genomepy 0.14.0

Genes and genomes at your fingertips

genomepy: genes and genomes at your fingertips

genomepy is designed to provide a simple and straightforward way to download and use genomic data. This includes (1) searching available data, (2) showing the available metadata, (3) automatically downloading, preprocessing and matching data and (4) generating optional aligner indexes. All with sensible, yet controllable defaults. Currently, genomepy supports Ensembl, UCSC, NCBI and GENCODE.

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!

Table of Contents

1. Installation
2. Quick usage
3. Plugins and indexing
4. Configuration
5. Usage
   • Command line
   • Python
6. Known issues
7. Getting help
8. Citation
9. Contributing
10. License

Installation

genomepy requires Python 3.7+

You can install genomepy via bioconda:

$ conda install -c bioconda genomepy

Or via pip:

$ pip install genomepy

Or via git:

$ git clone https://github.com/vanheeringen-lab/genomepy.git
$ cd genomepy

# optional:
$ conda env create -n genomepy -f environment.yml
$ conda activate genomepy

$ pip install -e .

With Pip installation, you will have to install additional dependencies, and make them available in your PATH.

To read/write bgzipped genomes you will have to install tabix.

If you want to use gene annotation features, you will have to install the following utilities:

• genePredToBed
• genePredToGtf
• bedToGenePred
• gtfToGenePred
• gff3ToGenePred

You can find the binaries here.

Quick usage

1. Find your genome: $ genomepy search zebrafish

Console output:

name      provider    accession           tax_id     annotation    species        other_info
GRCz11    Ensembl     GCA_000002035.4     7955       ✓             Danio rerio    2017-08-Ensembl/2018-04
 ^
 Use name for genomepy install

2. Install your genome (with annotation): $ genomepy install --annotation GRCz11 --provider ensembl

The default genomes directory: ~/.local/share/genomes/

Plugins and indexing

By default, genomepy generates support files including a genome index, chromosome sizes and gap locations (Ns in the sequence).

For some model organisms, genomepy can download a genome blacklist (generated by the Kundaje lab). Blacklists are only available for these model organisms when downloaded from UCSC, and for the human and mouse genomes. Enable the blacklist plugin to use it.

$ genomepy plugin enable blacklist

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

• bowtie2
• bwa
• gmap
• hisat2
• minimap2
• star

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

Note 2: splice-aware indexing (required for e.g. RNA-seq) is performed by STAR and Hisat2. Splice-aware indexing requires the annotation to be downloaded as well. You will receive a warning if indexing is performed without annotation for these aligners.

Note 3: STAR can further improve mapping to (novel) splice junctions by indexing again (see 2-pass mapping mode in the STAR manual). The second pass is not supported by genomepy.

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

Configuration

To change the default configuration, generate a personal config file:

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

Genome location

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

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

genomes_dir: ~/.local/share/genomes/

to:

genomes_dir: /data/genomes

The genome directory can still be overwritten via the command-line.

Compression

Optionally genome FASTA files can be saved using bgzip compression. This means that the FASTA files will take up less space on disk. To enable this use the flag --bgzip on the command line, or add the following line to your config file:

bgzip: True

Most tools are able to use bgzip-compressed genome files. One notable exception is bedtools getfasta. As an alternative, you can use the faidx command-line script from pyfaidx which comes installed with genomepy.

Usage

Command line

All functions come with a short explanation when appended with --help.

$ genomepy --help
Usage: genomepy [OPTIONS] COMMAND [ARGS]...

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

Commands:
  annotation  show 1st lines of each annotation
  clean       remove provider data
  config      manage configuration
  genomes     list available genomes
  install     install a genome & run active plugins
  plugin      manage plugins
  providers   list available providers
  search      search for genomes

Install a genome.

