Multiple Experiment Comparison
Last updated
Last updated
The "Multiple Experiment Comparison" function collects gene expression profiles from publicly published RNA-seq data in the SRA database, allowing users to query the expression of any gene in all included transcriptome data. In this project, Sapbase have normalized the transcriptomic data using the Transcripts Per Million (TPM) method. TPM is a commonly used metric for gene expression that effectively eliminates the influence of sequencing depth and transcript length, allowing for direct comparisons of expression levels across different samples and genes.
In mode 1, the user can specify any Sapindaceae species to be queried and enter the corresponding Gene ID to query its expression in all transcriptome data.
Example of Gene ID format:
The search results display the expression of genes in different tissues or treatments in the form of study. For different study, the corresponding topics and abstracts of experimental contents are showed. In addition, two links are provided, which can jump to NCBI to browse the detailed introduction of the research project and the detailed information of each sample. Finally, histogram were used to interactively visualize gene expression in each sample, allowing users to obtain gene expression more intuitively.
Demo:
In mode 2, users can specify any Sapindaceae species to be queried and input the corresponding gene set, one gene per line, to query the expression of all genes in all transcriptome data.
Example of Gene set format (Note: one gene per line):
The search results display the expression of genes in different tissues or treatments in the form of study. For different study, the corresponding topics and abstracts of experimental contents are showed. In addition, two links are provided, which can jump to NCBI to browse the detailed introduction of the research project and the detailed information of each sample. Finally, an interactive heatmap is used to display the expression of the gene set. Mouse over to display specific gene expression values.
Demo:
