fastaframes 1.1.0

A very simple fasta file parser.

FastaFrames

FastaFrames is a python package to convert between FASTA files and pandas DataFrames.

Usage

To install fastaframes use pip:

pip install fastaframes

Reading a FASTA file

from fastaframes import to_df

fasta_df = to_df(data='example.fasta')

Writing a FASTA file

from fastaframes import to_fasta

to_fasta(data=fasta_df, output_file='output.fasta')

Columns:

• db: Database from which the sequence was retrieved. db is 'sp' for UniProtKB/Swiss-Prot and 'tr' for UniProtKB/TrEMBL.
• unique_identifier: The primary accession number of the UniProtKB entry.
• entry_name: The entry name of the UniProtKB entry.
• protein_name: The recommended name of the UniProtKB entry as annotated in the RecName field. For UniProtKB/TrEMBL entries without a RecName field, the SubName field is used. In case of multiple SubNames, the first one is used. The 'precursor' attribute is excluded, 'Fragment' is included with the name if applicable.
• organism_name: The scientific name of the organism of the UniProtKB entry.
• organism_identifier: The unique identifier of the source organism, assigned by the NCBI.
• gene_name: The first gene name of the UniProtKB entry. If there is no gene name, OrderedLocusName or ORFname, the GN field is not listed.
• protein_existence: The numerical value describing the evidence for the existence of the protein.
• sequence_version: The version number of the sequence.
• protein_sequence: The protein amino acid sequence.

Example FASTA file:

>sp|A0A087X1C5|CP2D7_HUMAN Putative cytochrome P450 2D7 OS=Homo sapiens OX=9606 GN=CYP2D7 PE=5 SV=1
MGLEALVPLAMIVAIFLLLVDLMHRHQRWAARYPPGPLPLPGLGNLLHVDFQNTPYCFDQ

Will produce the following:

	db	unique_identifier	entry_name	protein_name	organism_name	organism_identifier	gene_name	protein_existence	sequence_version	protein_sequence
0	sp	A0A087X1C5	CP2D7_HUMAN	Putative cytochrome P450 2D7	Homo sapiens	9606.0	CYP2D7	5.0	1.0	MGLEALVPLAMIVAIFLLLVDLMHRHQRWAARYPPGPLPLPGLGNLLHVDFQNTPYCFDQ