SigmaP
Python package for Sigma70 promoter Prediction. This package used Sigma70Pred (Patiyal et al. 2022).
Installation
This package can be installed by pip.
pip install sigmap
How to use
First, prepare fasta file containing DNA sequence. Minimum length for prediction is 81nt. Then, calculate probability score by SigmaFactor. Run prediction model by .predict method. Results will be returned as pd.DataFrame.
from sigmap import SigmaFactor
sigma = SigmaFactor()
df_out = sigma.predict('tutorial/example_seq.fa')
| ID | Sequence | Score | Prediction |
|---|---|---|---|
| >Seq_1 | TAGCACGACGATAATATAAACGCAGCAAAAAAAAAAAAAAAAAAAA... | 0.145 | Non-Promoter |
| >Seq_2 | AGCTTGCGTCAATGGGCAAGGTGGGCTTGCATTTGCTTAATAGAAA... | 0.478 | Promoter |
| >Seq_3 | TCGTTTTATTTCTTTTTTCTCCATTGAACTTTCAGTTTCTTTTCTA... | 0.692 | Promoter |
| >Seq_4 | CGCAGCGGGTTTACCCTCTGACCGTTTCTGTTACGAAGGCTTTTTA... | 0.216 | Non-Promoter |
| >Seq_5 | TGCTGCTTGGTCTGTGGGTTGCCGCACAGGTTGCCGGTTCCACCAA... | 0.162 | Non-Promoter |
| >Seq_6 | GAATCCAACTAATGTTGTAAACTGGCAAGGTAATGTCATTAGTCAT... | 0.418 | Promoter |
The input type for sigmap can also be a pd.DataFrame. If you want to convert a FASTA file into a DataFrame, you can use the fasta2df function.
from sigmap import fasta2df
df_seq = fasta2df('tutorial/example_seq.fa')
| Sequence_ID | Sequence |
|---|---|
| >Seq_1 | TAGCACGACGATAATATAAACGCAGCAA |
| >Seq_2 | AGCTTGCGTCAATGGGCAAGGTGGGCTTGCATTTGCTTAATAGAAA... |
| >Seq_3 | TCGTTTTATTTCTTTTTTCTCCATTGAACTTTCAGTTTCTTTTCTA... |
| >Seq_4 | CGCAGCGGGTTTACCCTCTGACCGTTTCTGTTACGAAGGCTTTTTA... |
| >Seq_5 | TGCTGCTTGGTCTGTGGGTTGCCGCACAGGTTGCCGGTTCCACCAA... |
| >Seq_6 | GAATCCAACTAATGTTGTAAACTGGCAAGGTAATGTCATTAGTCAT... |
If the DataFrame contains data with ID and sequence columns, you can directly use it as input for SigmaFactor.
sigma = SigmaFactor()
# input type: pd.DataFrame
df_out = sigma.predict(df_seq)
| ID | Sequence | Score | Prediction |
|---|---|---|---|
| >Seq_1 | TAGCACGACGATAATATAAACGCAGCAAAAAAAAAAAAAAAAAAAA... | 0.145 | Non-Promoter |
| >Seq_2 | AGCTTGCGTCAATGGGCAAGGTGGGCTTGCATTTGCTTAATAGAAA... | 0.478 | Promoter |
| >Seq_3 | TCGTTTTATTTCTTTTTTCTCCATTGAACTTTCAGTTTCTTTTCTA... | 0.692 | Promoter |
| >Seq_4 | CGCAGCGGGTTTACCCTCTGACCGTTTCTGTTACGAAGGCTTTTTA... | 0.216 | Non-Promoter |
| >Seq_5 | TGCTGCTTGGTCTGTGGGTTGCCGCACAGGTTGCCGGTTCCACCAA... | 0.162 | Non-Promoter |
| >Seq_6 | GAATCCAACTAATGTTGTAAACTGGCAAGGTAATGTCATTAGTCAT... | 0.418 | Promoter |
Contact: Goosang Yu (gsyu93@gmail.com)
1 maintainer
Release files for sigmap 1.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| sigmap-1.1.2.tar.gz | 247.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| sigmap-1.1.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 503.5 kB
Release files / sigmap-1.1.2.tar.gz
| Download URL | sigmap-1.1.2.tar.gz |
|---|---|
| Size | 247.3 kB |
| Tags | Source |
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| Size | 256.2 kB |
| Tags | Python 3 |
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