What is the meaning of percentages in each coordiante? i.e. PC1 13 % and PC 2 4.4 %, How can we define this percentages, when we will have to write a research paper?
Hi Dr. Knight, I am wondering instead of doing relatively abundance, could we normalize all the reads to the same sequence count by divide each sequence count to certain factor (for example, sample 1 got 30000 reads, sample 2 have 60000 sample 3 have 90000 then we divide the first read by 1, second by 2 and third by 3 and end up with each of them have 30000 reads) and from there we can consider the abundance we have as absolute abundance for statistic test. Thank you so much!
I really appreciate your tutorials. Easy to understand for beginners, thank you.
Very clear and concise tutorial. Easy to understand for beginners like me. Thank you!
I really appreciate your tutorials, nicely explained
great videoo... very simple and explainatory
Really good explanations Dan. Keep it up with the good job.
Thank you for your sharing, it is easy to understand.
Why does nobody ever use the variance of the Chao 1 estimator?
Awesome video👍🏻 Thank you!
Terrific video -- very instructive!
Thanks for this awesome video series! :)
Any example: I have two different soil samples. so what would be the alpha and beta diversity in this case.
Thank you! Great lecture
Can you explain what is the diffrent between OTUs and Observed OTUs?
Thank you for the lecture.
I did not really get how changes in composition happen without changes in diversity..? Can someone help?
Thank you for this informative series of presentation. Regarding the alpha diversity, do we need to include the normalized table as input?
What is the meaning of percentages in each coordiante? i.e. PC1 13 % and PC 2 4.4 %, How can we define this percentages, when we will have to write a research paper?
As far as I know, they represent the percentage of the variance explained by each principal component.
@@mohamedrefaat197 Yeh I also know but if the percentage reduce or very low in coordinates what does it indicates
Very clear, thank you!
Hi Dr. Knight,
I am wondering instead of doing relatively abundance, could we normalize all the reads to the same sequence count by divide each sequence count to certain factor (for example, sample 1 got 30000 reads, sample 2 have 60000 sample 3 have 90000 then we divide the first read by 1, second by 2 and third by 3 and end up with each of them have 30000 reads) and from there we can consider the abundance we have as absolute abundance for statistic test. Thank you so much!
Nice tutorial, thank you
Very nice! Thank you
Thank you!
👍
Thank you!