From 7924ce459dddafec8150544aa8b748379610c83f Mon Sep 17 00:00:00 2001 From: jeffersonfparil Date: Sat, 8 Jun 2024 16:26:57 +1000 Subject: [PATCH 1/2] increasing default memory usage multiplier from 40 to 50 to fix OOM error in test data runs --- R/cross_validation.R | 3 --- R/io.R | 7 ++++--- 2 files changed, 4 insertions(+), 6 deletions(-) diff --git a/R/cross_validation.R b/R/cross_validation.R index d40513e..4066882 100644 --- a/R/cross_validation.R +++ b/R/cross_validation.R @@ -424,7 +424,6 @@ fn_cross_validation_preparation = function(list_merged, cv_type=1, n_folds=10, n n_folds=n_folds, n_reps=n_reps, memory_requested_Gb=max_mem_Gb, - memory_multiplier=40, verbose=verbose) } else if (cv_type == 2) { ############################################ @@ -455,7 +454,6 @@ fn_cross_validation_preparation = function(list_merged, cv_type=1, n_folds=10, n n_folds=n_folds, n_reps=1, memory_requested_Gb=max_mem_Gb, - memory_multiplier=40, verbose=verbose) } else if (cv_type == 3) { ################################################# @@ -486,7 +484,6 @@ fn_cross_validation_preparation = function(list_merged, cv_type=1, n_folds=10, n n_folds=n_folds, n_reps=1, memory_requested_Gb=max_mem_Gb, - memory_multiplier=40, verbose=verbose) } else { error = methods::new("gpError", diff --git a/R/io.R b/R/io.R index 673c4f7..bbc9322 100644 --- a/R/io.R +++ b/R/io.R @@ -2276,7 +2276,7 @@ fn_subset_merged_genotype_and_phenotype = function(list_merged, vec_idx, verbose #' @param n_folds number of cross-validation folds (Default=10) #' @param n_reps number of cross-validation replication (Default=10) #' @param memory_requested_Gb memory requested or available for use (Default=400) -#' @param memory_multiplier estimated memory usage multiplier (Default=40) +#' @param memory_multiplier estimated memory usage multiplier (Default=50) #' @param verbose show memory usage estimation messages? (Default=FALSE) #' @returns #' - Ok: @@ -2288,7 +2288,8 @@ fn_subset_merged_genotype_and_phenotype = function(list_merged, vec_idx, verbose #' list_mem = fn_estimate_memory_footprint(X=rnorm(10000), verbose=TRUE) #' @export fn_estimate_memory_footprint = function(X, n_models=7, n_folds=10, n_reps=10, - memory_requested_Gb=400, memory_multiplier=40, verbose=FALSE) { + memory_requested_Gb=400, memory_multiplier=50, verbose=FALSE) +{ ################################################### ### TEST # X = matrix(0.0, nrow=492, ncol=455255) @@ -2296,7 +2297,7 @@ fn_estimate_memory_footprint = function(X, n_models=7, n_folds=10, n_reps=10, # n_reps = 10 # n_folds = 10 # memory_requested_Gb = 400 - # memory_multiplier = 40 + # memory_multiplier = 50 # verbose = TRUE ################################################### if ((as.numeric(utils::object.size(X)) == 0) | (n_models <= 0) | (n_folds <= 0) | (n_reps <= 0) | (memory_requested_Gb <= 0) | (memory_multiplier <= 0)) { From e062028fec83068b561adfed698af88a5837a0fd Mon Sep 17 00:00:00 2001 From: jeffersonfparil Date: Sat, 8 Jun 2024 16:28:07 +1000 Subject: [PATCH 2/2] increasing default memory usage multiplier from 40 to 50 to fix OOM error in test data runs --- exec/00_gp_slurm_job_wrapper-LUCERNE.sh | 95 ++++++++++++++++++ exec/00_gp_slurm_job_wrapper-RYEGRASS.sh | 95 ++++++++++++++++++ exec/01_gp_slurm_job-LUCERNE.sh | 120 +++++++++++++++++++++++ exec/01_gp_slurm_job-RYEGRASS.sh | 117 ++++++++++++++++++++++ exec/tests/grape.Rds | Bin 0 -> 147501 bytes exec/tests/grape_pheno.tsv | 78 +++++++++++++++ 6 files changed, 505 insertions(+) create mode 100755 exec/00_gp_slurm_job_wrapper-LUCERNE.sh create mode 100755 exec/00_gp_slurm_job_wrapper-RYEGRASS.sh create mode 100755 exec/01_gp_slurm_job-LUCERNE.sh create mode 100755 exec/01_gp_slurm_job-RYEGRASS.sh create mode 100644 exec/tests/grape.Rds create mode 100644 exec/tests/grape_pheno.tsv diff --git a/exec/00_gp_slurm_job_wrapper-LUCERNE.sh b/exec/00_gp_slurm_job_wrapper-LUCERNE.sh new file mode 100755 index 0000000..f84ef8d --- /dev/null +++ b/exec/00_gp_slurm_job_wrapper-LUCERNE.sh @@ -0,0 +1,95 @@ +#!