Add MCMCtree workflow and SNaQ analysis scripts
- Updated `pixi.toml` to include new R package dependencies for MCMCtree workflow. - Modified markdown file to remove unnecessary simulation data discussion. - Introduced `.lintr` configuration for linting R scripts. - Created `mcmctree.ctl` control file for MCMCtree analysis. - Developed `mcmctree_workflow.r` script to orchestrate MCMCtree analysis with model testing and ESS checks. - Added `06.snaq.jl` script for SNaQ analysis with plotting capabilities. - Implemented `07.mcmctree.sh` bash script to run MCMCtree on multiple alignments in parallel.
This commit is contained in:
IvisTang
parent
316017a575
commit
7f4e888e6a
1
.envrc
1
.envrc
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@ -5,3 +5,4 @@ export PUEUE_CONFIG_PATH="$PROJECTHOME/.pueue.yml"
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watch_file pixi.lock
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eval "$(pixi shell-hook)"
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PATH_add $SCRIPTS/bucky/bin
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PATH_add $SCRIPTS/bpp/bin
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@ -16,6 +16,7 @@
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98.results/*
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99.scripts/bucky/
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99.scripts/phyparts/
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99.scripts/bpp/
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run.status.json
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!*/_description.md
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tmp/
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@ -0,0 +1,5 @@
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linters: linters_with_defaults(
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line_length_linter(80),
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commented_code_linter = NULL,
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indentation_linter(4, hanging_indent_style = "never")
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)
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@ -0,0 +1,32 @@
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seed = 12345
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seqfile = input.fa
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treefile = input.tre
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outfile = {{PREFIX_PLACEHOLDER}}.mcmctree.out
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ndata = 1
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seqtype = 0 * 0: nucleotides; 1:codons; 2:AAs
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usedata = 1 * 0: no data; 1:seq like; 2:use in.BV; 3: out.BV
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clock = 3 * 1: global clock; 2: independent rates; 3: correlated rates
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RootAge = <100 * safe constraint on root age, used if no fossil for root.
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model = {{MODEL_PLACEHOLDER}} * 0:JC69, 1:K80, 2:F81, 3:F84, 4:HKY85
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alpha = {{GAMMA_PLACEHOLDER}} * alpha for gamma rates at sites
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ncatG = 4 * No. categories in discrete gamma
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cleandata = 0 * remove sites with ambiguity data (1:yes, 0:no)?
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BDparas = 1 1 0.1 C * birth, death, sampling
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kappa_gamma = 6 2 * gamma prior for kappa
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alpha_gamma = 1 1 * gamma prior for alpha
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rgene_gamma = 2 2 * gamma prior for overall rates for genes
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sigma2_gamma = 1 10 * gamma prior for sigma^2 (for clock=2 or 3)
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finetune = 1: 0.1 0.1 0.1 0.01 .5 * auto (0 or 1) : times, musigma2, rates, mixing, paras, FossilErr
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print = 2
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burnin = 200000
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sampfreq = 200
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nsample = 5000
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*** Note: Make your window wider (100 columns) before running the program.
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@ -0,0 +1,276 @@
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#! /usr/bin/env Rscript
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suppressMessages({
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library(ape)
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library(phytools)
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library(coda)
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library(argparser)
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library(processx)
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library(cli)
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})
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# Function to check if the specified outgroup is at the root of the tree
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check_tree_outgroup <- function(tree, outgroup) {
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if (!is.rooted(tree)) {
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return(list(
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judge = FALSE,
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msg = "The tree is unrooted."
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))
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}
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if (!outgroup %in% tree$tip.label) {
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return(list(
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judge = FALSE,
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msg = "Outgroup not found in tree tip labels."
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))
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}
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root_node <- getMRCA(tree, tree$tip.label)
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outgroup_parent <- getParent(tree, which(tree$tip.label == outgroup))
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if (root_node != outgroup_parent) {
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list(
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judge = FALSE,
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msg = "The specified outgroup is not at the root of the tree."
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)
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} else {
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list(
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judge = TRUE,
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msg = "The outgroup is correctly placed at the root."
