Stability analysis in R | Genotype X Environment interaction | Fixed effect models (AMMI) | GGE plot

Описание: This tutorial covers all the concepts of stability analysis in plant breeding which will be conducted on a multi environment data in order to know the different type of interaction between genotype and environments, here in this video i will show how to do the data analysis of a multi environment trail by using fixed effect models in which random effects will be ignored. The video starts from brief introduction followed by data structure or guidelines in entering data into excel later in the r studio i will suggest all the care and precautions which are taken by the beginners and this will be beginner friendly video because i wont read the script instead i go through step wise in order to make the video more desirable to follow on. The procedure starts with importing dataset into the environment followed by data manipulation and finally data inspection for detecting outliers and handling mess in the dataset, before getting into the data analysis part. In the analysis part i will talk about getting mean values in different combination for preparing two table along with some of the plots like heat map and line graph, next i will show you how to do individual anova with bartlett test and pooled anova based on fixed effect model, later we will get into the stability analysis part where i do cover up concepts like environmental index, ecovalence, shukla’s stability variance, regression based anova (Eberhart and Russell model) followed by some of the non parametric stability concepts like superiority by Linn and Bins, Fox top third criteria, Factor based analysis etc.. The most important aspect of the tutorial is AMMI model here i will fit ammi model and get all kinds of biplots, with that i do talk about weighted average absolute scores concept developed by the author of this package himself where we do fit a new model and get a different kind of plot. In the last part of the video i do cover GGE modelling and model options which are available in this package and talk about ten different kinds of biplots including which won where, basic biplot, ranking of environment, genotypes and evaluation of them etc…..
1) Statistical modelling - https://www.frontiersin.org/articles/...
2) Mixed models - https://onlinelibrary.wiley.com/doi/a...
3) Metan -
https://besjournals.onlinelibrary.wil...
4) Supp. info - https://besjournals.onlinelibrary.wil...
5) Yan and Tinker - https://cdnsciencepub.com/doi/pdf/10....

Data set is there in TNAU stat example of stability analysis
https://drive.google.com/file/d/1bjZW...

Script
https://docs.google.com/document/d/1M...

00:00 - Intro
00:37 Interactions
03:22 statistical models
04:31 metan
05:45 study materials
06:28 original paper
06:41 supplementary material
07:41 Yan and Tinker
08:46 Data structure
11:02 Beginners tips
12:15 packages required
14:24 setting up working directory
14:56 importing data set
17:52 factor conversion
20:37 data inspection
21:18 judging outliers
24:12 Data cleaning
26:07 Data analysis
26:18 Descriptive statistics
28:02 importing table
29:50 Mean performance
34:13 Plotting performance
37:08 Winners
38:24 Ranks
40:01 Ind anova and Bartlett test
45:59 Pooled anova
48:23 Stability analysis
48:45 Environmental index
50:44 Ecovalence
52:05 Shukla’s stability var.
52:57 Regression based model
54:01 Reg. anova
56:22 superiority
58:16 Fox top third criteria
59:28 Factorial
1:02:08 Wrapper function
1:03:20 Ranks based on stab. Ind.
1:05:53 Correlation b/w indexes
1:07:55 AMMI Model
1:11:11 AMMI Biplots
1:21:00 AMMI based stats
1:22:46 WAAS
1:25:43 Cross verify IPCA
1:26:46 GGE Modelling
1:26:51 Model options
1:27:09 svp
1:27:34 svp = environment
1:29:12 Basic biplot
1:30:38 Discriminative vs. representativeness
1:32:23 Ranking of environments
1:33:21 Relationship among environments
1:34:46 svp = genotype
1:36:29 Mean performance vs. stability
1:37:42 Examining a genotype
1:39:06 Ranking of Genotypes
1:40:12 svp = symmetrical
1:41:56 Which Won Where
1:43:11 Examine a environment
1:44:37 Comparison among genotypes
1:46:02 Getting a plot out
1:47:14 Genotypic and Phenotypic correlations