This is a post in the ongoing series, Traversing TCGA. So far we've been able to download, extract, organize and analyze The Cancer Genome Atlas data in Python. However, storing data as an internal variable in Python isn't ideal for all scenarios. Storing data over the long term in a database, such as PostgreSQL, is a… Continue reading Traversing TCGA: Storing Data in PostgreSQL
Month: April 2016
Traversing TCGA: Trying to Find Trends in the Data
This is an edition of Traversing TCGA, an ongoing project analyzing The Cancer Genome Atlas. Update: I've added a Github repository containing the code for this project here! Check it out. In the last post, I started extracting data from the XML files downloaded from TCGA. Now, I'll begin to find trends in the data. I… Continue reading Traversing TCGA: Trying to Find Trends in the Data
Traversing TCGA: Making Sense of the Data Files
This post is part of an ongoing series, Traversing TCGA, in which I analyze data from The Cancer Genome Atlas using Python. Once the download of the data is complete, we end up with a folder full of .xml files containing the clinical data. How do we go from relatively free-from data in hundreds of… Continue reading Traversing TCGA: Making Sense of the Data Files