|I. Phenotype for sesame white and black seed and capsule development|
Sample instruction: sesame black, white seeds and capsules, 9 time points (5, 8, 11, 14, 17, 20, 23, 26, 30 days; interval 2 days,
the last interval of 3 days), two biological replicates.
|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 36 samples, including 9 time
points in white capsules, white seeds, black capsules and black seeds
respectively. After curation, 22,095 genes, representing 81.387% of all
sesame genes, were detected to express among 36 samples distributed in sesame black, white seeds and capsules.
|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,
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: