This entry is part five in a series of instructional videos detailing a meta-analysis on eight different human gene expression studies looking at papillary renal cell carcinoma (pRCC). In this installment, I use Partek Genomics Suite to select a group of clustered genes (130 genes) over-expressed in the more severe forms of pRCC.
Rare Cancer Meta-Analysis, pt5.1: Selecting a gene cluster with Partek GS
I then import this list into the networking platforms STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) and Elsevier’s Pathway Studio for biological interpretation. A text file containing the list of clustered genes, along with their normalized fold change scores for each comparison, can be downloaded at this Google Drive link.
Rare Cancer Meta-Analysis, pt5.2: Using STRING to connect our genes of interest
Inspiration for this meta-analysis on papillary kidney cancer came from an upcoming ‘Hackathon’ in May 2018 that brings together researchers, engineers and computer scientists to try to tackle challenging problems in life sciences. This year they are focusing on papillary renal-cell carcinoma type 1 (p1RCC), a disease that accounts for between 15 to 20% of all kidney cancers. Little is known about the genetic basis of sporadic papillary renal-cell carcinoma, and no effective forms of therapy for advanced disease exist.
Rare Cancer Meta-Analysis, pt5.3: Using Pathway Studio to identify biological sub-groups
The opinions expressed during this video are mine and may not represent the opinions of the companies associated with the bioinformatics tools I use in these videos. Any uses of the products described in this demonstration may be uses that have not been cleared or approved by the FDA or any other applicable regulatory body. I do not get direct compensation from the platforms I demonstrate in these videos, but do receive reimbursement for travel when I speak at company-sponsored events.
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Special thanks goes out to the biotech companies Illumina (Correlation Engine and Cohort Analyzer), Partek Inc. (Partek Genomics Suite) and Elsevier (Pathway Studio) for donating their platforms and providing technical assistance for this bioinformatics series.
-Michael Edwards PhD, Bioinfo Solutions LLC