Principal component analysis in R | PCA for genetic diversity assessment using varimax rotation |

[@Guruprasad_A]

Check the script with dataset in the video description.......

[@joankibet4221]

wow wow wow, so helpful, found it when I was really struggling to run PCA analysis. Thank you

[@ramanathanthusyanthini9342]

I do not know how to express my thankfulness. I had been worrying about PCA. Fortunately, i found your video and started to watch it. Now i am completely clear. Could please do more video . These are really helpful. I highly recommend your teaching to others. Thank god.

[@Guruprasad_A]

Sure.

[@priyankaparihar2217]

you are amazing. Thanku for sharing this information in such easy and detailed manner

[@JyotiKumari-fu6js]

Well explained sir .. and in just simple way thankuh so much

[@obadiahrai4380]

Big thanks to you. This video is a great help to me. 👍👍👍👍

[@ShaoyaZhang-v8g]

excellent explanation!!!

[@nikamarolt5480]

Thank you very much for your explanation.

[@Scholar_shubham]

God type explanation, thank so much sir❤

[@saro4761]

Great Video thanks

[@emilyford7883]

Thank you so much, it's very useful for a beginner.

[@poliyugandhar4614]

Your videos are so simple and informative. Please do the video on QTL mapping. That will be a great help..........

[@deeptitiwari7097]

Thank you for the informative video. Please make videos on STRUCTURE and GWAS analysis also. The knowledge of statistics is required in all the fields, please try to spread it for everyone.

[@deepikachandrasekaran3554]

Sir I am watching your videos regularly..they are very simple and easy to learn... please do video on variability and path analysis using unreplicated data.

[@Guruprasad_A]

Hi Deepika, you can do the path analysis without replication just in a single line using "path_coeff" function in metan.

[@Guruprasad_A]

So please do refer the supplementary information on metan, as I said in previous video on stability analysis.

[@deepikachandrasekaran3554]

Thank you sir.

[@sainayanvlogs1704]

excellent video thank you so mucjj sir please do more such guiding videos iam aphd scholar in genetics AND PLANT BREEDING

[@mdc2scmobiledatacollection199]

Great

[@dattipurushotamarao1603]

👍👍👍👍👍👍

[@poojayadav-mw6dr]

Thank you very much sir :)

[@parihars2849]

How to interpret the screeplot in which PC1 and PC2 don't have any significant difference in their contribution to variation?

[@Guruprasad_A]

Not soo much diversity present in the data.

[@adityapratapsingh6068]

Sir, the same codes used by you in the video would work well when some variables are categorical along with quantitative variables?

[@Guruprasad_A]

If you are using categorical variable, if possible to scale then using scaling (1 to 5 ) or (1 to 10) 1 = Worst, 10= Good.

[@adityapratapsingh6068]

@@Guruprasad_A yes. It is like that. So now is it good to go? Or any modification in coding is needed?

[@Guruprasad_A]

@@adityapratapsingh6068 Yup, you can proceed.

[@pabolutejasree6359]

Sir, how to do analysis for alpha lattice design...??

[@Guruprasad_A]

Try using STAR application.

[@zsliu]

could you please share the cotton data?

[@linuxvegalinuxvega1918]

where can i download the dataset ?

[@Guruprasad_A]

Check the description.

[@mesfinhailemariam9684]

On line19 how can i write the symbol variance that comes before the number 2 ?

[@Guruprasad_A]

I did't get your question?

[@bhumikasinghlodhi6632]

Commendable work. Just a doubt, why you have taken nfactor as 7, rpca

[@Guruprasad_A]

That's based on Eigen value, it's subjective you can select any number of factors as you want.

[@bhumikasinghlodhi6632]

@@Guruprasad_A what is the significance of nfactor.

[@Guruprasad_A]

@@bhumikasinghlodhi6632 See, the main aim of PCA itself is to reduce variables, by using principal components right, where the information present in all the variables will be diverted into principal components, first component 40%, second 20% like that, if we won't select number of factors to be retained everything will be of no use.

[@bhumikasinghlodhi6632]

@@Guruprasad_A Thanks a ton

[@drbantikumar6642]

when running below script >rpca = principal(scd, nfactors = 18, rotate = "varimax", scores = T) shows following error Error in principal(scd, nfactors = 18, rotate = "varimax", scores = T) : could not find function "principal" please resolve

[@Guruprasad_A]

Have you loaded the package "psych" using command library("psych") and try to write the script as I have shown in the video "

[@abigaila.jubilee6329]

Thank you very much for your video sir. I'm already converted the data using log 10 (x+1). Can I still use the options (scipen=100)? Thanks

[@Guruprasad_A]

Yup, no problem.

[@ashwininigut1543]

Where I can get dataset for this analysis ?

[@Guruprasad_A]

It's my own data.

[@golumworks]

If I just use addEllipses =TRUE, what determines the size of those ellipses? Also, if I specify ellipse.type = “confidence”, what confidence level is used to generate the ellipses? I used factoextra.

[@Guruprasad_A]

Based on the PCA scores the ellipse will be added to form a cluster. CI=+- 5%

[@akhildonga6389]

Simply explain the PCA analysis. but have one query about if we have a number of observations (Characters) that are more (2x) than a number of treatments (genotypes) then what changes do?

[@Guruprasad_A]

No changes required.

[@mubangansofu7469]

where is the cottin dataset?

[@Guruprasad_A]

Check the description.

[@ikrambashir8604]

Hello thanks for the very informative video. I have a question. I have data with 2 factors, Genotype and environment (control and stress) and I have almost 40 variables. So, I want to apply PCA. Should I apply PCA separately on control and stress data or should I apply it together? what you suggest???

[@Guruprasad_A]

As per my knowledge it is better to do PCA seperately for both treatment and control.

[@ikrambashir8604]

In Rotated component analysis I am getting this warning. is it normal or should I need to do something > rpca

[@Guruprasad_A]

Warnings are not a problem.

[@VinaySharma-eu6nj]

Dear Sir Thanks for this informative video Can you please, make video on Molecular diversity and STUCTURE analysis using SNP calls in R Best regards Vinay

[@Guruprasad_A]

Sure, I will look forward.

[@VinaySharma-eu6nj]

@@Guruprasad_A thanks sir

[@v.c.jayaramaiah4815]

For those want to learn AMMI and GGE biplot analysis complete basic information is essential for Non Statistical students please guide through it will be of immense help

[@Guruprasad_A]

Ok sir, I will look into it.

[@dattipurushotamarao1603]

Make a video for QTL and meta QTL mapping

[@rojalinbiswal4825]

Here no pca graph

[@Guruprasad_A]

Which graph your referring to?

[@rojalinbiswal4825]

here is scree plot and not eleptical pca plot.

[@Guruprasad_A]

I haven't consider the elliptical plot, because I did't had a categorical variable in the data. You can check the plot in other videos

[@zanvlogs9720]

beautifull but it would have been more if word file of codes were pinned

[@Guruprasad_A]

You just mail me your email address, i will send it

[@Guruprasad_A]

If you have any doubts in the analysis you can contact me through [e-mail]