R/Python modules and scripts for the analysis of recombination and linkage disequilibrium from aligned genomic sequences. It provides means to dissect the phylotype/haplotype structure of a genomic dataset per gene locus, to perform genome-wide sliding-window scans for the detection of hotspots of local LD, .
This software suite and underlying methods were describedwas used in the following paper:
Lassalle, F. et al. (2016) Islands of linkage in an ocean of pervasive recombination reveals two-speed evolution of human cytomegalovirus genomes. Virus Evolution 2 (1), vew017. doi:10.1093/ve/vew017.
Please cite this paper if using any of the software below.
Bipartition profiling: searching for long-range LD between genes from bayesian phylogenetic tree samples
The bayesbipartprofile suite intends to explore the local phylogenetic structure within genomes of recombining species. It reconstructs haplotypes spanning genome regions, looking for any conserved phylogenetetic relationships between variable sets of strains/species/isolates across loci.
From a dataset of bayesian samples of gene trees, the bayesbipartprofile.py script generates a database of bipartiations and searches for similarities between them. (parser last tested and working on ouput from MrBayes 3.2.2)
Then, the bayesbipartprofile.r script builds matrices of bipartition support (two metrics are reported: posterior probability and compatibility score) across loci to detect conserved tracks of clonal phylogenetic structure, i.e. haplotypes, and provide text table and graphic output. This includes a map of phylogenetic haplotypes, and heatmaps of split profile correlation matrices, that provide a direct insight into linkage disequilibrium (LD) between genes, i.e. long-range LD.
Example:
# generate database of splits
python bayesbipartprofile.py --ltax /path/to/orderred_taxon_list --bs.thresh.ref.bip=0.35 /path/to/orderred_gene_list /path/to/mrbayes_result_directory /path/to/bayesbipartprofile_output_directory
# make correlation matrices and plots
bayesbipartprofile.r --gene.list.is.ordered --new /path/to/bayesbipartprofile_output_directoryBelow is an example of the matrix of bipartition compatibility score correlation (R^2) between genes in a dataset of 142 HCMV genomes (data from Lassalle et al. (2016)):
The genome-wide_localLD_scan.r script performs a genome-wide search for LD between pairs of sites, specifically comparing the allelic patterns at biallelic polymorphic sites (bial-SNPs) in a multiple genome sequence alignment.
First this script computes all r^2 or Fisher's exact test p-values for all pairs of bi-allelic sites in the genomes, and stores then in a matrix (saved in an .RData file). This can be restrained to neighbouring sites using --max.dist.ldr option to save computional time when ong-range LD is not of interest.
Then, it performs a sliding-window scan, reporting a map (and peaks) of local LD, based on either the average r^2 in each window (--LD.metric=r2), or by testing for local excess of LD compared to the whole genome (-- LD.metric=Fisher).
The 'Fisher' version of the scan is done by selecting a number b (20 by default) of most-equally spaced biallelic sites in the focal window of size w (3000 bp by default) and retrieving the Fisher's exact test p-values for all site pairs; the resulting p-value distribution is compared to a same-size quantile sample of the distributon observed over the whole genome within similar distances. This comparison is done with a Man-Witney-Wilcoxon U-test and its -log10-transformed p-value is reported as the local LD index. Note that windows with less than b biallelic sites are considered not fit for testing and are not reported; the size of windows w must therefore be adapted to the density of biallelic sites so to cover most of the genome, with a trade-off with precision on the location of reported LD peaks.
Finally, long-range associations between sites are searched in the whole-genome LD matrix, using Bonferroni correction to scale Fisher's p-values.
This script was originally designed to be applied to alignments of mapped assemblies, and to include the reference genome. If provided, this reference genome is used to provide coodinates of of the sites in the ouput; it is otherwise ignored for the LD computations. The reference genome label can be specified as the argument of the -r|--excl.ref.label option (specifically as its first part if a comma-separated list of genome labels). If nothing is specified, by default the coordinates are taken from the first alignment row.
