Cptac

This release fixes a bug that dropped all of the LUAD followup data. It also changes the data loaders so that when the followup table includes samples that aren't anywhere else in the dataset (because they're from a different cohort), those samples are kept and not dropped like they were previously.

This release also switches the install to require pandas 1.0.0 or greater.

This release adds the LSCC dataset (password protected). It also includes the DataSet.get_genotype_all_vars function, as well as minor formatting improvements.

This release stops using generated Sample IDs (e.g. S001, S002, etc.) for indexing tables, and instead uses the original CPTAC Patient IDs (e.g. C3L-00078, etc.). Normal samples are indicated by a ".N" appended to the end of the Patient ID (e.g. "C3L-00078.N") in all datasets.

This release also includes updates to the GBM, LUAD, and HNSCC datasets. We also have added a new "followup" table in all datasets besides GBM, which contains followup data for the patients in the cohort.

Finally, this release includes increased access to datasets. The BRCA dataset now has no access restrictions. The GBM and LUAD datasets are both under publication embargo, but no longer require passwords for access.

This release contains the newest GBM data freeze (2.1), and adds the sample immune classification to the CCRCC clinical table. We also fixed a small bug in utils.get_frequently_mutated that was preventing it from working properly with the HNSCC dataset.

This release contains some small bug fixes. We removed duplicate rows from the colon cancer dataset's somatic_mutation dataframe, and renamed a column in the endometrial cancer's derived_molecular dataframe that was causing a column name overlap when joining the derived molecular dataframe to mutations for the JAK1 gene.

This release adds a feature that, in the future, will prevent an old version of the package from loading data versions that were released after that version of the package was released, and it fixes indexing errors in joins with the HNSCC dataset.