Find the name of your desired genome:

$ genomepy search xenopus tro
name                       provider    accession           tax_id    annotation     species               other_info
                                                                      n r e k
Xenopus_tropicalis_v9.1    Ensembl     GCA_000004195.3       8364        ✓          Xenopus tropicalis    2019-04-Ensembl/2019-12
xenTro1                    UCSC        na                    8364     ✗ ✗ ✗ ✗       Xenopus tropicalis    Oct. 2004 (JGI 3.0/xenTro1)
xenTro2                    UCSC        na                    8364     ✗ ✓ ✓ ✗       Xenopus tropicalis    Aug. 2005 (JGI 4.1/xenTro2)
xenTro3                    UCSC        GCA_000004195.1       8364     ✗ ✓ ✓ ✗       Xenopus tropicalis    Nov. 2009 (JGI 4.2/xenTro3)
xenTro7                    UCSC        GCA_000004195.2       8364     ✓ ✓ ✗ ✗       Xenopus tropicalis    Sep. 2012 (JGI 7.0/xenTro7)
xenTro9                    UCSC        GCA_000004195.3       8364     ✓ ✓ ✓ ✗       Xenopus tropicalis    Jul. 2016 (Xenopus_tropicalis_v9.1/xenTro9)
Xtropicalis_v7             NCBI        GCF_000004195.2       8364        ✓          Xenopus tropicalis    DOE Joint Genome Institute
Xenopus_tropicalis_v9.1    NCBI        GCF_000004195.3       8364        ✓          Xenopus tropicalis    DOE Joint Genome Institute
UCB_Xtro_10.0              NCBI        GCF_000004195.4       8364        ✓          Xenopus tropicalis    University of California, Berkeley
ASM1336827v1               NCBI        GCA_013368275.1       8364        ✗          Xenopus tropicalis    Southern University of Science and Technology
 ^
 Use name for genomepy install

You can search by genome name (case-insensitive), taxonomy ID or assembly accession ID. Additionally, you can limit the search result to one provider with -p/--provider.

$ genomepy search 8364 -p ucsc
name                    provider    accession           tax_id    annotation     species               other_info
                                                                   n r e k
xenTro1                 UCSC        na                    8364     ✗ ✗ ✗ ✗       Xenopus tropicalis    Oct. 2004 (JGI 3.0/xenTro1)
xenTro2                 UCSC        na                    8364     ✗ ✓ ✓ ✗       Xenopus tropicalis    Aug. 2005 (JGI 4.1/xenTro2)
xenTro3                 UCSC        GCA_000004195.1       8364     ✗ ✓ ✓ ✗       Xenopus tropicalis    Nov. 2009 (JGI 4.2/xenTro3)
xenTro7                 UCSC        GCA_000004195.2       8364     ✓ ✓ ✗ ✗       Xenopus tropicalis    Sep. 2012 (JGI 7.0/xenTro7)
xenTro9                 UCSC        GCA_000004195.3       8364     ✓ ✓ ✓ ✗       Xenopus tropicalis    Jul. 2016 (Xenopus_tropicalis_v9.1/xenTro9)
 ^
 Use name for genomepy install

Let's say we want to download a Xenopus tropicalis genome from UCSC.

If you are interested in the gene annotation as well, you might want to check which gene annotation suits your needs. Because we're looking at UCSC, and there are several options for us to choose from. In the search results, n r e k denotes which UCSC annotations are available. These stand for ncbiRefSeq, refGene, ensGene and knownGene, respectively.

We can quickly inspect these with the genomepy annotation command:

$ genomepy annotation xenTro9 -p ucsc
12:04:41 | INFO | UCSC ncbiRefSeq
chr1    genomepy        transcript      133270  152620  .       -       .       gene_id "LOC100490505"; transcript_id "XM_012956089.1";  gene_name "LOC100490505";
chr1    genomepy        exon    133270  134186  .       -       .       gene_id "LOC100490505"; transcript_id "XM_012956089.1"; exon_number "1"; exon_id "XM_012956089.1.1"; gene_name "LOC100490505";
12:04:45 | INFO | UCSC refGene
chr1    genomepy        transcript      193109390       193134311       .       +       .       gene_id "pias2"; transcript_id "NM_001078987";  gene_name "pias2";
chr1    genomepy        exon    193109390       193109458       .       +       .       gene_id "pias2"; transcript_id "NM_001078987"; exon_number "1"; exon_id "NM_001078987.1"; gene_name "pias2";
12:04:49 | INFO | UCSC ensGene
chr1    genomepy        transcript      133270  152620  .       -       .       gene_id "ENSXETG00000030302.2"; transcript_id "ENSXETT00000061673.2";  gene_name "ENSXETG00000030302.2";
chr1    genomepy        exon    133270  134186  .       -       .       gene_id "ENSXETG00000030302.2"; transcript_id "ENSXETT00000061673.2"; exon_number "1"; exon_id "ENSXETT00000061673.2.1"; gene_name "ENSXETG00000030302.2";

Here we can see that the refGene annotation has actual HGNC gene names, so lets go with this annotation. This differs between genomes, so be sure to check!

