PyOVERCAST
A Python package for mining key transcription factors from transcriptome data.
Installation
pip install numpy pandas statsmodels scipy seaborn matplotlib PyOVERCAST
Usage
from PyOVERCAST import clinks, predict
if __name__ == '__main__':
# download TF-target set, only need to run once!!!
clinks.download_data()
# list available TF-target set
sets_names = clinks.get_sets(species='Homo sapiens')
print(sets_names)
# list avaiable TFs
tfs_codes = clinks.get_tfs(set_name='human_hocomoco_CLink_rci4_1w_0.8')
print(tfs_codes)
# get targets
targets = clinks.get_targets(set_name='human_hocomoco_CLink_rci4_1w_0.8', tf='NFKB1_HUMAN.H11MO.1.B')
print(targets)
# predict one DEG-list
result = predict.olcr(set_names=['human_jaspar_CLink_rci4_1w_0.8', 'human_hocomoco_CLink_rci4_1w_0.8'], list_file='./PyOVERCAST_data/input_deg-list.txt', win=30, thread_n=16)
# or predict one DEG-list with bootstrap
result = predict.olcr_bootstrap(set_names=['human_jaspar_CLink_rci4_1w_0.8', 'human_hocomoco_CLink_rci4_1w_0.8'], list_file='./OVERCAST_data/input_deg-list.txt', win=30, bs_n=1000, thread_n=32)
# save result to text file
result.to_csv('output.txt', sep='\t', index=False, encoding='utf-8')
# plot OLC matrix
predict.plot_olc(set_names=['human_jaspar_CLink_rci4_1w_0.8', 'human_hocomoco_CLink_rci4_1w_0.8'], list_file='./PyOVERCAST_data/input_deg-list.txt', tf='MA0844.2_XBP1', win=30)
# plot OLC matrix
predict.plot_olc(set_names=['human_jaspar_CLink_rci4_1w_0.8', 'human_hocomoco_CLink_rci4_1w_0.8'], list_file='./PyOVERCAST_data/input_deg-list.txt', tf='MA0844.2_XBP1', win=30)
# plot fitted 3D U-surface
predict.plot_contour(set_names=['human_jaspar_CLink_rci4_1w_0.8', 'human_hocomoco_CLink_rci4_1w_0.8'], list_file='./PyOVERCAST_data/input_deg-list.txt', tf='MA0844.2_XBP1', win=30)
Release files for PyOVERCAST 1.0.6
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pyovercast-1.0.6.tar.gz | 13.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pyovercast-1.0.6-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 25.8 kB
Release files / pyovercast-1.0.6.tar.gz
| Download URL | pyovercast-1.0.6.tar.gz |
|---|---|
| Size | 13.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
bc5224cdf27a3b6fe2b6292d10e5f82a19f90cc9bc47086eb0b3e7a042c61d9e
|
|
BLAKE2b-256 checksum How to use checksums |
257c0377ac3f5872ec4aa6ced8e0ea8c9e08870441cd22fe258b1ec1ba0dcebe
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.13
|
Release files / pyovercast-1.0.6-py3-none-any.whl
| Download URL | pyovercast-1.0.6-py3-none-any.whl |
|---|---|
| Size | 12.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
0c30c04745d1c71d970fc9afb6f450247b5bb1336b3fdcad3bb39dcbc8b06c1d
|
|
BLAKE2b-256 checksum How to use checksums |
6a9f82fda2963f7bc5887b1523f17e3602277543d80d461c1aea3adad13c7108
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.13
|