Thank You! Truly gold value content. I am in my undergraduate in Biotechnology Engineering. I am doing a project in Bioinformatics. This was truly helpful and educational. The concepts taught are in simple language. Thank you once again!
Thank you for detailed explaination How do set cut off to select top 3 DEG Pathway, Top 2 Highly enriched, from clusterprofiler, And also there there any standard cut to be called significant, How to mark Disease in pathview ( KEGG Plot )
great work sir, kindly explain a little about how did you create this bubble plot if we are using the DAVID database then how do we create the bubble plot diagram of KEGG and GO analysis
Sir one question..sir if in the excel sheet we know 23 DEGs are involved in one of the KEGG pathway then how can we identify what are those DEGs, I mean how can we trace back the DEGs. Also, are the green coloured coxes indicative of DEGs involved in that patwhay?
You can find genes which are involved in your specific pathway then can check from excel sheet it had more than 2 FC value and p value less than 0.05. If yes then that gene can be regarded as DEG.
Bro, please clarify your statement. A low enrichment factor equals the highest number of enrichment genes. From the diagram, I see low enrichment factor bubbles but a low number of genes
Hi, It seems there might be some confusion. Let’s clarify the concepts of enrichment factor and the number of enriched genes: 1. Enrichment Factor: This is a measure used in gene enrichment analysis to determine how significantly a set of genes is overrepresented in a specific biological pathway or process compared to what would be expected by chance. A higher enrichment factor indicates that the genes are more overrepresented. 2. Number of Enriched Genes: This is simply the count of genes in your set that are found in a particular pathway or process. In a typical enrichment analysis bubble plot: • Bubble Size: Often represents the number of enriched genes. • Bubble Position: X and Y axes can represent different parameters such as p-value, enrichment factor, or other statistical measures. Clarifying the Statement A low enrichment factor does not necessarily mean a higher number of enriched genes. Instead: • Low Enrichment Factor: Indicates that the genes are not significantly overrepresented in the pathway, even if a considerable number of genes are involved. • High Enrichment Factor: Indicates that the genes are significantly overrepresented in the pathway, even if the number of genes might be smaller. Interpreting the Diagram If you see bubbles with a low enrichment factor and a low number of genes, it means that those genes are not significantly overrepresented in that particular pathway. Conversely, bubbles with a high enrichment factor, even with a lower number of genes, indicate a significant overrepresentation. In summary, a low enrichment factor does not correlate with a high number of enriched genes. Instead, it suggests a lesser significance of those genes in the specific pathway being analyzed. Feel free to share the diagram if you need a more specific explanation based on the visual data.
Dr it very useful and understanding lecture. THANK YOU Dr But might I know what is the apps that you use because I'm using ShinyGO but the x-axis is fold enrichment not rich factor. Might you help me because I'm little bit confius
Last video i saw in your channel was how to upload transcriptome data. It was only Bcz of ur video, I uploaded my data. Thank you fr tht. But now I would like to know about the different pathways involved in the disease resistance (treatment) with the help of my transcriptome data. The analysis summary submitted by the company was without kegg pathways involved. So now I would like to estimate that. Plz help me in that as I hv limited time to submit of my report.
Thanks for comment, please be informed that there is no hard a fast rule to select KEGG pathway. In other words, disease resistance mechanism can be explained with the help of many possible kegg pathways. You can also choose onr of the many among suitable (with the help of literature)
@@asifmolbio Thanks for the reply. Actually I have gone through few research articles, I guess whether they have analysed kegg pathways for their disease resistance or any other specific treatment. Or they hv gone through kegg portal to identify the possible pathways involved in disease resistance. Plz check the text portion and table of one of the paper in attachment. And plz let me know what they hv actually done.
Thank You! Truly gold value content. I am in my undergraduate in Biotechnology Engineering. I am doing a project in Bioinformatics. This was truly helpful and educational. The concepts taught are in simple language. Thank you once again!
Glad if it’s helping
Can we use this tool as a gene annotation
Very nice explanation
Keep watching
Thank you Prof., it really helps me a lot!!!!!
Glad if it’s helping
Very informative video. Thanks
Glad you like it
very informative video sir..can you also please explain about generating these graphs in R..
It is of great worth, and important. thanks 👍👍
Glad you like it
Well explained
Thanks Dr 👨⚕️
Thank you for detailed explaination How do set cut off to select top 3 DEG Pathway, Top 2 Highly enriched, from clusterprofiler, And also there there any standard cut to be called significant, How to mark Disease in pathview ( KEGG Plot )
How to select genes for qPCR validation in transcriptome/RNA seq data?
th-cam.com/video/PRhHBcjKAKU/w-d-xo.html
How to calculate FC, log2FC, Pvalue, Padj, Up/down genes in RNA seq data using Excel
th-cam.com/video/HH3Mll4W5WE/w-d-xo.html
@@asifmolbio thank you
Thank you so much sir, you made it really easy.
Please make a video on gwas results interpretation as well.