Copy the name returned by the search function to install. For UCSC we can also select the annotation type.

$ genomepy install xenTro9 --UCSC-annotation refGene

Since we did not specify the provider here, genomepy will use the first provider it can find with xenTro9. Since we learned in genomepy search that only UCSC uses this name, it will be UCSC. We can also specify genomepy to use UCSC by giving it the provider name with -p/--provider:

$ genomepy install xenTro9 -p UCSC
Downloading genome from http://hgdownload.soe.ucsc.edu/goldenPath/xenTro9/bigZips/xenTro9.fa.gz...
Genome download successful, starting post processing...

name: xenTro9
local name: xenTro9
fasta: /data/genomes/xenTro9/xenTro9.fa

Next, the genome is downloaded to the directory specified in the config file. To choose a different directory, use the -g/--genomes_dir option:

$ genomepy install sacCer3 -p UCSC -g /path/to/my/genomes
Downloading genome from http://hgdownload.soe.ucsc.edu/goldenPath/sacCer3/bigZips/chromFa.tar.gz...
Genome download successful, starting post processing...

name: sacCer3
local name: sacCer3
fasta: /path/to/my/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 -p 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, or -m none for no masking.

You can choose to download gene annotation files with the --annotation option. These will be saved in (gzipped) BED and GTF format.

$ genomepy  install hg38 -p UCSC --annotation

All selected options are stored in a README.txt. This includes the original name, download location and other genomepy operations (such as regex filtering and time).

Other providers (any URL/local files)

To facilitate the downloading of genomes not supported by either NCBI, UCSC, or Ensembl, genomes can also be downloaded directly from any URL, by specifying URL as the provider:

$ genomepy install -p url https://research.nhgri.nih.gov/hydra/download/assembly/\Hm105_Dovetail_Assembly_1.0.fa.gz

Similarly, if you have a local fasta file, you can install this using the filepath and specifying Local as the provider. This installs the genome under the filename of the URL/filepath, but can be changed with the --localname option.

If you add the --annotation flag, genomepy will search the (remote) directory for an annotation file as well. Should this fail, you can also add a URL to the annotation with --URL-to-annotation with the URL provider, or a filepath with --Local-path-to-annotation with the Local provider:

$ genomepy install -p local /path/to/genome.fa --Local-path-to-annotation /path/to/gene.annotation.gtf

Manage plugins.

Use genomepy plugin list to view the available plugins.

$ genomepy plugin list
plugin              enabled
bowtie2             
bwa                 
gmap                
hisat2              
minimap2            
star
blacklist

Enable plugins as follows:

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

And disable like this:

$ genomepy plugin disable bwa
Enabled plugins: hisat2

Search for a genome.

You can search by genome name (case-insensitive), taxonomy ID or assembly accession ID. Additionally, you can limit the search result to one provider with -p/--provider.

$ genomepy search xenopus tropicalis
name                       provider    accession           tax_id    annotation     species               other_info
                                                                      n r e k
Xenopus_tropicalis_v9.1    Ensembl     GCA_000004195.3       8364        ✓          Xenopus tropicalis    2019-04-Ensembl/2019-12
xenTro1                    UCSC        na                    8364     ✗ ✗ ✗ ✗       Xenopus tropicalis    Oct. 2004 (JGI 3.0/xenTro1)
xenTro2                    UCSC        na                    8364     ✗ ✓ ✓ ✗       Xenopus tropicalis    Aug. 2005 (JGI 4.1/xenTro2)
xenTro3                    UCSC        GCA_000004195.1       8364     ✗ ✓ ✓ ✗       Xenopus tropicalis    Nov. 2009 (JGI 4.2/xenTro3)
xenTro7                    UCSC        GCA_000004195.2       8364     ✓ ✓ ✗ ✗       Xenopus tropicalis    Sep. 2012 (JGI 7.0/xenTro7)
xenTro9                    UCSC        GCA_000004195.3       8364     ✓ ✓ ✓ ✗       Xenopus tropicalis    Jul. 2016 (Xenopus_tropicalis_v9.1/xenTro9)
Xtropicalis_v7             NCBI        GCF_000004195.2       8364        ✓          Xenopus tropicalis    DOE Joint Genome Institute
Xenopus_tropicalis_v9.1    NCBI        GCF_000004195.3       8364        ✓          Xenopus tropicalis    DOE Joint Genome Institute
UCB_Xtro_10.0              NCBI        GCF_000004195.4       8364        ✓          Xenopus tropicalis    University of California, Berkeley
ASM1336827v1               NCBI        GCA_013368275.1       8364        ✗          Xenopus tropicalis    Southern University of Science and Technology
 ^
 Use name for genomepy install

