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README.md

genomepy

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Easily install and use genomes in Python and elsewhere!

The goal is to have a simple and straightforward way to download and use genomic sequences. Currently, genomepy supports UCSC, Ensembl and NCBI.

asciicast

Pssst, hey there! Is genomepy not doing what you want? Does it fail? Is it clunky? Is the documentation unclear? Have any other ideas on how to improve it? Don't be shy and let us know!

Installation

Genomepy works with Python 2.7 and Python 3.4+. You can install it via bioconda:

$ conda install genomepy

Or via pip:

$ pip install genomepy

If you install via pip, you will have to install some dependencies, only if you want to use the annotation download feature. You will have to install the following utilities and make sure they are in your PATH:

  • genePredToBed
  • genePredToGtf
  • bedToGenePred
  • gtfToGenePred
  • gff3ToGenePred

You can find the binaries here.

Plugins and indexing

By default genomepy generates a file with chromosome sizes and a BED file with gap locations (Ns in the sequence).

For some genomes genomepy can download blacklist files (generated by the Kundaje lab). This will only work when installing these genomes from UCSC. Enable this plugin to use it.

$ genomepy plugin enable blacklist

You can also create indices for some widely using aligners. Currently, genomepy supports:

Note 1: these programs are not installed by genomepy and need to be installed seperately for the indexing to work.

Note 2: the index is based on the genome, annotation (splice sites) is currently not taken into account.

You can configure the index creation using the genomepy plugin command (see below)

Configuration

By default genomes will be saved in ~/.local/share/genomes.

To change the configuration, generate a personal config file:

$ genomepy config generate
Created config file /home/simon/.config/genomepy/genomepy.yaml

To set the default genome directory to /data/genomes for instance, edit ~/.config/genomepy/genomepy.yaml and change the following line:

genome_dir: ~/.local/share/genomes/

to:

genome_dir: /data/genomes

The genome directory can also be explicitly specified in both the Python API as well as on the command-line.

Usage

Command line

Usage: genomepy [OPTIONS] COMMAND [ARGS]...

Options:
  --version   Show the version and exit.
  -h, --help  Show this message and exit.

Commands:
  config     manage configuration
  genomes    list available genomes
  install    install genome
  plugin     manage plugins
  providers  list available providers
  search     search for genomes

Install a genome.

The most important command. The most simple form:

$ genomepy  install hg38 UCSC 
downloading...
done...
name: hg38
fasta: /data/genomes/hg38/hg38.fa

Here, genomes are downloaded to the directory specified in the config file. To choose a different directory, use the -g option.

$ genomepy install sacCer3 UCSC -g ~/genomes/
downloading from http://hgdownload.soe.ucsc.edu/goldenPath/sacCer3/bigZips/chromFa.tar.gz...
done...
name: sacCer3
local name: sacCer3
fasta: /home/simon/genomes/sacCer3/sacCer3.fa

You can use a regular expression to filter for matching sequences (or non-matching sequences by using the --no-match option). For instance, the following command downloads hg38 and saves only the major chromosomes:

$ genomepy  install hg38 UCSC -r 'chr[0-9XY]+$'
downloading from http://hgdownload.soe.ucsc.edu/goldenPath/hg38/bigZips/hg38.fa.gz...
done...
name: hg38
local name: hg38
fasta: /data/genomes/hg38/hg38.fa
$ grep ">" /data/genomes/hg38/hg38.fa
>chr1
>chr10
>chr11
>chr12
>chr13
>chr14
>chr15
>chr16
>chr17
>chr18
>chr19
>chr2
>chr20
>chr21
>chr22
>chr3
>chr4
>chr5
>chr6
>chr7
>chr8
>chr9
>chrX
>chrY

By default, sequences are soft-masked. Use -m hard for hard masking.

The chromosome sizes are saved in file called <genome_name>.fa.sizes.