Many options are available, as described below (result of call with --help option):
Usage: ./genome-wide_localLD_scan.r [-[-genomic.aln|a] <character>] [-[-out.dir|o] <character>] [-[-LD.metric|D] [<character>]] [-[-excl.ref.label|r] [<character>]] [-[-window.size|w] [<integer>]] [-[-step|s] [<integer>]] [-[-nb.snp|m] [<integer>]] [-[-signif.thresh|t] [<double>]] [-[-feature.table|f] [<character>]] [-[-chomp.gene.names|C] [<character>]] [-[-threads|T] [<integer>]] [-[-max.dist.ldr|d] [<integer>]] [-[-max.gap|g] [<integer>]] [-[-min.allele.freq|q] [<integer>]] [-[-nuc.div|n] [<integer>]] [-[-crazy.plot|K] [<integer>]] [-[-help|h]]
-a|--genomic.aln path to genomic alignment from which biallelic sites will be searched and LD tested
-o|--out.dir path to an existing ouput folder; a prefix to give to oupout files can be appended, e.g.:
'/path/to/ouput/folder/file_prefix'
-D|--LD.metric metric to report from measurement of LD, one of:
'r2', the mean site-to-site polymorphism correlation coeff. in the window;
'median_Fisher_pval', the median of the -log(10) p-values of Fisher's exact tests in the window;
'sitepairs_signif_Fisher', the number of sites in the window involved in pairs with significant
Fisher's exact tests (p-value scaled by the number of comparisons in the window < 0.05);
'Local_LD_Index' (aliases: 'LDI', 'Wilcox_Test_Fisher_pval', 'Fisher') [default],
the -log(10) p-value of a Man-Witney-Wilcoxon U-test comparing the local distribution
of p-values of Fisher exact tests for pairs of neighbour biallelic sites
within the window vs. in the whole genome)
-r|--excl.ref.label (comma-separated) label(s) of the genome sequence(s) to exclude from the analysis;
the first is also assumed to be the reference genome and is used to translate alignment
coordinates into reference genome coordinates
-w|--window.size physical size (bp) of the sliding windows in which LD is evaluated [default: 3000]
-s|--step step (bp) of the sliding windows in which LD is evaluated [default: 10]
-m|--nb.snp number of biallelic SNP within each window that are used for LD computation
(windows with less than that are excluded from the report) [default: 20]
-t|--signif.thresh threshold of Local LD Index above which the observed LD is significant [default: 5]
-f|--feature.table path to GenBank feature table file indicating CDSs and matching the reference sequence coordinates
-C|--chomp.gene.names regular expression pattern to shortern gene names; default to '^.+_(.+)_.+$';
disable by providing all-matching pattern '(.+)'
-T|--threads number of parallel threds used for computation (beware of memory use increase)
[default to 1: no parallel computation]
-d|--max.dist.ldr maximum distance between pairs of bi-allelic sites for which to compute LD
(in mumber of intervening bi-allelic sites ; Beware: this is not uniform !!!
polymorphism density varry across the genome !!!); by default compute the full matrix,
which is rarely that much bigger
-g|--max.gap maximum number of allowed missing sequences to keep a site in the alignement for LD and NucDiv computations
-q|--min.allele.freq minimum allele frequency (in count of sequences) in bi-alelic sites to be retained
(minalfreq = 1 => all bi-allelic sites [default])
-n|--nuc.div window size (bp) enabless computation of nucleotidic diversity within windows of specified size
-K|--crazy.plot plots the genome-wide pairwise site LD matrix to a PDF file; parameter value gives the number of sites
to represent per page in a sub-matrix; number of cells to plot grows quickly, this can be very long
to plot, and tedious to read as well [not done by default]
-h|--help
These detect_recomb scripts provide wrappers for recombination detection programs, including GeneConv, PHI and HyPhy's SBP/GARD in particular.
It is highly recommended to perform such a search for recombination breakpoints prior to any phylogenetic inference, including the bayesian gene tree sampling (e.g. with MrBayes) that provides the input for the bayesbipartprofile scripts descibed above.
Both script allow the execution of many unique jobs. For that you've got to provide a list of tasks, i.e. a file in which each line is a path to a sequence alignment you desire to scan = one task. The detect_recomb.py script run tasks sequentially, and the detect_recomb.qsub script (shell wrapper to submit parallel jobs of the Python script to a SGE type of computer cluster) can schedule them for execution in parallel, each job dealing with a chunk of tasks to be executed sequentially).
A requirement to use GARD is to specify the location of the mpirun command and of the hyphy/ root folder (set mpipath and hyphypath variables directly in the Python script, or set the $mympi and $myhyphy variables in the qsub script).