Only search a specific provider:

$ genomepy search tropicalis -p ucsc
name                    provider    accession           tax_id    annotation     species               other_info
                                                                   n r e k
xenTro1                 UCSC        na                    8364     ✗ ✗ ✗ ✗       Xenopus tropicalis    Oct. 2004 (JGI 3.0/xenTro1)
xenTro2                 UCSC        na                    8364     ✗ ✓ ✓ ✗       Xenopus tropicalis    Aug. 2005 (JGI 4.1/xenTro2)
xenTro3                 UCSC        GCA_000004195.1       8364     ✗ ✓ ✓ ✗       Xenopus tropicalis    Nov. 2009 (JGI 4.2/xenTro3)
xenTro7                 UCSC        GCA_000004195.2       8364     ✓ ✓ ✗ ✗       Xenopus tropicalis    Sep. 2012 (JGI 7.0/xenTro7)
xenTro9                 UCSC        GCA_000004195.3       8364     ✓ ✓ ✓ ✗       Xenopus tropicalis    Jul. 2016 (Xenopus_tropicalis_v9.1/xenTro9)
 ^
 Use name for genomepy install

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

List available providers

$ genomepy providers
GENCODE
Ensembl
UCSC
NCBI
Local
URL

List available genomes

You can constrain the genome list by using the -p/--provider option to search only a specific provider. Additionally, you can get the absolute --size of each genome (this option slows down the search).

$ genomepy genomes -p UCSC
name                    provider    accession          tax_id     annotation     species                                     other_info
                                                                   n r e k
ailMel1                 UCSC        GCF_000004335.2      9646      ✓ ✗ ✓ ✗       Ailuropoda melanoleuca                      Dec. 2009 (BGI-Shenzhen 1.0/ailMel1)
allMis1                 UCSC        GCA_000281125.1      8496      ✗ ✓ ✗ ✗       Alligator mississippiensis                  Aug. 2012 (allMis0.2/allMis1)
anoCar1                 UCSC        na                  28377      ✗ ✗ ✓ ✗       Anolis carolinensis                         Feb. 2007 (Broad/anoCar1)

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
genomes_dir: ~/.local/share/genomes/

plugin:
 - blacklist

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 while 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 using genomepy clean.

Python

Check out our Python API documentation here

>>> import genomepy
>>> for row in genomepy.search("GRCh38"):
...    print(row)
...    
['GRCh38.p13', 'Ensembl', 'GCA_000001405.28', 9606, True, 'Homo sapiens', '2014-01-Ensembl/2021-03']
['hg38', 'UCSC', 'GCA_000001405.15', 9606, [True, True, False, True], 'Homo sapiens', 'Dec. 2013 (GRCh38/hg38)']
['GRCh38', 'NCBI', 'GCF_000001405.26', 9606, True, 'Homo sapiens', 'Genome Reference Consortium']
['GRCh38.p1', 'NCBI', 'GCF_000001405.27', 9606, True, 'Homo sapiens', 'Genome Reference Consortium']
['GRCh38.p2', 'NCBI', 'GCF_000001405.28', 9606, True, 'Homo sapiens', 'Genome Reference Consortium']
['GRCh38.p3', 'NCBI', 'GCF_000001405.29', 9606, True, 'Homo sapiens', 'Genome Reference Consortium']
['GRCh38.p4', 'NCBI', 'GCF_000001405.30', 9606, True, 'Homo sapiens', 'Genome Reference Consortium']
['GRCh38.p5', 'NCBI', 'GCF_000001405.31', 9606, True, 'Homo sapiens', 'Genome Reference Consortium']
['GRCh38.p6', 'NCBI', 'GCF_000001405.32', 9606, True, 'Homo sapiens', 'Genome Reference Consortium']
['GRCh38.p7', 'NCBI', 'GCF_000001405.33', 9606, True, 'Homo sapiens', 'Genome Reference Consortium']
['GRCh38.p8', 'NCBI', 'GCF_000001405.34', 9606, True, 'Homo sapiens', 'Genome Reference Consortium']
['GRCh38.p9', 'NCBI', 'GCF_000001405.35', 9606, True, 'Homo sapiens', 'Genome Reference Consortium']
['GRCh38.p10', 'NCBI', 'GCF_000001405.36', 9606, True, 'Homo sapiens', 'Genome Reference Consortium']
['GRCh38.p11', 'NCBI', 'GCF_000001405.37', 9606, True, 'Homo sapiens', 'Genome Reference Consortium']
['GRCh38.p12', 'NCBI', 'GCF_000001405.38', 9606, True, 'Homo sapiens', 'Genome Reference Consortium']
['GRCh38.p13', 'NCBI', 'GCF_000001405.39', 9606, True, 'Homo sapiens', 'Genome Reference Consortium']

