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.

In this project, we employed TopHat2 [1] 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.

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 [2]. In this project,

Note: Click the different color blocks on the left side of below pictures to get co-expression genes in this experiments

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: 10.1186/1471-2105-9-559.