For a full tutorial, see: https://github.com/jtlovell/GENESPACE/blob/dev/doc/genespaceOverview.pdf
GENESPACE is a comparative genomics framework implemented in the R environment for statistical computing. The premise is that, when analyzing high-quality genome assemblies and annotations, we can improve the confidence of evolutionary inference by combining two sources of evidence for common ancestry: synteny (i.e. collinearity of gene order) and coding sequence similarity (homology). In addition to providing a second line of evidence beyond sequence similarity, combining synteny and homology have several benefits:
- exclude paralogous regions
- control for variable ploidy among genomes
- search for orthologs within single-copy regions
- infer expected gene position across genomes: a priori hypothesis about presence-absence variation
- track genes in regions of interest (e.g. QTL intervals)
GENESPACE outputs a synteny-constrained and -anchored orthogroup pan-genome annotation among multiple genomes. This simple text file allows for extraction and exploration of regional gene-level variation, a necessary step to integrate comparative and quantitative genomic goals.
For details and a complete example run, see the vignette and source code in /doc directory.
GENESPACE requires third-party software can be installed as follows.
orthofinder (which includes diamond) is most simply installed via conda (in the terminal, not R).
conda create -n orthofinder
conda activate orthofinder
conda install -c bioconda orthofinder
If conda is not available on your machine, you can install orthofinder from a number of other sources. See orthofinder documentation for details.
MCScanX should be installed from github.
NOTE Due to nested dependencies in the orthofinder install, orthofinder must be in the path when called, while the file path to MCScanX does not need to be in the path and can be specified in R.
If you are planning to run orthofinder from within R, which is needed if using orthofinderInBlk (see below for details) and recommended when using any genomes with ploidy > 1, enter R from the terminal with either R (for command line interace), or if Rstudio is installed on your machine open -na rstudio.
Once in R, GENESPACE can be installed directly from github via:
if (!requireNamespace("devtools", quietly = TRUE))
install.packages("devtools")
devtools::install_github("jtlovell/GENESPACE", upgrade = F)
The above command will install the CRAN-sourced dependencies (data.table, dbscan and R.utils). The bioconductor dependencies (Rtracklayer and Biostrings) need to be installed separately via:
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install(c("Biostrings", "Rtracklayer"))
GENESPACE R Package (GENESPACE) Copyright (c) 2021,HudsonAlpha Institute for Biotechnology. All rights reserved.
If you have questions about your rights to use or distribute this software, please contact Berkeley Lab's Intellectual Property Office at [email protected].
NOTICE. This Software was developed under funding from the U.S. Department of Energy and the U.S. Government consequently retains certain rights. As such, the U.S. Government has been granted for itself and others acting on its behalf a paid-up, nonexclusive, irrevocable, worldwide license in the Software to reproduce, distribute copies to the public, prepare derivative works, and perform publicly and display publicly, and to permit others to do so.
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