Glad you like it
Thanks for suggesting a great topic, definitely i will
Actually, I'm working on GWAS for salt stress in plant.
great work sir, kindly explain a little about how did you create this bubble plot
if we are using the DAVID database then how do we create the bubble
plot diagram of KEGG and GO analysis
these were genreated by R. You can use iDEP tool also for KEGG analysis.
search about the R package "clusterProfiler"
Thank you Sir. I have one question. If we want to make a heatmap, should we make it on the basis of KEGG or biological pathways of Gene Ontology?
You can choose genes from both
Allah bless you sir.
Allah bless you too
Well explained sir, please make a full video on KEGG for how to generate different type of plots
Thanks, please check the list already videos are uploaded related to this
Sir one question..sir if in the excel sheet we know 23 DEGs are involved in one of the KEGG pathway then how can we identify what are those DEGs, I mean how can we trace back the DEGs. Also, are the green coloured coxes indicative of DEGs involved in that patwhay?
You can find genes which are involved in your specific pathway then can check from excel sheet it had more than 2 FC value and p value less than 0.05. If yes then that gene can be regarded as DEG.
So what is the best pathway should I select from the chart? and depend on which criteria? Need explanation please
Your question has answer in this video
How to select genes for qPCR validation in transcriptome/RNA seq data?
th-cam.com/video/PRhHBcjKAKU/w-d-xo.html
Bro, please clarify your statement. A low enrichment factor equals the highest number of enrichment genes. From the diagram, I see low enrichment factor bubbles but a low number of genes
Hi,
It seems there might be some confusion. Let’s clarify the concepts of enrichment factor and the number of enriched genes:
1. Enrichment Factor: This is a measure used in gene enrichment analysis to determine how significantly a set of genes is overrepresented in a specific biological pathway or process compared to what would be expected by chance. A higher enrichment factor indicates that the genes are more overrepresented.
2. Number of Enriched Genes: This is simply the count of genes in your set that are found in a particular pathway or process.
In a typical enrichment analysis bubble plot:
• Bubble Size: Often represents the number of enriched genes.
• Bubble Position: X and Y axes can represent different parameters such as p-value, enrichment factor, or other statistical measures.
Clarifying the Statement
A low enrichment factor does not necessarily mean a higher number of enriched genes. Instead:
• Low Enrichment Factor: Indicates that the genes are not significantly overrepresented in the pathway, even if a considerable number of genes are involved.
• High Enrichment Factor: Indicates that the genes are significantly overrepresented in the pathway, even if the number of genes might be smaller.
Interpreting the Diagram
If you see bubbles with a low enrichment factor and a low number of genes, it means that those genes are not significantly overrepresented in that particular pathway. Conversely, bubbles with a high enrichment factor, even with a lower number of genes, indicate a significant overrepresentation.
In summary, a low enrichment factor does not correlate with a high number of enriched genes. Instead, it suggests a lesser significance of those genes in the specific pathway being analyzed.
Feel free to share the diagram if you need a more specific explanation based on the visual data.
Thank you for for the explanation
Dr it very useful and understanding lecture. THANK YOU Dr
But might I know what is the apps that you use because I'm using ShinyGO but the x-axis is fold enrichment not rich factor. Might you help me because I'm little bit confius
These were generated in R
But don’t worry use of shiny go is also fine, you can explain with fold enrichment.
It is the same concept to explain using fold enrichment and rich factor?
Yes same
Dr thank you so much.
May god always blessed you
So all my pathway have fdr greater than 0.05 but p value is less can i validate then
P value is highly significant?
@@asifmolbio yes .
Hello sir, I have a doubt. Can I also represent the KEGG pathway as bar chart?
Yes you can use
Last video i saw in your channel was how to upload transcriptome data. It was only Bcz of ur video, I uploaded my data. Thank you fr tht. But now I would like to know about the different pathways involved in the disease resistance (treatment) with the help of my transcriptome data. The analysis summary submitted by the company was without kegg pathways involved. So now I would like to estimate that. Plz help me in that as I hv limited time to submit of my report.
Thanks for comment, please be informed that there is no hard a fast rule to select KEGG pathway. In other words, disease resistance mechanism can be explained with the help of many possible kegg pathways. You can also choose onr of the many among suitable (with the help of literature)
@@asifmolbio Thanks for the reply. Actually I have gone through few research articles, I guess whether they have analysed kegg pathways for their disease resistance or any other specific treatment. Or they hv gone through kegg portal to identify the possible pathways involved in disease resistance. Plz check the text portion and table of one of the paper in attachment. And plz let me know what they hv actually done.
pubmed.ncbi.nlm.nih.gov/31136934/
Text section: 3.6
Table 6
Sir can you put videos on circular rna analysis?
Sure i will upload soon
How to inter pret metabolic data in rice
Depends on specific treatments
hello sir how do you perform KEGG enrichment analysis
iDEP tool
th-cam.com/video/6sNyNYH_v2U/w-d-xo.html
👍
🙏
Very well explain. Truly informatics...
Can I have your mail ID?
asifalikalas@foxmail.com
Abiotic stress
Everyone has their own data and relevant information
very informative video sir..can you also please explain about generating these graphs in R..
Sure i will, keep watching. You can use build KEGG pathways using iDEP web based tools.