For genomes from UCSC and Ensembl, you can choose to download gene annotation files with the --annotation option. These will be saved in BED and GTF format.

$ genomepy  install hg38 UCSC --annotation

Finally, in the spirit of reproducibility all selected options are stored in a README.txt. This includes the original name and download location.

Manage plugins.

Use genomepy plugin list to view the available plugins.

$ genomepy plugin list
plugin              enabled
bowtie2             
bwa                 
gaps                *
gmap                
hisat2              
minimap2            
sizes               *

Enable plugins as follows:

$ genomepy plugin enable bwa hisat2
Enabled plugins: bwa, gaps, hisat2, sizes

And disable like this:

$ genomepy plugin disable bwa
Enabled plugins: gaps, hisat2, sizes

Search for a genome.

$ genomepy search Xenopus
NCBI	Xenopus_tropicalis_v9.1	Xenopus tropicalis; DOE Joint Genome Institute
NCBI	ViralProj30173	Xenopus laevis endogenous retrovirus Xen1; 
NCBI	Xenopus_laevis_v2	Xenopus laevis; International Xenopus Sequencing Consortium
NCBI	v4.2	Xenopus tropicalis; DOE Joint Genome Institute
NCBI	Xtropicalis_v7	Xenopus tropicalis; DOE Joint Genome Institute
Ensembl	JGI 4.2	Xenopus

Only search a specific provider:

$ genomepy search tropicalis -p UCSC
UCSC	xenTro7	X. tropicalis Sep. 2012 (JGI 7.0/xenTro7) Genome at UCSC
UCSC	xenTro3	X. tropicalis Nov. 2009 (JGI 4.2/xenTro3) Genome at UCSC
UCSC	xenTro2	X. tropicalis Aug. 2005 (JGI 4.1/xenTro2) Genome at UCSC
UCSC	xenTro1	X. tropicalis Oct. 2004 (JGI 3.0/xenTro1) Genome at UCSC

Note that searching doesn't work flawlessly, so try a few variations if you don't get any results. Search is case-insensitive.

List available providers

$ genomepy providers
Ensembl
UCSC
NCBI

List available genomes

You can constrain the genome list by using the -p option to search only a specific provider.

$ genomepy genomes -p UCSC
UCSC	hg38	Human Dec. 2013 (GRCh38/hg38) Genome at UCSC
UCSC	hg19	Human Feb. 2009 (GRCh37/hg19) Genome at UCSC
UCSC	hg18	Human Mar. 2006 (NCBI36/hg18) Genome at UCSC
...
UCSC	danRer4	Zebrafish Mar. 2006 (Zv6/danRer4) Genome at UCSC
UCSC	danRer3	Zebrafish May 2005 (Zv5/danRer3) Genome at UCSC

Manage configuration

List the current configuration file that genomepy uses:

$ genomepy config file
/home/simon/.config/genomepy/genomepy.yaml

To show the contents of the config file:

$ genomepy config show
# Directory were downloaded genomes will be stored
genome_dir: ~/.local/share/genomes/

plugin:
 - gaps
 - sizes

To generate a personal configuration file (existing file will be overwritten):

$ genomepy config generate
Created config file /home/simon/.config/genomepy/genomepy.yaml

Local cache.

Note that the first time you run genomepy search or list the command will take a long time as the genome lists have to be downloaded. The lists are cached locally, which will save time later. The cached files are stored in ~/.cache/genomepy and expire after 7 days. You can also delete this directory to clean the cache.

