unravel.allen_institute.genetic_tools_atlas.org_samples module#
Use gta_org_samples (gta_os) from UNRAVEL to organize GTA data across samples for batch processing.
- Prereqs:
gta_download(gta_dl) must be run first to download .zarr data at a set resolution.io_convert_img(conv) must be run to convert the .zarr data to TIFF series.
- Inputs:
*.zarr files from
gta_download(gta_dl) at a set resolution (e.g., level 3).
- Outputs:
Root dir: TIFFs/
Directories created based on the fluorescent channel (e.g., red, green, dual).
Relevant sample directories created in each channel directory (e.g., ID_<Image Series ID>).
Sample directories contain ‘green’ and ‘red’ directories with TIFF files for each channel.
Note
Key SpecimenMetadata.csv columns: ‘Image Series ID’ ‘Donor Genotype’ ‘Cargo’
Run from GTA_level_3 directory
- Next steps:
…
Usage:#
gta_os [-d red green] [-i “path/to/SpecimenMetadata.csv”] [-col col1 col2 …] [-o output_dir] [-p sample_prefix] [-v]
- unravel.allen_institute.genetic_tools_atlas.org_samples.org_samples(df, target_dir, prefix, tif_dirs)[source]#
Organize samples into directories based on the SpecimenMetadata DataFrame.
Parameters:#
- dfpd.DataFrame
DataFrame containing ‘Image Series ID’ with the sample IDs to organize.
- target_dirPath
Directory where the sample directories will be created.
- prefixstr
Prefix for sample directories.
- tif_dirslist of str
List of TIFF directory names to organize (e.g., [‘red’, ‘green’]).