QA Checklist for Cancer Browser: Difference between revisions
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***Are there repeated features, or features with meaningless info (ie gender in an Ovarian tumor dataset) | ***Are there repeated features, or features with meaningless info (ie gender in an Ovarian tumor dataset) | ||
*** Stats function: Run one or two statistical tests. Keep in mind that you have to designate subgroups in order for the function to work | *** Stats function: Run one or two statistical tests. Keep in mind that you have to designate subgroups in order for the function to work | ||
* Data track documentation: | * Data track documentation: it's bad. The details page should have some minor info, like wrangler, date, number of samples, and a list of features in no particularly useful order | ||
[[Category:Browser QA]] | [[Category:Browser QA]] |
Revision as of 17:18, 26 July 2010
This is a rough draft for now
QA checklist for tracks on the cancer browser
- Tracks can have both Chromosomes and Genesets as display options, check both
- Occasionally tracks will work in one but not the other, but give no warning of this (or only a little tiny on on their details pages)
- Speed. Does it take a long time for a dataset to load? Indicating there is no down-sampled data table, or data table is not indexed.
- Is there data on every chromosome? Any missing sections should be accounted for.
- Do the colors look okay? Are there any visual issues with the track?
- Does the clickthrough to the Genome Browser worK?
- Test mostly using heatmap, but remember to check Boxplot and Proportions modes as well
- Clinical data: Features and Feature Settings:
- How many features are on by default? Too many will cause feature names not to display
- Does sorting features work? Does sorting features properly sort the heatmap?
- Use features to sanity-check data. Does gender match with X/Y, that sort of thing
- View Feature info by using the blue button next to the Feature graph. Here, check for:
- Feature values: do they match what gets graphed? Do they make sense? Sometimes non-numerical values get made into a numerical scale, for example.
- Do the Feature short labels match up with their names?
- Are there repeated features, or features with meaningless info (ie gender in an Ovarian tumor dataset)
- Stats function: Run one or two statistical tests. Keep in mind that you have to designate subgroups in order for the function to work
- Data track documentation: it's bad. The details page should have some minor info, like wrangler, date, number of samples, and a list of features in no particularly useful order