You can start a new task as follows.
- 1. Click the NEW TASK menu button.
By default, your task is identified through your IP address. If you would like to manage your tasks from multiple locations (or in the case of floating IP addresses), you should register an account and sign in using it.
2. Select an organism and related expression data
You can select an organism and related expression data as follows.
- 1. Select an organism.
- 2. Select an array platform.
- 3. Select a suitable set of expression datasets (denoted by GSE accession numbers) by keyword-based search.
- 4. You can see the summary of each expression dataset by pushing the Summary button.
- 5. You can remove an expression dataset by pushing the Remove button. (You can also insert or remove each expression dataset using the checkboxes)
6. You can select a subset of genes by pushing the Gene selection button.
8. You can select a subset of samples (denoted by GSM accession number) after expanding an expression dataset by clicking the GSM button. (After selecting a subset of samples, only the MAS5 algorithm is applicable.)
- 9. After choosing a suitable group of expression datasets, click the Next button.
3. Select a method for expression level calculation
You can select an expression-level calculation method as follows.
- 1. Select an expression-level calculation method.
- 2. Click Next button.
4. Select the target platform
As Affymetrix arrays are one of the most prevalently submitted array platforms to Gene Expression Omnibus, this website basically supports Affymetrix arrays for creating coexpressed gene sets. In the case of analyzing microarray data obtained from other than the supported array platforms, you can create sets of genes denoted by other gene identifiers, e.g., RefSeq transcript ID as follows.
- 1. You can turn on/off the platform conversion. If the platform conversion is turned on, each probe set is mapped onto the selected gene identifiers and processed as such.
- 2. Click Next button.
7. Watch running status
After clicking the Next
button in the previous step, you would see the running status page. It would take from a few minutes to a few hours to coordinate each gene based on the selected expression datasets. You can check the running status by clicking Running Status
menu button afterwards. (Your task is identified through your IP address, if you are not logged in.)
Details of the running status table is as follows.
- 1. You can turn on/off the auto reload option.
- 2. You can set the refresh interval.
- 3. You can see task details.
- 4. Start time of each task.
- 5. End time of each task.
Also you can see other details.
- 1. Expression dataset is being compiled.
- 2. Platform conversion is being processed.
- 3. Coexpression between gene pairs is being calculated.
- 4. Genes are being ordinated.
- 5. Being processed.
- 6. Waiting.
- 7. Done.
- 8. Stopped or failed.
- 9. Not applicable.
- 10. You can stop this task.
- 11. You can see the coordinated result, after all processes are done.
8. Visualize coordinated results and determine an appropriate level of division (example)
This is the most crucial step in COEX. When the coordination process finishes, you can click "See the result
" button placed in the running status table to have the ordinated genes be displayed on a two-dimensional space with a grid. Basically, the genes placed in a same grid cell compose a gene set. You can vary the three parameters, i.e., scale, grid size, and grid position, which jointly influence the gene-set size distribution. The three parameters and how to adjust them are detailed in the following paragraphs.
Brief menu layout explanation
The menu layout of coordination viewer is as follows.
- 1. Grid resizer
- 2. Grid position controller
- 3. Zoom-in/out buttons
- 4. Gene set distribution button
- 5. FuncAssociat button
- 6. Search options
- 7. Scale controller
Changing the level of division
- 1. Grid resizer: Grid size means the size of each grid cell. By sliding up or down the Grid resizer, grid size can be changed. It also possible to insert some value to control its size.
- 2. Grid position controller: You can move the grid. This function can be used for checking the invariability of gene-set size distributions due to slight variations in grid position. To simplify moving task, we provide moving degree as 1/10 times of grid size. In other words, moving same direction 10 timee, then the grid offset will be same with the original one.
- 3. Zoom-in/out buttons: You can zoom in/out of the coordinated result.
- 4. Gene set distribution button: You can click Gene-set size distribution button to view the resulting gene-set size distribution. Details are explained in the following paragraphs.
The resulting gene-set size distribution can be illustrated in a bar chart. The desirable size of each gene set can be specified and the respective numbers of desirably-sized gene sets, smaller ones, and larger ones are displayed side by side. The resulting gene-set size distribution from each parameters setting is saved when you click Gene-set size distribution button. The distributions from all the saved parameters-setting are viewed together. Thus, you can explore a diverse set of parameters settings and compare the resulting gene-set size distributions.
- 1. You can adjust the higher and lower boundaries of desirable gene-set size.
- 2. Illustration of resulting gene-set size distributions. The parameters (cell size, x axis offset, y axis offset) setting is indicatged at the head of each chart.
- 3. After selecting proper level of division, then you can download gene set data file by pressing Save gene set data button.
- 4. You can save chart images by clicking Save chart image button.
An illustration of coordinated result is as follows.
Scale: x4. Grid size: 25. Grid position: unchanged.
- 1. There are 451 gene sets in the above figure. The figure is a trimmed version.
- 2. Click Download gene-set location file button to obtain the coordinates of each gene.
Gene sets characteristics
- You can analysis the degree of each grid cell's property intensity by pressing FuncAssociate button. As its name, this process makes the result by using FuncAssociation algorithm. While this process is being progressed, users can check how much the process has calculated.
- After the progress has been finished, you can check analyzed result per each grid cell's genesets.
Other function of the viewer
7. Scale controller: It means the visualization scale. For example, the distance of ten (in arbitrary measure) between two genes in x1 (times one) scale corresponds to the distance of 20 in x2 (times two) scale.
The larger scale is selected, the more pixels are considered when constructing grid plain. Its illustration is as follows. Red, blud and green rectangles are different nodes but when scale is 1 then they are seen as duplicated one. However, as scale increase, they became seperated one.
- After all data related with geneset, you can filter genesets by using keyword. At the time, user can choose one category in which user want to search
- Once genesets are searched, it is possible to check each geneset's property by cliking the button. The table includes several Gene Ontology properties such as biological process, cellular component and molecularfunction.
9. Download resulting gene set data (example)
After exploring and comparing various parameters settings, you can choose an appropriate level of partition and get the resluting gene set data.
- 1. Click the bar chart having plausible gene set size distribution.
- 2. Select gene set data format (*.gmx or *.gmt).
- 3. Click Save gene-set data button. You might have some problems related to Internet security when trying to download gene set data files using Microsoft's Internet Explorer. You should allow the download by clicking the Information Bar and try again.