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)
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}
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}
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# Function to check multiple outgroups sequentially
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check_outgroup_list <- function(tree, outgroup_list) {
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tree_iter <- tree
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iter <- NULL
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for (outgroup in outgroup_list) {
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res <- check_tree_outgroup(tree_iter, outgroup)
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if (!res$judge) {
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cli_alert_danger(
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paste(
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"Outgroup check failed for", outgroup,
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":", res$msg
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)
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)
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break
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}
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iter <- c(iter, outgroup)
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tree_iter <- drop.tip(tree_iter, outgroup)
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}
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cli_alert_success("All outgroups are correctly placed at the root.")
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res$judge
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}
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# Function to generate input tree for mcmctree with calibration points
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gen_input_tre <- function(tree) {
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tree_bak <- tree
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tree_bak$node.label <- rep("", tree$Nnode)
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tree_bak$edge.length <- NULL
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ntips <- length(tree$tip.label)
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ep_node <- getParent(tree, which(tree$tip.label == "EP"))
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tree_bak$node.label[ep_node - ntips] <- "'L(55.8,0.02,0.02)'"
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zju_node <- getParent(tree, which(tree$tip.label == "Zju"))
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tree_bak$node.label[zju_node - ntips] <- "'L(99.6,0.02,0.02)'"
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cli_alert_info("Generated input tree for mcmctree with calibration points:")
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cat(paste(ntips, "1\n"), file = "input.tre")
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raw_check_label <- function(x) {
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# this is a workaround to bypass the checkLabel function in ape
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x
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}
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assignInNamespace("checkLabel", raw_check_label, ns = "ape")
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write.tree(tree_bak, file = "input.tre", append = TRUE)
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cli_text(write.tree(tree_bak))
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}
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# Function to run modeltest-ng on the alignment file
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run_modeltest <- function(alnfile, prefix) {
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file.copy(alnfile, "input.fa", overwrite = TRUE)
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cmd <- "modeltest-ng"
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args <- c(
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"-p", 1,
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"-d", "nt",
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"-r", 12345,
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"-m", "JC,K80,F81,HKY",
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"-h", "ug",
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"-t", "ml",
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"-i", "input.fa",
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"-o", paste0(prefix, ".modeltest")
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)
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result <- run(cmd, args = args, echo_cmd = TRUE, echo = TRUE)
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if (result$status != 0) {
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cli_alert_danger("modeltest-ng execution failed.")
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stop("modeltest-ng execution failed.")
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} else {
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cli_alert_success("modeltest-ng run completed.")
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}
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}
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# Function to parse modeltest-ng output and extract the model & gamma parameter
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parse_modeltest_output <- function(modeltest_file) {
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model_map <- c(
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"JC" = "JC69",
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"K80" = "K80",
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"F81" = "F81",
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"HKY" = "HKY85"
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)
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lines <- readLines(modeltest_file)
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head_line <- grep("Best model according to AICc", lines, value = FALSE)
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if (length(head_line) == 0) {
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cli_alert_danger("No model found in modeltest-ng output.")
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stop("No model found in modeltest-ng output.")
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}
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model_line <- lines[head_line + 2]
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model_out <- strsplit(model_line, ":")[[1]][2]
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model_out <- unlist(strsplit(trimws(model_out), "+", fixed = TRUE))
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cli_alert_info(paste("Selected model:", paste(model_out, collapse = "+")))
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model <- model_map[model_out[1]]
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if (length(model_out) > 1 && model_out[2] == "G4") {
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gamma <- 0.5
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} else {
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gamma <- 0
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}
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list(
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model = model,
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gamma = gamma
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)
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}
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# Function to render the mcmctree control file from the template
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render_mcmctree_ctl <- function(template, outputfile, model, gamma, prefix) {
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ctl_lines <- readLines(template)
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ctl_lines <- gsub("{{MODEL_PLACEHOLDER}}", model, ctl_lines, fixed = TRUE)
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ctl_lines <- gsub("{{GAMMA_PLACEHOLDER}}",
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as.character(gamma),
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ctl_lines,
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fixed = TRUE
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)
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ctl_lines <- gsub("{{PREFIX_PLACEHOLDER}}",
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prefix,
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ctl_lines,
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fixed = TRUE
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)
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writeLines(ctl_lines, con = outputfile)
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}
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# Function to run mcmctree with the specified control file
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run_mcmctree <- function(ctlfile) {
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cmd <- "mcmctree"
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args <- ctlfile
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result <- run(cmd, args = args, echo_cmd = TRUE, echo = TRUE)
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if (result$status != 0) {
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cli_alert_danger("mcmctree execution failed.")
