geneanot 0.4.0

Vertebrates gene annotation based on Ensembl.

Vertebrates Gene Annotation

A Python package that annotates genes and transcripts in vertebrates species based on Ensembl.

Python

Requires python>=3.10

Installing

geneanot is available on PyPI:

pip install geneanot

Running it provides a documentation link:

$ geneanot

Welcome to the vertebrates gene annotation package geneanot.
Please visit https://github.com/yoramzarai/geneanot for documentation.

Requirements

A designated local folder is required to hold the Ensembl annotation file.

Please consult the usage notebook for more information.

Chromosome Data

Some of the methods require the chromosome sequence data. Two chromosome data access modes are supported:

• local - user provides the corresponding chromosome Fasta file
• remote - genenot uses the Ensembl REST API to extract sequence from the chromosome

local access implies faster sequence retrival from the chromosome, whereas remote access requires network connection and implies a slower sequence retrival.

The provided chromosome Fasta file, in case of a local access mode, MUST contain equal number of bps per row in all sequence rows (other than possibly the last row). The chromosome Fasta file can be downloaded from Ensembl (Ensembl chromosome Fasta files contain equal number of bps per sequence row).

Please consult the usage notebook for more information.

Usage

See the usage notebook for a detailed usage description.

Here are few basic usage examples (assuming the code is executed from the .Scripts/ folder). We start with annotating a Homo sapiens gene (Homo sapiens is the default assumed species in geneanot).

Instantiating an annotation object

from pathlib import Path
import geneanot as u

# folder to hold Ensembl annotation file.
Annotation_folder: Path = Path('./../AnnotationDB')

# get/update annotation file
download_done, ensembl_file, local_file = u.update_local_release_to_latest(Annotation_folder, enable_download=True)
annotation_full_file = Annotation_folder / (ensembl_file if download_done else local_file)

# instantiate an annotation object (can use gene name or gene ID) in remote access mode
gA = u.Gene_cls('EGFR', annotation_full_file, verbose=True)

# or - instantiate (can use gene name or gene ID) in local access mode
chrm_fasta_file: str = 'Homo_sapiens.GRCh38.dna_sm.chromosome.7.fa'  # change to your path
gA = u.Gene_cls('EGFR', annotation_full_file, chrm_fasta_file=chrm_fasta_file, verbose=True)

Basic gene annotation

# show gene basic information
gA.info()

# show all transcripts
print(f"\n{gene} contains {len(gA)} transcripts.")
gA.show_all_transcript_IDs()

# gene start and end coordinates
print(f"\nGene start = {gA.gene_start:,}, gene end = {gA.gene_end:,}")

print(f"\n{gene=} encoded in chromosome {gA.chrm} on the {'negative' if gA.rev else 'positive'} DNA strand.")

# the various gene attributes printed from the above commands are also available via gA
print(gA.gene_name, gA.gene_ID, gA.gene_desc, gA.gene_type, gA.gene_ver, gA.rev, gA.chrm, gA.gene_start, gA.gene_end, len(gA.transcripts_info), sep='\n')

Transcript annotation

transcript_id: str = 'ENST00000275493'

# show transcript basic information
gA.transcript_info(transcript_id, verbose=True)

# the transcript features are accessible via gA.transcripts_info[transcript_id], for example
t_info = gA.transcripts_info[transcript_id]
print(t_info['transcript_name'], t_info['transcript_v_id'], t_info['transcript_ver'])

Transcript and RNA tables

The transcript table lists the exons and introns in the transcript. Following is a partial transcript table of the transcript ENST00000275493.

The RNA table lists the exons in the RNA, and in case of protein-coding transcripts, maps the ORF and the AAs to the exons. Following is the RNA table of the transcript ENST00000275493.

Here mRNA_NT_region gives the mRNA bp count, ORF_NT_region gives the ORF bp count, ORF_AA_region gives the protein AA count, and next_exon_frame_alignment gives the codon phase (i.e., number of bps required in the next exon to complete the last codon in the current exon).

# Transcript table
df = gA.exon_intron_map(transcript_id)
display(df)

# the transcript table can be written to excel, CSV or HTML file
gA.exon_intron_map_to_csv(transcript_id, './../Reports/transcript_table.csv')
gA.exon_intron_map_to_excel(transcript_id, './../Reports/transcript_table.xlsx', usr_desc={"Description": "Transcript table", "Transcript": transcript_id})
gA.exon_intron_map_to_html(transcript_id, './../Reports/transcript_table.html')

# RNA table
df = gA.exon_map(transcript_id)
display(df)

# this table can also be written to excel, CSV or HTML file
gA.exon_map_to_csv(transcript_id, './../Reports/mRNA_table.csv')
gA.exon_map_to_excel(transcript_id, './../Reports/mRNA_table.xlsx', usr_desc={"Description": "mRNA table", "Transcript": transcript_id})
gA.exon_map_to_html(transcript_id, './../Reports/mRNA_table.html')

Sequences

pre_RNA_seq = gA.seq(transcript_id).upper()
print(f"pre-RNA contains {len(pre_RNA_seq):,} bps.")

rna_seq = gA.rna(transcript_id).upper()
print(f"\nrna:\n{rna_seq}\n{len(rna_seq):,} bps.")

orf_seq = gA.ORF(transcript_id).upper()
print(f"\norf:\n{orf_seq}\n{len(orf_seq):,} bps.")

aa_seq = gA.AA(transcript_id)
print(f"\nprotein:\n{aa_seq}\n{len(aa_seq):,} AAs.")