/bin/bash + +### Load the conda environment +module load Miniconda3/22.11.1-1 +conda init bash +source ~/.bashrc +conda activate genomic_selection + +################################################################ +### TOP-LEVEL SLURM ARRAY JOB SUBMISSION SCRIPT +### Please edit the input variables below to match your dataset: +################################################################ + +### Input variables (use the absolute path to files to be precise) +### (1) R matrix object with n rows corresponding to samples, and p columns corresponding to the markers or loci. +### Should have no missing data or else will be imputed via mean value imputation. +GENOTYPE_DATA_RDS='/group/pasture/Jeff/lucerne/workdir/FINAL-IMPUTED-noTrailingAllele-filteredSNPlist.Rds' +### (2) Tab-delimited phenotype file where column 1: sample names, column 2: population name, columns 3 and so on refers to the phenotype values of one trait per column. +### Headers for the columns should be named appropriately, e.g. ID, POP, TRAIT1, TRAIT2, etc. +### Missing values are allowed for samples whose phenotypes will be predicted by the best model identified within the population they belong to. +### Missing values may be coded as empty cells, -, NA, na, NaN, missing, and/or MISSING. +PHENOTYPE_DATA_TSV='/group/pasture/Jeff/lucerne/workdir/Lucerne_PhenomicsDB_2024-05-27-BiomassPredicted.tsv' +### (3) Number of folds for k-fold cross-validation. +KFOLDS=5 +### (4) Number of replications of the k-fold cross-validation each representing a random sorting of the samples hence yielding different ways of partitioning the data. +NREPS=5 +### (5) Full path to the location of the executable Rscript gp.R +DIR='/group/pasture/Jeff/gp/exec' + +### Check if the genotype file exists +if [ ! -f $GENOTYPE_DATA_RDS ] +then + echo "Error: The genotype file: $GENOTYPE_DATA_RDS does not exist. Are you specifying the full path? Is the name correct?" + exit 101 +fi +### Check if the phenotype file exists +if [ ! -f $PHENOTYPE_DATA_TSV ] +then + echo "Error: The phenotype file: $PHENOTYPE_DATA_TSV does not exist. Are you specifying the full path? Is the name correct?" + exit 102 +fi +### Check if the genotype file is a valid Rds file +echo 'args = commandArgs(trailingOnly=TRUE) +geno = suppressWarnings(tryCatch(readRDS(args[1]), error=function(e){print("Error loading genotype file.")})) +' > test_geno_rds.R +if [ $(Rscript test_geno_rds.R $GENOTYPE_DATA_RDS | grep -i "error" | wc -l) -eq 1 ] +then + echo "Error: The genotype file: $GENOTYPE_DATA_RDS is not an Rds file." + exit 103 +fi +rm test_geno_rds.R +### Check if the phenotype file is formatted according to the required specifications +echo 'args = commandArgs(trailingOnly=TRUE) +pheno = suppressWarnings(tryCatch(read.delim(args[1], sep="\t", header=TRUE), error=function(e){print("Error loading phenotype file.")