Installation — bcbio-nextgen 1.2.9 documentation (original) (raw)

Fresh installation (HPC cluster, server, AMI instance, Linux only)¶

2. Install data¶

Bcbio needs reference files, indices, and databases. It is possible to install bcbio package and data at once, but we recommend to split these steps, because:

(i) some datatargets (dbNSFP, gnomad, snpEff) may take from tens of hours to several days to finish, they could break in the middle due to unstable connections, i.e. it is better to tackle them one by one;
(ii) you can re-use your data installation between bcbio instances. Data does not change much even between years, so you can just create symlinks /old_bcbio/genomes -> /new_bcbio/genomes, /old_bcbio/galaxy/tool-data -> /new_bcbio/galaxy/tool-data.
(iii) it is easier to debug conda/mamba issues (code installation) and cloudbiolinux issues (recipes) separately.

bcbio_nextgen.py upgrade -u skip --genomes hg38 --aligners bwa

This command installs hg38 human reference genome and bwa aligner index - the bare minimum required to run germline or somatic variant calling pipelines.

Installation notes¶

bcbio should install cleanly on Linux systems. For Mac OSX, we suggest trying bcbio-vm which runs bcbio on Cloud or isolates all the third party tools inside a Docker container. bcbio-vm is still a work in progress but not all of the dependencies bcbio uses install cleanly on OSX.
Don’t run the installer with sudo or as the root user. Do not use directories with : in the name, it is not POSIX compliant and will cause installation failures.
To use custom mirrors for conda-forge and bioconda channels used during bcbio installation, set appropriate channel alias in your .condarc configuration file.
The machine will need to have some basic requirements for installing and running bcbio:
- Python 3.x
- Basic system setup for unpacking files: tar, gzip, unzip, bzip2, xz-utils
- The git version control system (https://git-scm.com/)
- wget for file retrieval (https://www.gnu.org/software/wget/)
Optional tool specific requirements:
- Java 1.7, needed when running GATK < 3.6 or MuTect. This must be available in your path so typing java -version resolves a 1.7 version. bcbio distributes Java 8 as part of the Anaconda installation for recent versions of GATK and MuTect2. You can override the Java 8 installed with bcbio by setting BCBIO_JAVA_HOME=/path/to/your/javadir if you have the Java you want in /path/to/your/javadir/bin/java.
- An OpenGL library, like Mesa (On Ubuntu/deb systems: libglu1-mesa, On RedHat/rpm systems: mesa-libGLU-devel). This is only required for cancer heterogeneity analysis with BubbleTree.
- The Pisces tumor-only variant callers requires the Microsoft .NET runtime.
The bcbio-nextgen Dockerfile contains the packages needed to install on bare Ubuntu systems.
The automated installer creates a fully integrated environment that allows simultaneous updates of the framework, third party tools and biological data. This offers the advantage over manual installation of being able to manage and evolve a consistent analysis environment as algorithms continue to evolve and improve. Installing this way is as isolated and self-contained as possible without virtual machines or lightweight system containers like Docker.

Installation parameters¶

Run

bcbio_nextgen.py upgrade --help

to see all supported installation options:

bcbio_nextgen.py upgrade --help usage: bcbio_nextgen.py upgrade [-h] [--cores CORES] [--tooldir TOOLDIR] [--tools] [-u {stable,development,system,deps,skip}] [--toolconf TOOLCONF] [--revision REVISION] [--toolplus TOOLPLUS] [--datatarget {variation,rnaseq,smallrna,gemini,vep,dbnsfp,dbscsnv,battenberg,kraken,ericscript,gnomad}] [--genomes {GRCh37,hg19,hg38,hg38-noalt,mm10,mm9,rn6,rn5,canFam3,dm3,galGal4,phix,pseudomonas_aeruginosa_ucbpp_pa14,sacCer3,TAIR10,WBcel235,xenTro3,GRCz10,GRCz11,Sscrofa11.1,BDGP6}] [--aligners {bwa,rtg,hisat2,bbmap,bowtie,bowtie2,minimap2,novoalign,twobit,bismark,snap,star,seq}] [--data] [--cwl] [--isolate] [--distribution {ubuntu,debian,centos,scientificlinux,macosx}]

optional arguments: -h, --help show this help message and exit --cores CORES Number of cores to use if local indexing is necessary. --tooldir TOOLDIR Directory to install 3rd party software tools. Leave unspecified for no tools --tools Boolean argument specifying upgrade of tools. Uses previously saved install directory -u {stable,development,system,deps,skip}, --upgrade {stable,development,system,deps,skip} Code version to upgrade --toolconf TOOLCONF YAML configuration file of tools to install --revision REVISION Specify a git commit hash or tag to install --toolplus TOOLPLUS Specify additional tool categories to install --datatarget {variation,rnaseq,smallrna,gemini,vep,dbnsfp,dbscsnv,battenberg,kraken,ericscript,gnomad} Data to install. Allows customization or install of extra data. --genomes {GRCh37,hg19,hg38,hg38-noalt,mm10,mm9,rn6,rn5,canFam3,dm3,galGal4,phix,pseudomonas_aeruginosa_ucbpp_pa14,sacCer3,TAIR10,WBcel235,xenTro3,GRCz10,GRCz11,Sscrofa11.1,BDGP6} Genomes to download --aligners {bwa,rtg,hisat2,bbmap,bowtie,bowtie2,minimap2,novoalign,twobit,bismark,snap,star,seq} Aligner indexes to download --data Upgrade data dependencies --cwl Install code and data for running CWL workflows --isolate Created an isolated installation without PATH updates --distribution {ubuntu,debian,centos,scientificlinux,macosx} Operating system distribution

