Glittery data analysis and multi-variate analysis for all kinds of data
The app is currently being created to allow the easy and straightforward data analysis of all kinds of data - from the mutant phenotypes to study of natural variation. Although the group developing the app is armpit-deep in Plant Science we are trying to make the App as applicable as possible for the other disciplines of Biology (or even beyond)
With the MVApp, we indend to provide a platform allowing: IN FUTURE => links will be linked to those individual points - directing you to the specific sections
- Fitting the curves (linear / quadratic / exponential / square root) to the time-course data
- Data exploration and removal of outliers
- Analysis of significant differences between the individual genotypes / conditions studied
- Analysis of variance among genotypes / conditions studied
- Perform Correlation analysis between different phenotypes - using the entire data set as well as subsetted data per chosen condition / genotype
- Principal Component Analysis with and without the normalization
- Cluster Analysis based on the chosen traits
All kinds of data can be used. We require that the format of your data will contain the following
- collumn with the genotype (if you use only one - please include the name)
- collumn(s) with the Independent Variable identifier (such as "condition", "position", "experiment number")
- collumn(s) with the Dependent Variables (phenotypes)
Additionally, if you would like to perform fitting the curves to your data, you should also include collumns containing:
- Time - this column has to contain only numeric values
- Sample ID - if you would like to model the change in the phenotype in your individual samples separately, please include Sample ID
The Example dataset would look like this: => IN FUTURE => SCREENSHOT OF THE DATA IN HERE open in EXCEL for example
Methods for selection (include links to the methods - preferably paper that uses it as an example or Wikipedia)