>>> genomepy.install_genome("hg38", "UCSC", genomes_dir="./data/genomes")
Downloading genome from UCSC.
Target URL: http://hgdownload.soe.ucsc.edu/goldenPath/hg38/bigZips/hg38.fa.gz...
Genome download successful, starting post processing...
name: hg38
local name: hg38
fasta: ./data/genomes/hg38/hg38.fa

>>> g = genomepy.Genome("hg38", genomes_dir="./data/genomes")
>>> g["chr6"][166502000:166502100]
>chr6:166502001-166502100
tgtatggtccctagaggggccagagtcacagagatggaaagtggatggcgggtgccgggggctggggagctactgtgcagggggacagagctttagttct

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

Genomepy utilizes external databases to obtain your files. Unfortunately this sometimes causes issues. Here are some of the more common issues, with solutions.

Let us know if you encounter issues you cannot solve by creating a new issue.

Provider is offline

Occasionally one of the providers experience connection issues, which can last anywhere between minutes to hours. When this happens genomepy will warn that the provider appears offline, or that the URL seems broken.

If the issue does not pass, you can try to reset genomepy. Simply run genomepy clean on the command line, or run genomepy.clean() in Python.

This genome is missing

Genomepy stores provider data on your computer to rerun it faster later. If a provider was offline during this time, it may miss (parts of) the data.

To re-download the data, remove the local data with genomepy clean, then search for your genome again.

This genome is STILL missing/URL is broken

Sadly, not everything (naming, structure, filenames) is always consistent on the provider end. Contact the provider to get it fixed! One notable group are Ensembl fungi, which seems to be mostly mislabelled.

In the meantime, you can still use the power of genomepy by manually retrieving the URLs, and downloading the files with genomepy install GENOME_URL -p url --url-to-annotation ANNOTATION_URL.

Which genome/gene annotation to use

Each provider has its pros and cons:

• Ensembl has excellent gene annotations, but their chromosome names can cause issues with some tools.
• UCSC has an excellent genome browser, but their gene annotations vary in format.
• NCBI allows public submissions, and so has the latest versions, although not always complete or error free.

Use genomepy search to see your options, and genomepy annotation to check the quality of the gene annotation(s).

The genomepy config was corrupted

You can create a new one with genomepy config generate on command line, or genomepy.manage_config("generate") in Python.

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.

Citation

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

Contributing

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

When contributing a PR, please use the develop branch.

Quick development setup:

1. Fork & download this repo.
2. cd into your local repo.
3. git checkout develop
4. conda env create -f environment.yaml
5. conda activate genomepy
6. pip install -e .
7. git checkout -b your_develop_branch

The command line and python imports will now use the code in your local repo. To test your changes locally, run the following command: pytest -vvv

Contributors

• Siebren Frölich - @siebrenf
• Maarten van der Sande - @Maarten-vd-Sande
• Tilman Schäfers @tilschaef
• Simon van Heeringen - @simonvh
• Dohoon Lee - @dohlee
• Jie Zhu - @alienzj

License

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