Some useful arguments are:

--isolate Avoid updating the user’s ~/.bashrc if installing in a non-standard PATH. This facilitates creation of isolated modules without disrupting the user’s environmental setup. Manually edit your ~/.bashrc to allow bcbio runs with:
export PATH=/path_to_bcbio/anaconda/bin:/path_to_bcbio/tools/bin:$PATH
--nodata Do not install genome data.

Upgrade¶

bcbio 1.2.9 has major changes in the conda environments. Please consider installing bcbio1.2.9 code/tools from scratch rather than upgrading from 1.2.8. You can re-use the data installation from bcbio<=1.2.8. snpeff databases has to be re-installed with the below command

We use the same automated installation process for performing upgrades of tools, software and data in place. Since there are multiple targets and we want to avoid upgrading anything unexpectedly, we have specific arguments for each. Generally, you’d want to upgrade the code, tools and data together with:

bcbio_nextgen.py upgrade -u stable --tools --data

Tune the upgrade with these options:

-u Type of upgrade to do for bcbio-nextgen code. stable gets the most recent released version and development retrieves the latest code from GitHub.
--datatarget Customized installed data or download additional files not included by default:
--toolplus Specify additional tools to include. See the section on extra software for more details.
--genomes and --aligners options add additional aligner indexes to download and prepare. bcbio_nextgen.py upgrade -h lists available genomes and aligners. If you want to install multiple genomes or aligners at once, specify --genomes or --aligners multiple times, like this: --genomes GRCh37 --genomes mm10 --aligners bwa --aligners bowtie2
Leave out the --tools option if you don’t want to upgrade third party tools. If using --tools, it will use the same directory as specified during installation. If you’re using an older version that has not yet gone through a successful upgrade or installation and saved the tool directory, you should manually specify --tooldir for the first upgrade. You can also pass --tooldir to install to a different directory.
Leave out the --data option if you don’t want to get any upgrades of associated genome data.
Some aligners such as STAR don’t have pre-built indices due to the large file sizes of these. You set the number of cores to use for indexing with --cores 8.
For example, recommended HPC job parameters for bcbio_nextgen.py upgrade -u skip --data --datatarget rnaseq --genomes GRCh37 are: 2 CPU cores, 2GB memory, and 2 hours run time.

Customizing data installation¶

bcbio supports the following genome references, 12 of them have additional data downloads. If you need a reference which is absent in the list, you may install it as a custom genome.

bcbio installs associated data files for sequence processing, and you’re able to customize this to install larger files or change the defaults. Use the --datatarget flag (potentially multiple times) to customize or add new targets.

By default, bcbio will install data files for variation, rnaseq and smallrna but you can sub-select a single one of these if you don’t require other analyses. The available targets are:

variation – Data files required for variant calling: SNPs, indels and structural variants. These include files for annotation like dbSNP, associated files for variant filtering, coverage and annotation files.
rnaseq – Transcripts and indices for running RNA-seq. The transcript files are also used for annotating and prioritizing structural variants.
smallrna – Data files for doing small RNA analysis.
gemini – The GEMINI framework associates publicly available metadata with called variants, and provides utilities for query and analysis. This target installs the required GEMINI data files, including ExAC.
gnomad – gnomAD is a large scale collection of genome variants, expanding on ExAC to include whole genome and more exome inputs. This is a large 25Gb download, available for human genome builds GRCh37, hg19 and hg38.
vep – Data files for the Variant Effects Predictor (VEP). To use VEP as an alternative to the default installed snpEff, set vep in the variant calling configuration.
dbnsfp – Like CADD, dbNSFP provides integrated and generalized metrics from multiple sources to help with prioritizing variations for follow up. The files are large: dbNSFP is 10Gb, expanding to 100Gb during preparation.
dbscsnv – dbscSNV includes all potential human SNVs within splicing consensus regions (−3 to +8 at the 5’ splice site and −12 to +2 at the 3’ splice site), i.e. scSNVs, related functional annotations and two ensemble prediction scores for predicting their potential of altering splicing.
battenberg – Data files for Battenberg, which detects subclonality and copy number changes in whole genome cancer samples.
kraken – Database for Kraken, optionally used for contamination detection.
ericscript – Database for EricScript, based gene fusion detection. Supports hg38, hg19 and GRCh37.
TOPMed – TOPMed Allele frequencies for whole genome variants from heart, lung, blood and sleep disorders. Supports hg38, hg19 and GRCh37.