utr5_seq = gA.UTR5(transcript_id).upper()
print(f"\n5'UTR:\n{utr5_seq}\n{len(utr5_seq):,} bps.")

utr3_seq = gA.UTR3(transcript_id).upper()
print(f"\n3'UTR=\n{utr3_seq}\n{len(utr3_seq):,} bps.")

exon_seq, seq_info = gA.exon_intron_seq('Exon', 5, transcript_id)
print(f"\nExon =\n{exon_seq}\n{seq_info}")

intron_seq, seq_info = gA.exon_intron_seq('Intron', 5, transcript_id)
print(f"\nIntron =\n{intron_seq}\n{seq_info.upper()}")

# A modified transcript
use_exon_list: list[int] = [1, 3]  # exon numbers to use
use_intron_list: list[int] = [2]  # intron numbers to use
m_seq = gA.modified_transcript(use_exon_list, use_intron_list, transcript_id)
print(f"\nA modified transcript containing exons {', '.join(map(str,use_exon_list))} and introns {', '.join(map(str,use_intron_list))} contains {len(m_seq.upper()):,} bps.")

Queries

# query the start and stop codon positions in the chromosome and in the RNA
# --------------------------------------------------------------------------
start_codon_info, stop_codon_info = gA.start_and_stop_codons_pos(transcript_id)

# query the start and end ORF positions in the exons
# --------------------------------------------------
orf_start_end_info = gA.orf_start_and_end_exon_info(transcript_id)

# query a chromosome position
chrm_pos: int = 55_157_663
# ---------------------------
chrm_info = gA.chrm_pos_info(transcript_id, chrm_pos)
print(chrm_info)

# query a RNA position
rna_pos: int = 685
# ----------------
chrm_info = gA.rna_pos2chrm_info(transcript_id, rna_pos)
print(chrm_info)

# map a chromosome position to the RNA position
chrm_pos: int = 55_211_628 
# ------------------------
rna_pos = gA.chrm_pos2rna_pos(transcript_id, chrm_pos)

# map a RNA position to the chromosome position
rna_pos: int = 685
# ----------------
chrm_p = gA.rna_pos2chrm_pos(transcript_id, rna_pos)
print(f"{rna_pos=} --> {chrm_p=}")

# query an exon position
exon_number: int = 7
bp_index_in_exon: int = 47
# -------------------
info = gA.exon_nt_info(transcript_id, exon_number, bp_index_in_exon)
print(info)

# query the RNA segment (UTR, ORF) of an exon position
exon_number: int = 28
bp_index_in_exon: int = 400
# --------------------------
exon_segment_info := gA.exon_nt_segment(transcript_id, exon_number, bp_index_in_exon)

# query an amino-acid position
aa_number: int = 163
# ------------------
aa_info = gA.aa_exon_info(transcript_id, aa_number)
print(aa_info)

# query an AA variant given a DNA variant
ref_allele, var_allele, chromosome_pos = 'G', 'C', 55_152_609
# ------------------------------------------------------------
aa_var = gA.DNA_SNP_mut_to_AA_mut(ref_allele, var_allele, chromosome_pos, transcript_id)
print(f"chr{gA.chrm}:{chromosome_pos}:{ref_allele}>{var_allele} --> {aa_var=}")

# query (all) DNA variants given an AA variant
aa_var: str = 'C231S'
# -------------------
dna_all_muts = gA.AA_mut_to_DNA_SNP_mut(aa_var, transcript_id)
print(f"{aa_var=} corresponds to the following DNA variants:")
for i, (codon, var_info) in enumerate(dna_all_muts.items(), start=1):
    print(f"{i}. {codon=}, {var_info}")

Annotating multiple genes (faster instantiation)

# parse annotation file into annotation dataframes
gff3_dfs = u.ensembl_gff3_df(annotation_full_file)  

# now instantiate with the annotation dataframes (faster)
# can instantiate in local mode by providing chrm_fasta_file (see above)
g_a1 = u.Gene_cls('EGFR', gff3_dfs)
g_a1.info()
g_a2 = u.Gene_cls('BRCA1', gff3_dfs)
g_a2.info()
g_a3 = u.Gene_cls('IDH1', gff3_dfs)
g_a3.info()
...

Annotating other vertebrates species

# Example: Mus_musculus

species: str = 'mus_musculus'  # required for non Homo sapiens species.

# The suggest annotation file name (used to extract annotation signature, which is required next)
suggest_annotation_file_name, _, release_n = u.suggested_annotation_file_name(species=species)

# update/download annotation file
download_done, ensembl_file, local_file = u.update_local_release_to_latest(
    Annotation_folder, 
    enable_download=True, 
    gff3_pattern=suggest_annotation_file_name.replace(release_n, 'XXX'),
    species=species)

annotation_full_file = Annotation_folder / (ensembl_file if download_done else local_file)

# instantiate annotation class (can use gene name or gene ID) in remote mode (see above for a local mode example)
gA = u.Gene_cls('ENSMUSG00000017167', annotation_full_file, species=species, verbose=True)
gA.info()

print(f"\n{gene} contains {len(gA)} transcripts.")
gA.show_all_transcript_IDs()

transcript_id: str = 'ENSMUST00000103109'
df = gA.exon_map(transcript_id)
print(df.to_string())

# protein sequence
aa_seq = gA.AA(transcript_id)
print(f"\nprotein:\n{aa_seq}\n{len(aa_seq):,} AAs.")

References

• Ensembl
• Ensembl GFF3 File Format
• GFF3 Format
• Ensembl REST