In the current project, RNASeq analyses were performed on the dataset of the oryzias latipes transcriptome. This dataset contains FASTQ files that control the transcriptome of this fish in four modes:
• 0 concentration
• 10 concentration
• 100 concentration
• and 1000 concentration
from a regulator, with the help of expression profiling by high throughput sequencing and new generation sequencing. FASTQ reads were converted to abundance tables using the Kallisto tool, which implements the pseudo-alignment algorithm. Finally, the abundance tables were combined, and the resulting count table was checked with the help of differential gene expression analysis or DEG Analysis to identify genes with differential expression among them. Differentially expressed genes were marked in red in the Volcano plot. For better separation of groups based on gene expression status, K-means clustering was used. This way, a cluster, and dendrogram were drawn for different groups and genes (100 genes with the highest significance).
