sigmap 1.1.0

SigmaP: Python package for predicting sigma70 promoter in Escherichia coli K-12

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 ([e-mail])