bed-annotation 1.2.0

# BED Annotation

[](https://travis-ci.org/vladsaveliev/bed_annotation) [](https://conda.anaconda.org/vladsaveliev)

A tool that assigns gene names to regions in a BED file based on Ensembl genomic features overlap.

### Requirements

Python 3.6, 3.7, 3.8, 3.9, 3.10.

### Installation

` pip install bed_annotation `

### Usage

` bed_annotation INPUT.bed -g hg19 -o OUTPUT.bed `

The script checks each BED region against the Ensembl genomic features database, and writes a BED file in a standardized format with a gene symbol, strand and exon rank in 4-6th columns:

INPUT.bed:

` chr1 69090 70008 chr1 367658 368597 `

OUTPUT.bed:

` chr1 69090 70008 OR4F5 1 + chr1 367658 368597 OR4F29 1 + `

Available genomes (to provide with -g): GRCh37, hg19, hg38.

#### Transcripts order

The piority for choosing transcripts for annotation is the following: - Overlap % with transcript - Overlap % with CDS - Overlap % with exons - Biotype (protein_coding > others > *RNA > *_decay > sense_* > antisense > translated_* > transcribed_*) - TSL (1 > NA > others > 2 > 3 > 4 > 5) - Presence of a HUGO gene symbol - Is cancer canonical - Transcript size

#### Extended annotation

Use –extended option to report extra columns with details on features, biotype, overlapping transcripts and overlap sizes:

` bed_annotation INPUT.bed -g hg19 -o OUTPUT.bed --extended `

OUTPUT.bed:

` ## Tx_overlap_%: part of region overlapping with transcripts ## Exon_overlaps_%: part of region overlapping with exons ## CDS_overlaps_%: part of region overlapping with protein coding regions #Chrom Start End Gene Exon Strand Feature Biotype Ensembl_ID TSL HUGO Tx_overlap_% Exon_overlaps_% CDS_overlaps_% Ori_Fields chr1 69090 70008 OR4F5 1 + capture protein_coding ENST00000335137 NA OR4F5 100.0 100.0 99.7 chr1 367658 368597 OR4F29 1 + capture protein_coding ENST00000426406 NA OR4F29 100.0 100.0 99.7 `

#### Ambuguous annotations

Regions may overlap mltiple genes. The –ambiguities controls how the script resolves such ambiguities

• –ambiguities all – report all reliable overlaps (in order in the “priority” section, see above)

• –ambiguities all_ask – stop execution and ask user which annotation to pick

• –ambiguities best_all (default) – find the best overlap, and if there are several equally good, report all (in terms of the “priority” above)

• –ambiguities best_ask – find the best overlap, and if there are several equally good, ask user

• –ambiguities best_one – find the best overlap, and if there are several equally good, report any of them

Note that the first 4 options might output multiple lines per region, e.g.:

` bed_annotation INPUT.bed -g hg19 -o OUTPUT.bed --extended --ambiguities best_all `

OUTPUT.bed:

` ## Tx_overlap_%: part of region overlapping with transcripts ## Exon_overlaps_%: part of region overlapping with exons ## CDS_overlaps_%: part of region overlapping with protein coding regions #Chrom Start End Gene Exon Strand Feature Biotype Ensembl_ID TSL HUGO Tx_overlap_% Exon_overlaps_% CDS_overlaps_% chr1 69090 70008 OR4F5 1 + capture protein_coding ENST00000335137 NA OR4F5 100.0 100.0 100.0 chr1 367658 368597 OR4F29 1 + capture protein_coding ENST00000426406 NA OR4F29 100.0 100.0 100.0 chr1 367658 368597 OR4F29 1 + capture protein_coding ENST00000412321 NA OR4F29 100.0 100.0 100.0 `

#### Other options

• –coding-only: take only the features of type protein_coding for annotation

• –high-confidence: annotate with only high confidence regions (TSL is 1 or NA, with HUGO symbol, total overlap size > 50%)

• –canonical: use only canonical transcripts to annotate (which to the most part means the longest transcript, by SnpEff definition)

• –short: add only the 4th “Gene” column (outputa 4-col BED file instead of 6-col)

• –output-features: good for debugging. Under each BED file region, also output Ensemble featues that were used to annotate it