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This is part 1 of step-by-step tutorial of Weighted Gene Co-expression Network Analysis (WGCNA). In this video I demonstrate how to perform Weighted Gene Co-expression Network Analysis (WGCNA) using a RNA-Seq dataset. I go over data manipulation, methods to detect outlier genes and samples in the dataset, normalization, picking soft threshold, identifying modules and visualizing modules as a dendrogram. I hope you find this video helpful! I look forward to your comments in the comment section below! Part 2 of this tutorial: • Weighted Gene Co-expression Network A... Data: https://www.ncbi.nlm.nih.gov/geo/quer... Code: https://github.com/kpatel427/YouTubeT... WGCNA Tutorial: https://horvath.genetics.ucla.edu/htm... Chapters 0:00 Intro 0:40 WGCNA Workflow steps at a glance 1:09 Study Design 1:57 Fetch Data and read data in R 2:56 Get metadata using GEOquery package 5:00 Manipulate expression data 8:53 Quality Control - Remove outlier samples and genes; using goodSampleGenes() 11:27 Detecting outliers using hierarchical clustering 12:22 Detecting outliers using Principal Component Analysis (PCA) 17:16 Data Normalization using vst() from DESeq2 package 20:51 filtering out genes with low counts 22:38 Pick soft threshold 28:48 Identify Modules 31:15 maxBlockSize parameter 33:35 Get module eigengenes 34:34 Visualize modules as dendrogram You can show your support and encouragement by buying me a coffee: https://www.buymeacoffee.com/bioinfor... To get in touch: Website: https://bioinformagician.org/ Github: https://github.com/kpatel427 Email: [email protected] #bioinformagician #bioinformatics #wgcna #coexpressionnetworks #geneexpression #scalefreenetworks #proteinproteininteractionnetworks #sequencing #coverage #samtools #depthofsequencing #samflag #sam #bam #alignment #phred #fasta #fastq #singlecell #10X #ensembl #biomart #annotationdbi #annotables #affymetrix #microarray #affy #ncbi #genomics #beginners #tutorial #howto #omics #research #biology #GEO #rnaseq #ngs