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stop("mcmctree execution failed.")
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} else {
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cli_alert_success("mcmctree run completed.")
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}
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}
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# Function to check ESS values from mcmctree MCMC output
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check_ess <- function(mcmcfile, check_file, threshold = 200) {
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mcmc_samples <- read.table(mcmcfile, header = TRUE)[, -1]
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mcmc_results <- mcmc(mcmc_samples)
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ess_values <- effectiveSize(mcmc_results)
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ess_table <- data.frame(
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Parameter = names(ess_values),
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ESS = as.numeric(ess_values)
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)
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write.table(ess_table,
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file = paste0(check_file, ".ess.tsv"),
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sep = "\t",
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row.names = FALSE,
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quote = FALSE
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)
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if (all(ess_values >= threshold)) {
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cli_alert_success(paste("All parameters have ESS >=", threshold))
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file.create(paste0(check_file, ".ess_check.passed"))
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} else {
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failed_params <- names(ess_values[ess_values < threshold])
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names(failed_params) <- rep("x", length(failed_params))
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cli_alert_warning(paste("Parameters with ESS <", threshold))
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cli_bullets(failed_params)
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file.create(paste0(check_file, ".ess_check.failed"))
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}
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}
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# Main function to orchestrate the workflow
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main <- function(treefile, alnfile, template, prefix) {
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tree <- read.tree(treefile)
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cli_h1("1. Checking Outgroups in the Tree")
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outgroup_list <- c("Zju", "EP")
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if (!check_outgroup_list(tree, outgroup_list)) {
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return(NULL)
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}
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cli_h1("2. Running ModelTest-NG")
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run_modeltest(alnfile, prefix)
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modeltest_file <- paste0(prefix, ".modeltest.out")
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model_info <- parse_modeltest_output(modeltest_file)
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cli_h1("3. Preparing and Running MCMCTree")
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gen_input_tre(tree)
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render_mcmctree_ctl(
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template,
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paste0(prefix, ".mcmctree.ctl"),
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model_info$model,
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model_info$gamma,
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prefix
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)
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cat("\n\n")
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run_mcmctree(paste0(prefix, ".mcmctree.ctl"))
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cli_h1("4. Checking ESS Values")
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check_ess("mcmc.txt", prefix)
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cli_h1("Workflow Completed Successfully")
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}
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p <- arg_parser("MCMCTree Workflow Script", hide.opts = TRUE)
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p <- add_argument(p, "--treefile",
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short = "-t",
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help = "Input tree file in Newick format",
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)
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p <- add_argument(p, "--alnfile",
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short = "-a",
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help = "Input alignment file in FASTA format"
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)
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p <- add_argument(p, "--template",
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short = "-c",
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help = "Template control file for mcmctree"
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)
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p <- add_argument(p, "--prefix",
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short = "-p",
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help = "Prefix for output files"
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)
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args <- parse_args(p)
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check_param <- c(
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!is.na(args$treefile),
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!is.na(args$alnfile),
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!is.na(args$template),
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!is.na(args$prefix)
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)
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if (all(check_param)) {
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cli_h1("Workflow Parameters:")
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cli_dl(args[c("treefile", "alnfile", "template", "prefix")])
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main(args$treefile, args$alnfile, args$template, args$prefix)
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} else {
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warnlist <- c(
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"--treefile, -t",
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"--alnfile, -a",
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"--template, -c",
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"--prefix, -p"
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)
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names(warnlist) <- ifelse(check_param, "v", "x")
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theme <- list(
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".bullets .bullet-x" = list(
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"text-exdent" = 4,