})) +' > test_pheno_rds.R +if [ $(Rscript test_pheno_rds.R $PHENOTYPE_DATA_TSV | grep -i "error" | wc -l) -eq 1 ] +then + echo "Error: The phenotype file: $GENOTYPE_DATA_RDS is not formatted according to specifications. It should be tab-delimited and a header line must be present." + exit 104 +fi +rm test_pheno_rds.R +### Check if the genomic_selection repo folder exists +if [ ! -d $DIR ] +then + echo "Error: The genotype_selection directory: $DIR does not exist. Are you specifying the full path? Is the name correct?" + exit 105 +fi +### Check if the genomic_selection repo belongs to the user +if [ ! -w $DIR ] +then + echo "Error: You do not have permission to write in the genotype_selection directory: $DIR. Did you clone the genomic_selection repository into a directory you have write-access to?" + exit 106 +fi +### Check if the genomic_selection repo has contains the slurm array job submission script +if [ ! -f ${DIR}/01_gp_slurm_job.sh ] +then + echo "Error: The genotype_selection directory: $DIR does not contain the script: 01_gp_slurm_job.sh. Are you sure this is the genomic_selection repo directory?" + exit 107 +fi +### Initialise the output directory which will contain all the output Rds files across populations and traits +if [ ! -d ${DIR}/output ] +then + mkdir ${DIR}/output +fi +### Submit an array of jobs equivalent to the number of traits in the phenotype file +cd $DIR/ +N_TRAITS=$(echo $(head -n1 $PHENOTYPE_DATA_TSV | awk '{print NF}') - 2 | bc) +N_POPS=$(tail -n+2 $PHENOTYPE_DATA_TSV | cut -f2 - | sort | uniq | wc -l) +sbatch --array 1-$(echo "${N_TRAITS} * ${N_POPS}" | bc) \ + 01_gp_slurm_job-LUCERNE.sh \ + ${GENOTYPE_DATA_RDS} \ + ${PHENOTYPE_DATA_TSV} \ + ${KFOLDS} \ + ${NREPS} \ + ${DIR} diff --git a/exec/00_gp_slurm_job_wrapper-RYEGRASS.sh b/exec/00_gp_slurm_job_wrapper-RYEGRASS.sh new file mode 100755 index 0000000..574382e --- /dev/null +++ b/exec/00_gp_slurm_job_wrapper-RYEGRASS.sh @@ -0,0 +1,95 @@ +#!/bin/bash + +### Load the conda environment +module load Miniconda3/22.11.1-1 +conda init bash +source ~/.bashrc +conda activate genomic_selection + +################################################################ +### TOP-LEVEL SLURM ARRAY JOB SUBMISSION SCRIPT +### Please edit the input variables below to match your dataset: +################################################################ + +### Input variables (use the absolute path to files to be precise) +### (1) R matrix object with n rows corresponding to samples, and p columns corresponding to the markers or loci. +### Should have no missing data or else will be imputed via mean value imputation. +GENOTYPE_DATA_RDS='/group/pasture/Jeff/ryegrass/workdir/STR_NUE_WUE_HS-1717536141.3435302.3200855812-IMPUTED.Rds' +### (2) Tab-delimited phenotype file where column 1: sample names, column 2: population name, columns 3 and so on refers to the phenotype values of one trait per column. +### Headers for the columns should be named appropriately, e.g. ID, POP, TRAIT1, TRAIT2, etc. +### Missing values are allowed for samples whose phenotypes will be predicted by the best model identified within the population they belong to. +### Missing values may be coded as empty cells, -, NA, na, NaN, missing, and/or MISSING. +PHENOTYPE_DATA_TSV='/group/pasture/Jeff/ryegrass/workdir/STR_NUE_WUE_PhenomicsDB_2024-05-20-BiomassPredictedAndGroudtruth.tsv' +### (3) Number of folds for k-fold cross-validation. +KFOLDS=5 +### (4) Number of replications of the k-fold cross-validation each representing a random sorting of the samples hence yielding different ways of partitioning the data. +NREPS=5 +### (5) Full path to the location of the executable Rscript gp.R +DIR='/group/pasture/Jeff/gp/exec' + +### Check if the genotype file exists +if [ ! -f $GENOTYPE_DATA_RDS ] +then + echo "Error: The genotype file: $GENOTYPE_DATA_RDS does not exist. Are you specifying the full path? Is the name correct?" + exit 101 +fi +### Check if the phenotype file exists +if [ ! -f $PHENOTYPE_DATA_TSV ] +then + echo "Error: The phenotype file: $PHENOTYPE_DATA_TSV does not exist. Are you specifying the full path? Is the name correct?" + exit 102 +fi +### Check if the genotype file is a valid Rds file +echo 'args = commandArgs(trailingOnly=TRUE) +geno = suppressWarnings(tryCatch(readRDS(args[1]), error=function(e){print("Error loading genotype file.")