Weighted Gene Co-expression Network Analysis (WGCNA) Detailed Workflow Steps | Bioinformatics 101

In this video I continue discussing Weighted Gene Co-expression Network Analysis (WGCNA) by going into the details of workflow steps and providing intuition behind each step.
I hope you find this video helpful! I look forward to your comments in the comment section below!
WGCNA resources:
1. bmcbioinformatics.biomedcentr...
2. horvath.genetics.ucla.edu/htm...
3. academic.oup.com/bib/article/...
Chapters:
0:00 Intro
0:58 Quick recap on basic idea behind WGCNA
1:54 WGCNA Workflow Steps
2:49 Basic Idea behind constructing networks
4:55 Step 1: Construct a weighted correlation matrix
6:40 Hard Thresholding (Unweighted Networks)
7:59 Soft Thresholding (Weighted Networks)
9:10 What is a scale-free network?
11:47 Step 2: Identify modules
12:38 Merge similar modules
13:41 Step 3a: Correlate modules with phenotypes/traits
14:58 Step 3b: Identify driver genes
You can show your support and encouragement by buying me a coffee:
www.buymeacoffee.com/bioinfor...
To get in touch:
Website: bioinformagician.org/
Github: github.com/kpatel427
Email: [e-mail]
#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

[@user-vu5uh3rk3u]

Breaks up a complex topic into manageable steps and adequately explains them! She is on point, a great resource for beginners and advanced users!

[@satheatul1]

Thank you for more detailed and better explanation. Waiting for the next and most important hands on tutorial.

[@harshasatuluri4540]

I think I only asked for this video for one person u made. Once again THANK YOU, MADAM

[@mocabeentrill]

I'm currently busy with this analysis. Thank you for the clarity on the concepts involved. You're the best!

[@markedmond1462]

As always, excellent. I am but a simple clinician and your videos are helping me so much with my thesis. Can’t wait for the tutorial video; I am currently trying to do a pathway analysis correlating HPV gene expression in HPV positive HNSCC. Thank you!

[@user-db5yx3fi4u]

It's really clearly explained!

[@atthegates92]

Great explanation, tyvm!

[@loriscapria6757]

incredibly helpful!

[@vinaykumarnandigam1163]

Thank you Magician. Please keep doing.

[@sijinakp2744]

Thank you mam, i was waiting for this video

[@farhanarnob]

Thanks!

[@juliangrandvallet5359]

THANKS!!!!!

[@andreas.chrysostomou]

Looking forward for the hands on tutorial

[@qingchen2510]

Thank you very much for the excellent explanation. I am going to perform the WGCNA analysis as well. I have two questions hopefully you could provide some advice. 1. I only have 11 samples with 4 conditions, I really want to perform WGCNA analysis on the data. Does the performance decrease a lot? 2. The soft threshold given is 1. I don't know if this is due to the fewer sample numbers. I wonder if I could change the power to a higher value? Appreciate any suggestions.

[@anushasunkum8484]

HI, thank you for the very clear explanation. i have a request. Can you do for label free quantified proteomics data, where there are many missing values for genes between different variables

[@shadabali9476]

Your videos are really nice and very informative... I have one suggestion
Please keep your voice level slightly high in next videos.

[@ruchigupta5655]

How to make a scatter plot between GS AND MM

[@tulikabhardwaj484]

Please make a video on mixomics package

[@grsbiosciences]

I don't have many traits like weight , cholesterol to correlate. I have only normal and disease traits. What I can try with wgcna

[@user-eh1qy6ff4g]

Ma’am, I've to do co-expressed modules and hub genes identification. Can you please provide me with the whole code and workflow required?

[@priyadarshinithirunavukkar1445]

Thank you. Does the trait has to be continuous variable to relate the module with the trait. I have a data in which I categorize the brain region gene expression as prenatal and postnatal.

[@Bioinformagician]

Not necessarily, discrete traits can also be associated with modules. I have spoken about this here - ruclips.net/video/mzXIxjPr_Mc/видео.html

[@wesleyeliasbheringbarrios8108]

Thank you very much for the video! I will perform a RNAseq experiment and i'd like to know your opinion about the number of replicates and the sequencing depth. I was planning to sequence 5 replicates at 100M reads / samples (paired end). My goal is to discover driver genes for a particular pathway. With 5 replicates would it be possible to do this analysis with high accuracy, or is it better to do it with 10 replicates and half of the depth? My organism doesn't have its genome sequenced.

[@Bioinformagician]

Is it a eukaryotic or a prokaryotic organism?

[@ramachandran8106]

Hi, very nice video. Thanks.
Can you teach GWAS and post Gwas
Video tutorial.please....

[@Bioinformagician]

Will surely plan a tutorial on it soon! :)

[@prachimishra9929]

Hello mam, i am working on WGCNA in R and i am facing error in soft threshold power function. I am using gene_count.matrix txt file of RNA-seq, please help me to resolve the error .
sft = powers = c(c(1:6), seq(from = 18, to=30, by=2))
pickSoftThreshold(datExpr0, powerVector = powers, verbose = 5)
pickSoftThreshold: will use block size 1435.
pickSoftThreshold: calculating connectivity for given powers...
..working on genes 1 through 1435 of 31169
Error in { : task 1 failed - "'x' has a zero dimension."

[@Bioinformagician]

Are you sure your datExpr0 is in the right format?