Seq integration analysis, cancer somatic mutation analysis using MAFtools, and machine learning approaches for biomarker identification. Understand file formats like GFF3, learn best practices for data manipulation and project organization in R, and explore 16s rRNA sequencing analysis. Delve into topics such as semantic similarity between genes, organoid creation, and utilizing resources like cBioPortal for human cancer genomics.
Overview
Syllabus
How to plot a Heatmap in Rstudio, the easy way - Part 1/3.
Galaxy Tutorial 1: How to identify DEGs from RNA-Seq sample.
Gene Set Enrichment Analysis (+ R tutorial).
Understanding VCF file | Variant Call Format Part 1/3.
RNASeq Analysis | Differential Expressed Genes (DEGs) from FastQ.
Clustering and Markers Identification for ScRNA-Seq | Seurat Package Tutorial.
Understanding SAM/BAM file specifications.
How to analyze GEO data in R?.
Log2 fold-change & DESeq2 model in a nutshell.
(Simplified) Linear Mixed Model in R with lme().
How to analyze 10X Single Cell RNA-seq data with R| Seurat Package Tutorial.
WGCNA in a nutshell.
Survival Analysis on Cancer data | RStudio Tutorial.
Understanding VCF file | Variant Call Format Part 2/3.
Weighted correlation network analysis (WGCNA) tutorial in R| PART I.
Understanding VCF file | Variant Call Format Part 3/3.
Hidden Markov Model | Clearly Explained.
S3 and S4 Object in R | Object Oriented Programming and Bioconductor.
You will need this for your meta analysis | Forest plot in RStudio.
Alphafold 2 and Protein Folding Explained.
Text Mining with R - Part 1 | Importing PDF and Text Detection.
How to check the frequencies of gene mutations in TCGA cancer database [R].
Creating a Heatmap in R | ComplexHeatMap tutorial p1.
How to read Cigar Strings in SAM file.
Subset Clusters in Seurat.
Summarized Experiment (se) Object from Bioconductor.
Comparing scRNA-Seq | Suerat Integration Analysis (Brief).
Gene Set Enrichment Analysis| GSEA algorithm.
I Force AI to read research paper 100 times | Text mining in R.
Annotations on Heatmaps | ComplexHeatMap tutorial.
Cancer Somatic Mutation Analysis | MAFtools R Package.
GFF3 File Format | Clearly Explained.
Buying Laptop for Bioinformatics is hard.
TCGA Biomarkers Identification using Machine Learning | Complete Walkthrough.
Why Negative Binomial is used in DESeq2?.
DEG isolation using limma voom | A Rstudio Tutorial.
Oncoprint Walkthrough (Essential).
Data manipulation in R (For Bioinformatics)| R tutorial | For beginner.
Joining Multiple Heatmaps | ComplexHeatMap tutorial.
How to Live Longer? | Disposable Soma Theory.
Youtube Channels I Would Recommend (On Bioinformatics).
R Data Project Best Practice.
16s rRNA Sequencing Analysis | Mothur Walkthrough Part 1.
Why R uses so much memory ? Probably.
How to know if two genes are similar? | Semantic Similarity Explained.
Organoid | How to Make Artificial Organs?.
16s rRNA Sequencing Analysis and Visualization.
We have a problem, you can help.
Can I make scRNA-Seq run faster in Seurat?.
I am impressed with Pop!OS.
No Code Seurat Analysis | Azimuth First Look.
cBioPortal for Human Cancer Genomics and why you should analyze the source data yourself.
Taught by
Liquid Brain