For somatic analyses, bcbio includes COSMIC v68 for hg19 and GRCh37 only. Due to license restrictions, we cannot include updated versions of this dataset and hg38 support with the installer. To prepare these datasets yourself you can use a utility script shipped with cloudbiolinux that downloads, sorts and merges the VCFs, then copies into your bcbio installation:

export COSMIC_USER="you@example.org" export COSMIC_PASS="your_cosmic_password" bcbio_python prepare_cosmic.py 89 /path/to/bcbio

/path/to/bcbio/ here is the directory one up from the genomes directory. The script removes variants marked as SNP in COSMIC, i.e. leaving only somatic variants. From version a minor portion of variants gets re-classified, for example: 3,779 variants were SNPs in cosmic-90 and became mutations in cosmic-92, 656 variants were mutations in cosmic-90 and became SNPs in cosmic-92.

System requirements¶

bcbio-nextgen provides a wrapper around external tools and data, so the actual tools used drive the system requirements. For small projects, it should install on workstations or laptops with a couple GB of memory, and then scale as needed on clusters or multicore machines.

Disk space requirement for the tools, including all system packages is about 22GB (or more, depending on the type of the file system). Biological data requirements will depend on the genomes and aligner indices used, but a suggested install with GRCh37 and bowtie/bwa2 indexes uses approximately 35GB of storage during preparation and ~25GB after:

$ du -shc genomes/Hsapiens/GRCh37/* 3.8G bowtie2 5.1G bwa 3.0G rnaseq-2014-05-02 3.0G seq 340M snpeff 4.2G variation 4.4G vep 23.5G total

Troubleshooting¶

Proxy or firewall problems¶

Some steps retrieve third party tools from GitHub, which can run into issues if you’re behind a proxy or block git ports. To instruct git to use https:// globally instead of git://:

git config --global url.https://github.com/.insteadOf git://github.com/

GATK or Java Errors¶

Most software tools used by bcbio require Java 1.8. bcbio distributes an OpenJDK Java build and uses it so you don’t need to install anything. Older versions of GATK (< 3.6) and MuTect require a locally installed Java 1.7. If you have version incompatibilities, you’ll see errors like:

Unsupported major.minor version 51.0

Fixing this requires either installing Java 1.7 for old GATK and MuTect or avoiding pointing to an incorrect java (unset JAVA_HOME). You can also tweak the java used by bcbio, described in the Automated installation section.

ImportErrors¶

Import errors with tracebacks containing Python libraries outside of the bcbio distribution (/path/to/bcbio/anaconda) are often due to other conflicting Python installations. bcbio tries to isolate itself as much as possible but external libraries can get included during installation due to the PYTHONHOME or PYTHONPATH environmental variables or local site libraries. These commands will temporary unset those to get bcbio installed, after which it should ignore them automatically:

unset PYTHONHOME unset PYTHONPATH export PYTHONNOUSERSITE=1

Finally, having a .pydistutils.cfg file in your home directory can mess with where the libraries get installed. If you have this file in your home directory, temporarily renaming it to something else may fix your installation issue.

Manual process¶

The manual process does not allow the in-place updates and management of third party tools that the automated installer makes possible. It’s a more error-prone and labor intensive process. If you find you can’t use the installer we’d love to hear why to make it more amenable to your system. If you’d like to develop against a bcbio installation, see the documentation on setting up a development environment.

Data requirements¶

In addition to existing bioinformatics software the pipeline requires associated data files for reference genomes, including pre-built indexes for aligners. The CloudBioLinux toolkit again provides an automated way to download and prepare these reference genomes:

fab -f data_fabfile.py -H localhost -c your_fabricrc.txt install_data_s3:your_biodata.yaml

The biodata.yaml file contains information about what genomes to download. The fabricrc.txt describes where to install the genomes by adjusting the data_files variable. This creates a tree structure that includes a set of Galaxy-style location files to describe locations of indexes:

├── galaxy │ ├── tool-data │ │ ├── alignseq.loc │ │ ├── bowtie_indices.loc │ │ ├── bwa_index.loc │ │ ├── sam_fa_indices.loc │ │ └── twobit.loc │ └── tool_data_table_conf.xml ├── genomes │ ├── Hsapiens │ │ ├── GRCh37 │ │ └── hg19 │ └── phiX174 │ └── phix └── liftOver

Individual genome directories contain indexes for aligners in individual sub-directories prefixed by the aligner name. This structured scheme helps manage aligners that don’t have native Galaxy .loc files. The automated installer will download and set this up automatically:

Maintain many bcbio installations¶

It is often asked how to reproduce older bcbio analyses when every update changes a lot in tools and in bcbio code. One of the solutions is the use of modules in HPC environemnt: https://www.admin-magazine.com/HPC/Articles/Environment-Modules. You can have a bcbio/version module for every bcbio snapshot you need. They would consume <50G each, and a single large genomesfolder could be symlinked to all of them. Data in genomes changes in a much slower pace compared to bcbio code and tools.