Local Data Loading

This example loads data from a local file

Load up a local data file

from biolearn.data_library import GeoData
from biolearn.util import get_test_data_file

#Files formatted as described in the standard https://bio-learn.github.io/methylation-standard.html will load correctly.
#Load will search for files names [name]_metadata.csv and [name]_methylation_part0.csv

file_path = get_test_data_file("")
data = GeoData.load_csv(file_path, "example")

data.dnam

/Users/MarcBalestreri/Master Documentation/DEV/Longevity/Biolearn/biolearn/biolearn/data_library.py:229: UserWarning: Found 1 samples in methylation data without metadata entries. Adding empty metadata rows for: GSM3074483
  warnings.warn(

	GSM3074480	GSM3074481	GSM3074482	GSM3074483
cpgSite
cg00000029	0.395	0.499	0.420	0.423
cg00000109	0.821	0.868	0.877	0.841
cg00000155	0.878	0.890	0.894	NaN

Metadata is loaded if available

data.metadata

	Sex	Age	Disease_State
GSM3074480	0.0	25.2	None
GSM3074481	0.0	29.5	COVID
GSM3074482	1.0	39.7	None
GSM3074483	NaN	NaN	NaN

You can now use it like any other Biolearn dataset

data.quality_report().show()

Quality Report Summary

------------------------------------------------
Sample Count: 4
Methylation Sites: 3
Missing Methylation Data: 1 (8.33%)
Samples With High Deviation: 0 (0.00%)
Methylation Sites With Over 20% of Reads Missing: 1 (33.33%)

Notes:
------------------------------------------------
- Your data set includes methylation sites that have over 20% of reads missing. Default imputation may replace the values for all reads from this site with a gold standard.

Estimated memory usage: 225 MB