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before = function(x) paste0(" ", col_red(symbol$cross), " ")
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),
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".bullets .bullet-v" = list(
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"text-exdent" = 4,
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before = function(x) paste0(" ", col_green(symbol$tick), " ")
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)
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)
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cli_div(theme = theme)
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cli_h1("Missing required arguments:")
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cli_bullets(warnlist)
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cli_h1("")
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cli_end()
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print(p)
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}
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@ -1,18 +0,0 @@
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#! /usr/bin/env bash
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if [ "$#" -ne 3 ]; then
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echo "Usage: $0 <input_fasta_dir> <extension> <output_nexus_dir>"
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exit 1
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fi
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input_dir=$1
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extension=$2
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output_dir=$3
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mkdir -p "${output_dir}"
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for f in "${input_dir}"/*."${extension}"; do
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filename=$(basename -- "${f}")
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filename_noext="${filename%.*}"
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output_file="${output_dir}/${filename_noext}.nex"
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echo "Converting ${f} to ${output_file}"
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seqmagick convert --output-format nexus --alphabet dna --input-format fasta "${f}" "${output_file}"
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done
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@ -104,10 +104,10 @@ R"dev.off"();
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## expected vs. observed quartet concordance factors
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using CSV, DataFrames, Distributions, Random, RCall;
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inputCFfile = joinpath("bucky_1.CFs.csv");
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inputCFfile = joinpath("..","bucky","bucky_1","input.mb.CFs.csv");
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inputCF = readtableCF(inputCFfile);
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net3 = readsnaqnetwork("net3.out");
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topologymaxQpseudolik!(net3, inputCF);
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net4 = readsnaqnetwork("net4.out");
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topologymaxQpseudolik!(net4, inputCF);
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df_long = fittedquartetCF(inputCF, :long);
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### Adding jitter to the points for better visualization
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@ -127,6 +127,6 @@ R"dev.off"();
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# Goodness of fit of the SNaQ networks
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using QuartetNetworkGoodnessFit;
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res1 = quarnetGoFtest!(net3, inputCF, true; seed=123, nsim=1000);
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res1 = quarnetGoFtest!(net4, inputCF, true; seed=123, nsim=1000);
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res1[[1,2,3]] # p-value, uncorrected z, σ
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@ -0,0 +1,29 @@
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#! /bin/bash
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set -e
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SCRIPTS=${SCRIPTS:-"$PROJECTHOME/99.scripts"}
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THREADS=${THREADS:-16}
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if [ "$#" -ne 4 ]; then
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echo "Usage: $0 <aln_dir> <ml_dir> <out_dir> <alignment_ext>"
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echo "Run MCMCtree on orthogroup alignments with corresponding ML trees"
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exit 1
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fi
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aln_dir=$1
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ml_dir=$2
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out_dir=$3
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ext=$4
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mkdir -p "$out_dir"
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echo -n >mcmctree.cmds
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ctlfile=$(readlink -f "$SCRIPTS/miscs/mcmctree.ctl")
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for i in "$aln_dir"/*."$ext"; do
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j=$(basename "$i" ."$ext")
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aln=$(readlink -f "$i")
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ml_tree=$(readlink -f "$ml_dir/${j}/${j}.raxml.bestTree")
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mkdir -p "${out_dir}/${j}"
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cmd="cd ${out_dir}/${j} && Rscript $SCRIPTS/miscs/mcmctree_workflow.r"
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params="-a $aln -t $ml_tree -c ${ctlfile} -p ${j}"
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echo "$cmd $params > mcmctree.log 2>&1" >>mcmctree.cmds
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done
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xargs -t -P "$THREADS" -I cmd -a mcmctree.cmds bash -c "cmd"
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echo "MCMCtree all completed."
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@ -52,6 +52,10 @@ paml = ">=4.10.9,<5"
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beagle-lib = "==3.1.2"
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mrbayes = ">=3.2.7,<4"
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cairosvg = ">=2.8.2,<3"
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r-devtools = ">=2.4.6,<3"
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r-phytools = ">=2.5_2,<3"
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r-argparser = ">=0.7.2,<0.8"
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r-processx = ">=3.8.6,<4"
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[feature.beast.dependencies]
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beagle-lib = ">=4.0.1,<5"
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@ -59,7 +59,6 @@ title: 方法验证不足
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- 讨论方法的**适用范围与局限性**（如是否适用于大规模物种？能否处理多次introgression？）。
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- **解决方案：**
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- ==bpp模拟数据实验==
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- ==添加其他真实数据集模拟（蛇）==
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---
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layout: top-title
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