Analysis>>Three Color Seeds:|
|I. Phenotype for sesame seeds with different color |
Sample instruction: sesame pericarp with 10 day; white, black
seeds, Each type of seeds with 4 time points (10,20,25,30 days).
|II. Expression analysis among different developmental stages in
sesame white and black seeds|
In this project, we employed TopHat2  to calculate the
expression values of sesame genes among 13 samples. After curation, 22,250 genes, representing 81.958% of all
sesame genes, were detected to express among 13 samples in sesame.
|III. Co-expression analysis by WGCNA|
WGCNA is a comprehensive collection of R functions for performing
various aspects of weighted correlation network analysis. The package
includes functions for network construction, module detection, gene
selection, calculations of topological properties, data simulation,
visualization, and interfacing with external software. Along with the R
package we also present R software tutorials. While the methods
development was motivated by gene expression data, the underlying data
mining approach can be applied to a variety of different settings .
In this project, the members of module were confirmed with the
parameter: kME > 0.7, FPKM > 1 and minimum module size: 30. After
curation, 11,895 genes were used to perform co-expression analysis of
sesame genes among 13 samples.
Note: Click the different color blocks on
the left side of below pictures to get co-expression genes in this
1. Kim D, Pertea G, Trapnell C, Pimentel H, Kelley
R, Salzberg SL. TopHat2: accurate alignment of transcriptomes in the
presence of insertions, deletions and gene fusions.
Genome Biol. 2013; 14(4): R36, doi: 10.1186/gb-2013-14-4-r36.
2. Langfelder P, Horvath S. WGCNA: an R package for weighted
correlation network analysis. BMC Bioinformatics, 2008, 9(1):559, doi: