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Depending on the version you use, the screen layouts may be slightly different, however, the basic design and the steps are similar. |
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Log into the caArray Application. Click on the "MANAGE ARRAY DESIGNS" button under "CURATION" on the right side of the page. A new window, "Manage Array Designs", opens. Before uploading the design file, check if your application already has a copy of the design file by the same name. If yes, skip the design file upload and proceed to #Step 2 Experiment Data File Upload. You can use this design file for your experiment. If not, follow Step 1.2 to upload a new design file.
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On clicking the "Save" button, the screen shown in Fig 1.6 opens. Click "Close window and go to Manage Array Designs". The "Manage Array Designs" re-opens, as shown in Fig 1.1b (c). (Please note that for large array design files, the importing process might take a while. An array design can only be used when it is fully imported.)
<gallery widths=450px heights=150px perrow=2 ">
Image
Fig1.6.png| Fig. 1.6 Click on the picture to enlarge
Image:Fig1.1c.png| Fig. 1.1b Click on the picture to enlarge
</gallery>
<font size="4" ><div align="Left">*Step 2
Experiment Data File Upload *</div></font>
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- 1b
Step 2: Experiment Data File Upload
Step 2.1
Click the "CREATE/PROPOSE EXPERIMENT" button under "EXPERIMENT MANAGEMENT" on the left side menu bar. The "Overall Experiment Characteristics" screen
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opens. See Fig 2.2.
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!800px-Fig2.2.png|
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alt="screenshot representing the step"1 - 2
Step 2.2
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Fill out the form with the information shown in Fig 2.2. You can use your own description or use the sample text displayed below. Make sure "Array Designs" field is selected with the right platform (highlighted in blue). Click
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the "Save" button.
Sample Text:
Title: Diffuse large B-cell lymphoma outcome prediction
Description: Diffuse large B-cell lymphoma (DLBCL), the most common lymphoid malignancy in adults, is curable in less than 50% of patients. Prognostic models based on pre-treatment characteristics, such as the International Prognostic Index (IPI), are currently used to predict outcome in DLBCL. However, clinical outcome models identify neither the molecular basis of clinical heterogeneity, nor specific therapeutic targets. We analyzed the expression of 6,817 genes in diagnostic tumor specimens from DLBCL patients who received cyclophosphamide, adriamycin, vincristine and prednisone (CHOP)-based chemotherapy, and applied a supervised learning prediction method to identify cured versus fatal or refractory disease. The algorithm classified two categories of patients with very different five-year overall survival rates (70% versus 12%). The model also effectively delineated patients within specific IPI risk categories who were likely to be cured or to die of their disease. Genes implicated in DLBCL outcome included some that regulate responses to B-cell-receptor signaling, critical serine/threonine phosphorylation pathways and apoptosis. Our data indicate that supervised learning classification techniques can predict outcome in DLBCL and identify rational targets for intervention. **NOTE: Migrated from caArray 1.x, identifier='gov.nih.nci.ncicb.caarray:Experiment:1015897558868337:1'.
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Step 2.3
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The screen shown in Fig 2.3
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opens. Check for the "Experiment has been successfully saved" message. Click
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the "Contacts" tab. Fill the form with your information. You can also edit the contact information from the screen shown in Fig 2.4
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.
!800px-Fig2.3.png|
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alt="screenshot representing the step"
!800px-Fig2.4.png|
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alt="screenshot representing the step"
Step 2.4
. </font> Click on the "Data" tab, then . Then Click on the "Upload New File(s)" button, see Fig 2.5. A new popup window, "Experiment Data Upload" window will appearopens, see Fig 2.6. <gallery widths=450px heights=150px perrow=2">
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!800px-Fig2.5.png| Fig. 2.5 Click on the picture to enlarge
Image:alt="screenshot representing the step" - 5
!Fig2.6.png| Fig. 2.6 Click on the picture to enlarge
</gallery>
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alt="screenshot representing the step" - 6
Step 2.5
. </font> Browse to the location where the sample experiment Data file (caArray_golub-00095_files.zip) was saved and click on the "Upload" button, see Fig 2.6.
; ;<font size="3" >**
Step 2.6
. </font> Wait until the window "Your file upload is complete" is displayed. Click on "OK" (Fig 2.7). Then click on the "Close Window and go to Experiment Data" button as shown in Fig 2.7. *
<gallery widths=450px heights=150px perrow=1">
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!Fig2.7.png| Fig. 2.7 Click on the picture to enlarge
</gallery>
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alt="screenshot representing the step" - 7
Step 2.7
. </font> On the main window shown below (Fig2.8), make sure the column "STATUS" displayed displays the word "Uploaded" for each file. Select the check boxes for all experiment data sets and then click on "Import" button. A new window "Import Options" will appear opens (Fig2.9). Select the first option "Autocreate annotation sets...", then click on the "Import" button. <gallery widths=450px heights=150px perrow=2">
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!630px-Fig2.8.png| Fig. 2.8 Click on the picture to enlarge
Image:Fig2.9.png| Fig. 2.9 Click on the picture to enlarge
</gallery>
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alt="screenshot representing the step" - 8
Step 2.8
. </font> Depending on the speed of the machine and the size of the data, it may take a few minutes for the sample data to be imported. Check the status of the import by Clicking on the "Refresh Status" button (Fig2.10). The initial status will be shown as "In queue" (Fig2.10). When the import is complete, no data will be displayed under the "Manage Data" tab (Fig2.11). Click on the "Imported Data" tab to view imported data file (Fig2.12). If you completed all these steps, Congratulations! You have just successfully created an experiment and deposited your microarray experiment data into the caArray.
<gallery widths=300px heights=200px perrow=3">
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Fig2.10.png| Fig. 2.10 Click on the picture to enlarge
Image:Fig2.11.png| Fig. 2.11 Click on the picture to enlarge
Image:Fig2.12.png| Fig. 2.12 Click on the picture to enlarge
</gallery>
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;<font size="3" >'''Step2.9. </font> To make the experiment data public so people other than you can view your data, click on the "My Experiment Workspace" button (Fig2.13). Locate the experiment of interest on "My experiment Workspace" page. Click on the "Permissions" icon (Fig2.13), the "Experiment Permissions" page will appear (Fig2.14). Click on the "Edit Access Control" button in the left panel.
<gallery widths=450px heights=150px perrow=2">
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Fig2.13.png| Fig. 2.13 Click on the picture to enlarge
Image:Fig2.16.png| Fig. 2.14 Click on the picture to enlarge
</gallery>
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