Data format¶
Response table (--response)¶
The response (y; dependent variable) table records the observed number of mutations, number of mutated samples and the length per genomic element. This table is required for both model (training) and infer (test) sub-commands.
Format: TSV (tab-delimited text) with header. Compressed tables are also accepted.
Fields:
binID: identifier of genomic element and used as key.length: effective length of the element.nMut: number of observed mutations.nSample: number of observed samples with mutations.N: total number of samples.
Example:
| binID | length | nMut | nSample | N |
|---|---|---|---|---|
| TP53.CDS | ||||
| KRAS.CDS | ||||
| … | … | … | … | … |
Feature table (--feature)¶
The feature (X; independent variable) table records genomic features per element.
This table can be large (~10GB) for thousands of features and ~1M genomic elements.
This table is required for both model (training) and infer (test) sub-commands.
Format:
- TSV (or compressed TSV) with header. Loading may be slow for large datasets.
- HDF5 (*.h5 or *.hdf5). The HDF5 must contain key
X, which is the feature table in pandas.DataFrame. Used for fast loading.
Fields:
binID: identifier of genomic element and used as key.- Column 2+: one feature per column. Unique feature names are required.
Example:
| binID | GERP | E128-H3K27ac | … |
|---|---|---|---|
| TP53.CDS | 4.80287 | 1.19475 | … |
| KRAS.CDS | 3.56563 | 2.53435 | … |
Feature importance table (--featImp)¶
The feature importance table records the feature importance score derived from randomized lasso, gradient boosting machine or other algorithms.
This table can be used together with the --featCut argument to specify features kept in the background model.
This table is only used and optional for the model sub-command with method GLM.
If not provided, DriverPower will generate and output it automatically.
Format: TSV (or compressed TSV) with header.
Fields:
name: name of features, should match the column name in feature table.importance: feature importance score.
Example:
| name | importance |
|---|---|
| GERP | 0.3 |
| E128-H3K27ac | 0.5 |
| … | … |
Functional score table (--funcScore)¶
The functional score table records the functional impact score per genomic element.
DriverPower can work with any functional impact score scheme.
This table is only used and optional for the infer sub-command.
Format: TSV (compressed TSV) with header.
Fields:
binID: identifier of genomic element and used as key.- Column 2+: one type of functional impact score per column.
Example:
| binID | CADD | EIGEN | … |
|---|---|---|---|
| TP53.CDS | 4.80287 | 1.19475 | … |
| KRAS.CDS | 3.56563 | 2.53435 | … |