xomics.load_dataset

xomics.load_dataset(name='Overview', n=None, random=False, drop_na=False)[source]

Loads protein benchmarking datasets.

Parameters:

  • name (str) – The name of the loaded dataset, from the ‘Dataset’ column in the overview table.

  • n (Optional[int]) – Number of proteins, selected by index. If None, the whole dataset will be returned.

  • random (bool) – If True, n randomly selected proteins will be chosen.

  • drop_na (bool) – If True, rows containing any missing value will be dropped.

Returns:

DataFrame with quantifiaction values for n samples, typically proteins or genes. Rows correspond samples and columns to quantifications over different conditions

Return type:

df_q

Examples

>>> import xomics as xo
>>> df_lfq = xo.load_dataset(name="PROT_DEMYELINATION", n=100)

Notes

  • The name of df_q can be specified for the respective quantification type such as ‘df_lfq’ for label free quantification (lfq) commonly used in mass-sepctromatery (MS)-based use_cases

See also