})) +' > test_geno_rds.R +if [ $(Rscript test_geno_rds.R $GENOTYPE_DATA_RDS | grep -i "error" | wc -l) -eq 1 ] +then + echo "Error: The genotype file: $GENOTYPE_DATA_RDS is not an Rds file." + exit 103 +fi +rm test_geno_rds.R +### Check if the phenotype file is formatted according to the required specifications +echo 'args = commandArgs(trailingOnly=TRUE) +pheno = suppressWarnings(tryCatch(read.delim(args[1], sep="\t", header=TRUE), error=function(e){print("Error loading phenotype file.")})) +' > test_pheno_rds.R +if [ $(Rscript test_pheno_rds.R $PHENOTYPE_DATA_TSV | grep -i "error" | wc -l) -eq 1 ] +then + echo "Error: The phenotype file: $GENOTYPE_DATA_RDS is not formatted according to specifications. It should be tab-delimited and a header line must be present." + exit 104 +fi +rm test_pheno_rds.R +### Check if the genomic_selection repo folder exists +if [ ! -d $DIR ] +then + echo "Error: The genotype_selection directory: $DIR does not exist. Are you specifying the full path? Is the name correct?" + exit 105 +fi +### Check if the genomic_selection repo belongs to the user +if [ ! -w $DIR ] +then + echo "Error: You do not have permission to write in the genotype_selection directory: $DIR. Did you clone the genomic_selection repository into a directory you have write-access to?" + exit 106 +fi +### Check if the genomic_selection repo has contains the slurm array job submission script +if [ ! -f ${DIR}/01_gp_slurm_job.sh ] +then + echo "Error: The genotype_selection directory: $DIR does not contain the script: 01_gp_slurm_job.sh. Are you sure this is the genomic_selection repo directory?" + exit 107 +fi +### Initialise the output directory which will contain all the output Rds files across populations and traits +if [ ! -d ${DIR}/output ] +then + mkdir ${DIR}/output +fi +### Submit an array of jobs equivalent to the number of traits in the phenotype file +cd $DIR/ +N_TRAITS=$(echo $(head -n1 $PHENOTYPE_DATA_TSV | awk '{print NF}') - 2 | bc) +N_POPS=$(tail -n+2 $PHENOTYPE_DATA_TSV | cut -f2 - | sort | uniq | wc -l) +sbatch --array 1-$(echo "${N_TRAITS} * ${N_POPS}" | bc) \ + 01_gp_slurm_job-RYEGRASS.sh \ + ${GENOTYPE_DATA_RDS} \ + ${PHENOTYPE_DATA_TSV} \ + ${KFOLDS} \ + ${NREPS} \ + ${DIR} diff --git a/exec/01_gp_slurm_job-LUCERNE.sh b/exec/01_gp_slurm_job-LUCERNE.sh new file mode 100755 index 0000000..f646369 --- /dev/null +++ b/exec/01_gp_slurm_job-LUCERNE.sh @@ -0,0 +1,120 @@ +#!/bin/bash +#SBATCH --job-name="GS" +#SBATCH --account="dbiopast2" ### EDIT ME: Pick the appropriate account name, e.g. dbiopast1 or dbiopast2 +#SBATCH --ntasks=1 ### LEAVE ME:Request a single task as we will be submitting this as an array job where each job corresponds to a trait +#SBATCH --cpus-per-task=32 ### EDIT ME: Parallelisation across replications, folds and models (more cpu means faster execution time but probably longer time to wait for the Slurm scheduler to find resources to allocate to the job) +#SBATCH --mem=400G ### EDIT ME: Proportional to the input data (will need to test the appropriate memory required, hint use `seff ${JOBID}`) +#SBATCH --time=7-0:0:00 ### EDIT ME: Proportional to the input data, number of folds, replications, and models to be used +################################################################################################### +### Edit the Slurm settings above to match your