Skip to main content

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)

	# or predict one DEG-list with bootstrap and permutation
	result = predict.olcr_bootstrap_permutation(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)

Metadata

Release files for PyOVERCAST 1.0.9

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for PyOVERCAST 1.0.9
File Size Uploaded
pyovercast-1.0.9.tar.gz 13.6 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for PyOVERCAST 1.0.9
File Interpreter ABI Platform
pyovercast-1.0.9-py3-none-any.whl Python 3 none any Details

Total release size: 26.7 kB

Release files / pyovercast-1.0.9.tar.gz

Download URL pyovercast-1.0.9.tar.gz
Size 13.6 kB
Tags Source
SHA-256 checksum
How to use checksums
5c63491166d919e911196e3169a34e701e86a54837d4dcaba11413af74d788c7
BLAKE2b-256 checksum
How to use checksums
ea8d42f96bb13143a6b6ab7713ba5355078dc1259815b5d9c3dee449fd4bb2de
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.13.13

Release files / pyovercast-1.0.9-py3-none-any.whl

Download URL pyovercast-1.0.9-py3-none-any.whl
Size 13.1 kB
Tags Python 3
SHA-256 checksum
How to use checksums
d1b4f1aa6a7e3f288f2f49ada5dff217697f3a03e5c01de4aec2fae3ed1dbc99
BLAKE2b-256 checksum
How to use checksums
6f2d2c54420ead1641b98ad0f4dcf937205d30ba66293415caa2c01cc6df67e1
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.13.13

Release history Release notifications | RSS feed

1.0.17

2 release files

1.0.16

2 release files

1.0.15

2 release files

1.0.14

2 release files

1.0.13

2 release files

1.0.12

2 release files

1.0.11

2 release files

1.0.10

2 release files

This release

1.0.9 This release

2 release files

1.0.8

2 release files

1.0.7

2 release files

1.0.6

2 release files

1.0.5

2 release files

1.0.4

2 release files

1.0.3

2 release files

1.0.2

2 release files

1.0.1

2 release files

1.0.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page