5.1 years ago by
Washington University in St. Louis, MO
It's often difficult to get appropriate matched normals for tumor methylation or expression data, as they'd have to be tissue-matched. If you're working with glioblastoma, you can't take a chunk of a patient's healthy brain. Same goes for blood cancers - it's really difficult to separate leukemic cells from non-leukemic cells and get a matched normal from the same patient. (for genomic DNA calls, you can just use non-proximal blood or skin)
Your best bet is to find healthy samples of that tissue type from another source. I'd start with GEO, and would definitely consider pooling the normals to help smooth out differences specific to only one of your normal samples. Also beware of batch effects, since it's likely that different facilities generated the data.