PCA Biplot Analysis with Genotype Names using R | RStudio | Plant Breeding | Agri Research

  Рет қаралды 6,254

Geeky Researcher

Geeky Researcher

Жыл бұрын

#pca #datavisualization #plantbreeding #pcawithgenotype
We have provided a demo of the procedure to plot a PCA biplot with genotype names inside the plot.
Link to R code: www.geekyresearcher.com/data-...

Пікірлер: 23
@anikasur1680
@anikasur1680 Ай бұрын
how to do pca biplot analysis using fact of minor library and fact of install Library... Where is this vedio??...would you please provide me the link
@positivevibes978
@positivevibes978 11 ай бұрын
Can you explain quantitative genetics sir. With example. Metroglyph analysis, pca analysis, diallel
@geekyresearcher
@geekyresearcher 11 ай бұрын
I will try to upload this sooner
@shilpasharma5213
@shilpasharma5213 3 ай бұрын
Thank you sir, but i am not getting correct total variation of PCs written in the axes of biplot? and Why you have not done scaling?
@nirmalrajrajendran3707
@nirmalrajrajendran3707 28 күн бұрын
Scaling depends on the dataset. So if you have wife range then go for scaling. I am not exactly what type of error is you are getting
@LishaIshal
@LishaIshal Жыл бұрын
When plant pathology net 2023 will be discussed
@geekyresearcher
@geekyresearcher Жыл бұрын
Shankar is still figuring out the video. Expecting it to be soon
@afeezoluniyishittuirri7645
@afeezoluniyishittuirri7645 3 ай бұрын
Good lecture. thanks. I tried to run the script but having this error, can you please be of help Error in loadNamespace(j = 3.4.0 is required
@geekyresearcher
@geekyresearcher 3 ай бұрын
Thank you for writing. I think you have an outdated cli package. Kindly update it and try again. Execute this code install.packages("cli")
@afeezoluniyishittuirri7645
@afeezoluniyishittuirri7645 3 ай бұрын
SAME ERROR namespace ‘cli’ 3.1.1 is already loaded, but >= 3.4.0 is required@@geekyresearcher
@bolagamravikumar7092
@bolagamravikumar7092 10 ай бұрын
This very informative but let's it conclude with how to export data from r studio please
@geekyresearcher
@geekyresearcher 10 ай бұрын
Thank you. Will include this in future videos. Regards
@bolagamravikumar7092
@bolagamravikumar7092 10 ай бұрын
Thank you for your response. Actually I have followed your last video and I got good results too, now I wolud like export data if possible help me out this Note.: Instead of word Dim. I try to use pc but it is not working
@geekyresearcher
@geekyresearcher 10 ай бұрын
I am not sure yet. I will try to get you a result.@@bolagamravikumar7092
@geekyresearcher
@geekyresearcher 10 ай бұрын
install.packages("writexl") library(writexl) my_pca
@bolagamravikumar7092
@bolagamravikumar7092 10 ай бұрын
@@geekyresearcher thank you I will try
@dr.sureshkumar2097
@dr.sureshkumar2097 Жыл бұрын
Net ars 2023 discussion
@keyachaudhari3152
@keyachaudhari3152 Жыл бұрын
NET 2023 results kab tak aayega sir
@geekyresearcher
@geekyresearcher Жыл бұрын
Shankar is preparing.. hold still
@chagiyar687
@chagiyar687 28 күн бұрын
What if I have 200+ variable?
@nirmalrajrajendran3707
@nirmalrajrajendran3707 28 күн бұрын
Do you mean 200+ traits
@chagiyar687
@chagiyar687 27 күн бұрын
@@nirmalrajrajendran3707 Treatments: There are three different treatments (for example, young sungkai leaves, medium-aged sungkai leaves, and old sungkai leaves). Repeats: Each treatment is repeated three times. Data: Each treatment has one column containing 255 compound data points (results from GC-MS analysis. Then, there are 255 compound data points that I need to plot into PCA.
@geekyresearcher
@geekyresearcher 27 күн бұрын
Can you send a screenshot of your data structure to researchergeeky@gmail.com
StatQuest: Principal Component Analysis (PCA), Step-by-Step
21:58
StatQuest with Josh Starmer
Рет қаралды 2,8 МЛН
Vivaan  Tanya once again pranked Papa 🤣😇🤣
00:10
seema lamba
Рет қаралды 34 МЛН
Principal Component Analysis Tutorial & Interpretation Using R
16:39
Stanford's FREE data science book and course are the best yet
4:52
Python Programmer
Рет қаралды 673 М.
Fixing RAG with GraphRAG
15:04
Vivek Haldar
Рет қаралды 6 М.
BIO178 Week8Lab PCA
9:30
Lani Gleason
Рет қаралды 9 М.
Principal components analysis in R
26:49
Hefin Rhys
Рет қаралды 157 М.
Principal Component Analysis (PCA) in R (presence-absence data)
8:00
Just One Bird's Opinion
Рет қаралды 9 М.
Principal Component Analysis (PCA)
13:46
Steve Brunton
Рет қаралды 367 М.