QA Checklist for Cancer Browser

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Revision as of 19:23, 20 January 2010 by Hiram (talk | contribs) (add category tag)
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This is a rough draft for now


QA checklist for tracks on the cancer browser

  • 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. Sometimes X/Y.
    • is the overall genome-wide view color looks too dim or too bright?
    • is the geneset view color looks too dim or too bright?
    • CNV data track : in the whole genome view, is the data looks like copy number data?
      • If there is a gender clinical feature, does the genomic data on X chromosome matches the gender variable?
    • Gene expression data: under whole genome view, is there any batch effect? typical gene expression data track does not show obvious pattern under whole genome view (there are exception such as if we normalized tumor againstnormal samples).
  • Zoom in and out
  • Drill down to base level. Is the transition between the views sensible?
  • Do the graphics make sense?
  • Does the clickthrough to the Genome Browser work?
    • go to the correct spot?
    • correspond with its alignment track in the genome browser?
    • check with featureBits or Table Browser
  • Test mostly using heatmap, but don't forget to toggle over to summary view too.
  • Clinical data. Fewer than 10 default features.
  • Do clinical sorts work? With microarray data? Does genomic data sort work?
  • Do the clinical features make sense? And iss the legend/key sensible?
    • I think the clarity of these labels is really important.
    • Also, in the subgrouping control, after you click on a feature, the feature categories/values will show up, do they make sense?
    • Sometimes, they are just left as numerical (float) numbers (showing as a slider in the UI) , it makes sense for patient age, gi50 sort of features, but not for features like TP53 mutation status kind of features.
  • Stats function: Run one or two statistical tests compare to subgroups under both whole genome and gene set view.
  • Data track documentation: After we commit Chris's help page implementation, is there a help page, and has the date source, pre-processing been documented?