Gene function and pathway enrichment analysis is one of most popular class of bioinformatic tools. Currently, the available tools take each gene in one gene set as equal weight, however, actually the essentiality or importance of the genes in one gene set should be different. This point could affect the analysis result greatly and thus should be considered. Given the above observation, here we developed, WEAT v1.0, for weighted gene function and pathway analysis. For any given gene list, WEAT tool is able to:
Click Help to know more.
791 metrics to evaluating the essentiality / importance of genes including 564 for Homo Sapiens
Please read the Analysis Wizard first. If you still got problems, please contact:
r.fan#bjmu.edu.cn (replace # to @)
Follow the steps shown in this tab:
Note that there will be an example data as default value in each field. You can replace them with your own data.
Figure 1. Analysis page.
You will get a result page including brief information of your submission on the top and a statistical table listed as follows. The statistical table including information and operation of gene sets databases where you can have (weighted) enrichment analysis.
Figure 2. Brief result page.
Count column shows the number of genes which is overlapped with the dataset.
Figure 3. Gene and counts page.
Detail column will lead you to the result of the enrichment analysis result. The
Plus button located on each terms' left can be clicked for detailed information including unweighted enrichment method p-value and hit or missed genes.
Figure 4. Detail page.
All the text with blue color can be clicked for an external link.
For each table, you can
search for specific keywords, select hidden
export the table, or show the table for
full screen on the top right of each table.
WEAT Result table, you can also
visualize the result by clicking the button on the top right of the table. After selecting the plot options, click
Plot to see the result and you can also download the vector figure in
SVG format by clicking the
photo button on the top right of the figure.
Figure 5. Visualize page.
|Gene Importance||GIC||None||GIC||Zeng et al.|
|IDF||[Sets]||Inverse Document Frequency (IDF)|
|Protein-Protein Interaction (PPI)||PPI_Degree||Count||STRING|
|Expression||GTEx_smts||None||GTEx||GTEx V8; Tissue Type, area from which the tissue sample was taken.|
|GTEx_smtsd||None||GTEx||GTEx V8; Tissue Type, more specific detail of tissue type|
Q: How to select scores?
A: In general, different essential scores are selected based on the point you are interested in. For example, if you just want investigate the biological process happened in specific tissue, we are suggesting the expression profile scores (like GTEx expression profile score) in specific tissue. Similarly, conservation scores can be used to investigate the evolutionarily conserved terms; Gene importance scores can be selected to have research on essential terms; PPI can be used to investigate hub-gene related sets; And IDF is just a correction of specific category. If you don’t have any purpose and preference of interest, we suggest you to have several tries using different essentiality scores to find out some interesting results and what is the relationship among selected scores, pathways and submitted gene list. In addition, we are now providing a function of selecting multiple scores, that is, merging all selected scores to one, which may get rid of the dilemma of choosing scores.
Q: What is the format of downloaded figure? What is
svg file? How to modify it for publication?
A: All the figure generated from this website can be download in
svg format, which is an Extensible Markup Language (XML)-based vector image format. And all major modern web browsers—including Mozilla Firefox, Internet Explorer, Google Chrome, Opera, Safari, and Microsoft Edge—have SVG rendering support.
Autogenerated figures are not always looking well and hence we need to modify it before publication. For some simple cases like text replacement, you can just open the
svg file in any text editor and the find-replace function will help you. For other harder cases, it is ok to modified it text editor. However, we are suggesting you to use any vector graph editor like Adobe Illustrator. It can also convert the
svg format to any common format you like.