Haplotyped Methylome

Reproducibility instructions for Gigante et al., 2019.

Note: this repository is still being tested! If you find a bug, please file an issue.

Data available at ENA Accession PRJEB27157.

Author's note: there is an error in Figure S2 of the paper, in which the figure legend was marked Maternal/Paternal where it should have been Black6/Cast. A corrected version is available here.

System requirements

• R
• Python>=3.5
• Lots of RAM (min 256GB)
• Lots of disk space (estimate: 2TB)

Dependencies

To install with conda, run the following command.

conda env create -f environment.yml
source activate haplotyped_methylome

You will then need to install Albacore: it is available on the Nanopore Community.

To install without conda, see the list of dependencies at the bottom of this README.

Required data

For the standard workflow, snakemake will download all the necessary files.

If you wish to avoid running albacore, bwa and nanopolish on the raw nanopore data, you can run the following command, which downloads the output of these programs and tricks snakemake into thinking you have run the pipeline from the beginning:

snakemake intermediate_download

Note: currently this only downloads the methylation files We hope to provide the alignment and phasing data in the future.

If you wish to rerun from the beginning after running this command, you can revert to the original download with snakemake --forceall.

Running the workflow

To generate all plots, tables and notebooks, simply run from the root directory:

snakemake --cores 16

If you don't wish to run the full analysis, you can run specific rules from the Snakefile by running, for example:

snakemake --cores 16 rnaseq_analysis
snakemake --cores 16 haplotype_analysis
snakemake --cores 16 methylation_analysis

Installation without conda

Software dependencies:

• SAMtools
• Hisat2
• Trim Galore
• SNPsplit
• Bismark
• Bowtie 2
• Pandoc
• Albacore (optional)
• BWA (optional)
• Nanopolish (optional)

Python package dependencies:

pip install --user -r requirements.txt

R package dependencies:

Rscript install_R_deps.R

Known Issues

• rnaseq_analys.Rmd failed: there is no package called 'ggrastr'

If devtools doesn't play nicely with conda, sometimes the automatic GitHub installation of ggrastr fails. You can resolve if as follows:

git clone --depth 1 https://github.com/VPetukhov/ggrastr.git
cd ggrastr
R -e 'devtools::install()'