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CUSTOM_INSTALL.md

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Performing a standalone custom install from each individual module.

The easiest way to do a standalone install is to follow the instructions from the README and use the install.sh script. If that or none of the other installation options are possible (e.g. you need to use python2, you can install each sub-module and dependency individually.

  1. Clone the AmpliconSuite-pipeline git rep:

git clone https://github.com/jluebeck/AmpliconSuite-pipeline.git

  1. Individually install other prerequisites from the section below following the install instructions on each.
  2. Set the location where you would like to store the $AA_DATA_REPO
        mkdir data_repo && cd data_repo
        # copy or download files into data_repo directory
        # See the list of available AA repo files:
        # https://datasets.genepattern.org/data/module_support_files/AmpliconArchitect/
        wget [url for data repo [hg19/GRCh37/GRCh38/mm10].tar.gz]
        tar -xzf [hg19/GRCh37/GRCh38/mm10].tar.gz

        echo export AA_DATA_REPO=$PWD >> ~/.bashrc
        touch coverage.stats && chmod a+r coverage.stats
        source ~/.bashrc
  1. Run install.sh --finalize_only script from AmpliconSuite-pipeline.

Prerequisites for standalone installation:

AmpliconSuite-pipeline supports both python2 and python3, however CNVkit requires python3. Python3 support for AmpliconArchitect was added in version 1.3.

Unless you are using a containerized version, and depending on what input data you are starting from, AmpliconSuite-pipeline may require the following tools to be installed beforehand:

  • (required) The AmpliconSuite/AmpliconArchictect fork must be installed. Instructions for that are available here.
  • (required) The latest AmpliconArchitect data repo.
    • versions of the data repos containing bwa index files are also provided here. Indexed version recommended if starting from unaligned fastq reads. Instructions for setting up the AA data repo are available here.
  • (recommended) AmpliconClassifier to generate classifications of AmpliconArchitect outputs.
    • To install, clone the codebase then
    • cd AmpliconClassifier
    • echo export AC_SRC=$PWD >> ~/.bashrc
    • source ~/.bashrc
  • (recommended) CNVkit to generate CNV calls for focal amplification seed region identification.
  • (optional) bwa mem (unless supplying your own BAM file)
  • (optional) samtools (unless you already have a coordinate-sorted and indexed BAM file).
  • Scripts packaged with AmpliconSuite-pipeline require the numpy, matplotlib and intervaltree python packages. Those packages can be installed with pip, conda or similar.

AmpliconSuite-pipeline assumes both samtools and bwa executables are on the system path and can be directly invoked from bash without pathing to the executables. AmpliconSuite-pipeline will generate a BWA index for the reference genome if one is not yet in place. This adds >1hr to running time for the first use only when alignment is performed. Data repos with BWA index pre-generated are available here. AmpliconSuite-pipeline will also function on coordinate-sorted CRAM files, provided that the CRAM reference is in place.

AmpliconSuite-pipeline has been tested with Ubuntu (16.04 and above) and CentOS 7. AmpliconSuite-pipeline's optional dependencies related to CNV calling will not work on CentOS 6.

Note on using CNVkit: We currently recommend using CNVkit for identification of AA seeds. CNVkit requires python3. It also requires R version >= 3.5, which is non-standard on Ubuntu 16.04/14.04.

Getting mscorefonts onto your system.

AmpliconArchitect figures will attempt to use the Arial font, and will fall back to the default matplotlib "Deja Vu Sans" font. On macOS, Arial will likely already be present. Install the mscorefonts package one of two ways:

a) First run conda install mscorefonts then launch python and do

import matplotlib.font_manager
matplotlib.font_manager._load_fontmanager(try_read_cache=False)

b) (Ubuntu) sudo apt update && sudo apt install ttf-mscorefonts-installer. Then do sudo fc-cache -f -v to rebuild the font cache.