From Python

>>> import genomepy
>>> for row in genomepy.search("GRCh38"):
...     print("\t".join(row))
...
UCSC	hg38	Human Dec. 2013 (GRCh38/hg38) Genome at UCSC
NCBI	GRCh38.p10	Homo sapiens; Genome Reference Consortium
NCBI	GRCh38	Homo sapiens; Genome Reference Consortium
NCBI	GRCh38.p1	Homo sapiens; Genome Reference Consortium
NCBI	GRCh38.p2	Homo sapiens; Genome Reference Consortium
NCBI	GRCh38.p3	Homo sapiens; Genome Reference Consortium
NCBI	GRCh38.p4	Homo sapiens; Genome Reference Consortium
NCBI	GRCh38.p5	Homo sapiens; Genome Reference Consortium
NCBI	GRCh38.p6	Homo sapiens; Genome Reference Consortium
NCBI	GRCh38.p7	Homo sapiens; Genome Reference Consortium
NCBI	GRCh38.p8	Homo sapiens; Genome Reference Consortium
NCBI	GRCh38.p9	Homo sapiens; Genome Reference Consortium
Ensembl	GRCh38.p10	Human
>>> genomepy.install_genome("hg38", "UCSC", genome_dir="/data/genomes")
downloading...
done...
name: hg38
fasta: /data/genomes/hg38/hg38.fa
>>> g = genomepy.Genome("hg38", genome_dir="/data/genomes")
>>> g["chr6"][166502000:166503000]
tgtatggtccctagaggggccagagtcacagagatggaaagtggatggcgggtgccgggggctggggagctactgtgcagggggacagagctttagttctgcaagatgaaacagttctggagatggacggtggggatgggggcccagcaatgggaacgtgcttaatgccactgaactgggcacttaaacgtggtgaaaactgtaaaagtcatgtgtatttttctacaattaaaaaaaATCTGCCACAGAGTTAAAAAAATAACCACTATTTTCTGGAAATGGGAAGGAAAAGTTACAGCATGTAATTAAGATGACAATTTATAATGAACAAGGCAAATCTTTTCATCTTTGCCTTTTGGGCATATTCAATCTTTGCCCAGAATTAAGCACCTTTCAAGATTAATTCTCTAATAATTCTAGTTGAACAACACAACCTTTTCCTTCAAGCTTGCAATTAAATAAGGCTATTTTTAGCTGTAAGGATCACGCTGACCTTCAGGAGCAATGAGAACCGGCACTCCCGGCCTGAGTGGATGCACGGGGAGTGTGTCTAACACACAGGCGTCAACAGCCAGGGCCGCACGAGGAGGAGGAGTGGCAACGTCCACACAGACTCACAACACGGCACTCCGACTTGGAGGGTAATTAATACCAGGTTAACTTCTGGGATGACCTTGGCAACGACCCAAGGTGACAGGCCAGGCTCTGCAATCACCTCCCAATTAAGGAGAGGCGAAAGGGGACTCCCAGGGCTCAGAGCACCACGGGGTTCTAGGTCAGACCCACTTTGAAATGGAAATCTGGCCTTGTGCTGCTGCTCTTGTGGGGAGACAGCAGCTGCGGAGGCTGCTCTCTTCATGGGATTACTCTGGATAAAGTCTTTTTTGATTCTACgttgagcatcccttatctgaaatgcctgaaaccggaagtgtttaggatttggggattttgcaatatttacttatatataatgagatatcttggagatgggccacaa

The genomepy.Genome() method returns a Genome object. This has all the functionality of a pyfaidx.Fasta object, see the documentation for more examples on how to use this.

Known issues

There might be issues with specific genome sequences. Sadly, not everything (naming, structure, filenames) is always consistent on the provider end. Let me know if you encounter issues with certain downloads.

Todo

  • Linking genomes to NCBI taxonomy ID
  • Optionally: Ensembl bacteria (although there might be better options specifically for bacterial sequences)

Citation

If you use genomepy in your research, please cite it: 10.21105/joss.00320.

Getting help

If you want to report a bug or issue, or have problems with installing or running the software please create a new issue. This is the preferred way of getting support. Alternatively, you can mail me.

Contributing

Contributions welcome! Send me a pull request or get in touch.

License

This module is licensed under the terms of the MIT license.

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