goodorfs 1.0

Introduction

GOODORFS is a tool to classify open reading frames into coding and noncoding

It takes as input a fasta file representing the entire genome. It then finds all potential open reading frames, and then for each, calculates the Energy Density Profile from the amino acid frequency.

To install GOODORFS,

git clone https://github.com/deprekate/goodorfs.git
cd goodorfs
python3 setup.py install

To run GOODORFS simply provide the path to a fasta file. The default output is the same format as Glimmers LONGORFS program, in order to serve as a drop in replacement. The columns are: orf_id, start_location, stop_location, frame, a bunch of zeros as filler

$ goodorfs.py tests/NC_001416.fna
00001     191     736  +2   0.000
00002     711    2636  +3   0.000
00003    2633    2839  +2   0.000
00004    3270    2830  -1   0.000
00005    2836    4437  +1   0.000
00006    5095    4604  -2   0.000
00007    4283    5737  +2   0.000
...

Additionally GOODORFS can also output the nucleotide sequences in fasta format for use in other applications:

$ good-orfs.py -Y fna tests/NC_001416.fna | head
>NC_001416_orf1 [START=191] [STOP=736]
ATGGAAGTCAACAAAAAGCAGCTGGCTGACATTTTCGGTGCGAGTATCCGTACCATTCA...
>NC_001416_orf2 [START=711] [STOP=2636]
GTGAATATATCGAACAGTCAGGTTAACAGGCTGCGGCATTTTGTCCGCGCCGGGCTTCG...
>NC_001416_orf3 [START=2633] [STOP=2839]
ATGACGCGACAGGAAGAACTTGCCGCTGCCCGTGCGGCACTGCATGACCTGATGACAGG...
>NC_001416_orf4 [START=3270] [STOP=2830]
GTGCATGGCCACACCTTCCCGAATCATCATGGTAAACGTGCGTTTTCGCTCAACGTCAA...
...