requirements. +################################################################################################### + +################################################################################################### +### The variables below will be exported from `00_gs_slurm_job_wrapper.sh`: +################################################################################################### +### Input variables (use the absolute path to files to be precise) +### (1) R matrix object with n rows corresponding to samples, and p columns corresponding to the markers or loci. +### Should have no missing data or else will be imputed via mean value imputation. +# GENOTYPE_DATA_RDS='/group/pasture/Jeff/genomic_selection/tests/grape.rds' +GENOTYPE_DATA_RDS=$1 +### (2) Tab-delimited phenotype file where column 1: sample names, column 2: population name, columns 3 and so on refers to the phenotype values of one trait per column. +### Headers for the columns should be named appropriately, e.g. ID, POP, TRAIT1, TRAIT2, etc. +### Missing values are allowed for samples whose phenotypes will be predicted by the best model identified within the population they belong to. +### Missing values may be coded as empty cells, -, NA, na, NaN, missing, and/or MISSING. +# PHENOTYPE_DATA_TSV='/group/pasture/Jeff/genomic_selection/tests/grape_pheno.txt' +PHENOTYPE_DATA_TSV=$2 +### (3) Number of folds for k-fold cross-validation. +# KFOLDS=5 +KFOLDS=$3 +### (4) Number of replications of the k-fold cross-validation each representing a random sorting of the samples hence yielding different ways of partitioning the data. +# NREPS=3 +NREPS=$4 +### (5) Full path to the location of the executable Rscript gp.R +# DIR='/group/pasture/Jeff/gp/exec' +DIR=$5 +################################################################################################### +### Edit the code below, if and only if you have read the documentation or familiar with `src/*.R`: +################################################################################################### +### Define the trait and population to include +N_POPS=$(tail -n+2 $PHENOTYPE_DATA_TSV | cut -f2 - | sort | uniq | wc -l) +TRAIT_IDX=$(echo "((${SLURM_ARRAY_TASK_ID}-1) / ${N_POPS}) + 1" | bc) +POP_IDX=$(echo "${SLURM_ARRAY_TASK_ID} % ${N_POPS}" | bc) +if [ "${POP_IDX}" -eq 0 ] +then + POP_IDX=${N_POPS} +fi +COLUMN_ID=$(echo 2 + ${TRAIT_IDX} | bc) +TRAIT=$(head -n1 $PHENOTYPE_DATA_TSV | cut -f${COLUMN_ID}) +POP=$(tail -n+2 $PHENOTYPE_DATA_TSV | cut -f2 - | sort | uniq | head -n${POP_IDX} | tail -n1) +### Skip leave-one-population-out cross-validation if there is only one population +if [ "${N_POPS}" -eq 1 ] +then + BOOL_ACROSS=FALSE +else + if [ "${POP_IDX}" -eq 1 ] + then + BOOL_ACROSS=TRUE + else + BOOL_ACROSS=FALSE + fi +fi +### Output directories +DIR_OUT_MAIN=${DIR}/output +DIR_OUT=${DIR_OUT_MAIN}/output-${TRAIT}-${POP} +mkdir $DIR_OUT +### Log messages +echo JOB_${SLURM_ARRAY_TASK_ID}-TRAIT_${TRAIT}-POP_${POP} > ${DIR_OUT}/job_info-${TRAIT}-${POP}.log +echo "========================================== +------------------------------------------- + Job Info +------------------------------------------- +SLURM_JOB_ID = $SLURM_JOB_ID +SLURM_JOB_NAME = $SLURM_JOB_NAME +SLURM_JOB_NODELIST = $SLURM_JOB_NODELIST +SLURM_SUBMIT_HOST = $SLURM_SUBMIT_HOST +SLURM_SUBMIT_DIR = $SLURM_SUBMIT_DIR +SLURM_NTASKS = $SLURM_NTASKS +SLURM_ARRAY_TASK_ID = $SLURM_ARRAY_TASK_ID +SLURM_MEM_PER_NODE = $(echo "$SLURM_MEM_PER_NODE / (2^10)" | bc) GB +SLURM_CPUS_PER_TASK = $SLURM_CPUS_PER_TASK +------------------------------------------- + Variables +------------------------------------------- +GENOTYPE_DATA_RDS : $GENOTYPE_DATA_RDS +PHENOTYPE_DATA_TSV : $PHENOTYPE_DATA_TSV +KFOLDS : $KFOLDS +NREPS : $NREPS +TRAIT : $TRAIT +POPULATION : $POP +------------------------------------------- + Output directory +------------------------------------------- +${DIR_OUT} +==========================================" >> ${DIR_OUT}/job_info-${TRAIT}-${POP}.log + +### Load the conda environment +module load Miniconda3/22.11.1-1 +conda init bash +source ~/.bashrc +conda activate genomic_selection + +### Run within and across population replicated k-fold cross-validation and prediction of missing phenotypes +time \ +Rscript ${DIR}/gp.R \ + --fname-geno $GENOTYPE_DATA_RDS \ + --fname-pheno $PHENOTYPE_DATA_TSV \ + --population $POP \ + --dir-output $DIR_OUT \ + --pheno-idx-col-y $COLUMN_ID \ + --bool-within TRUE \ + --bool-across $BOOL_ACROSS \ + --n-folds $KFOLDS \ + --n-reps $NREPS \ + --bool-parallel TRUE \ + --max-mem-Gb $(echo "$SLURM_MEM_PER_NODE / (2^10)" | bc) \ + --n-threads $SLURM_CPUS_PER_TASK \ + --verbose TRUE >> ${DIR_OUT}/job_info-${TRAIT}-${POP}.log +### Clean-up +mv ${DIR_OUT}/GENOMIC_PREDICTIONS_OUTPUT-*.Rds ${DIR_OUT_MAIN} +mv ${DIR_OUT}/job_info-${TRAIT}-${POP}.log ${DIR_OUT_MAIN} +rm -R ${DIR_OUT} diff --git a/exec/01_gp_slurm_job-RYEGRASS.sh b/exec/01_gp_slurm_job-RYEGRASS.sh new file mode 100755 index 0000000..5a32a1e --- /dev/null +++ b/exec/01_gp_slurm_job-RYEGRASS.sh @@ -0,0 +1,117 @@ +#!/bin/bash +#SBATCH --job-name="GS" +#SBATCH --account="dbiopast1" ### EDIT ME: Pick the appropriate account name, e.g. dbiopast1 or dbiopast2 +#SBATCH --ntasks=1 ### LEAVE ME:Request a single task as we will be submitting this as an array job where each job corresponds to a trait +#SBATCH --cpus-per-task=32 ### EDIT ME: Parallelisation across replications, folds and models (more cpu means faster execution time but probably longer time to wait for the Slurm scheduler to find resources to allocate to the job) +#SBATCH --mem=250G ### EDIT ME: Proportional to the input data (will need to test the appropriate memory required, hint use `seff ${JOBID}`) +#SBATCH --time=5-0:0:00 ### EDIT ME: Proportional to the input data, number of folds, replications, and models to be used +################################################################################################### +### Edit the Slurm settings above to match your requirements. +################################################################################################### + +################################################################################################### +### The variables below will be exported from `00_gs_slurm_job_wrapper.sh`: +################################################################################################### +### Input variables (use the absolute path to files to be precise) +### (1) R matrix object with n rows corresponding to samples, and p columns corresponding to the markers or loci. +### Should have no missing data or else will be imputed via mean value imputation. +# GENOTYPE_DATA_RDS='/group/pasture/Jeff/genomic_selection/tests/grape.rds' +GENOTYPE_DATA_RDS=$1 +### (2) Tab-delimited phenotype file where column 1: sample names, column 2: population name, columns 3 and so on refers to the phenotype values of one trait per column. +### Headers for the columns should be named appropriately, e.g. ID, POP, TRAIT1, TRAIT2, etc. +### Missing values are allowed for samples whose phenotypes will be predicted by the best model identified within the population they belong to. +### Missing values may be coded as empty cells, -, NA, na, NaN, missing, and/or MISSING. +# PHENOTYPE_DATA_TSV='/group/pasture/Jeff/genomic_selection/tests/grape_pheno.txt' +PHENOTYPE_DATA_TSV=$2 +### (3) Number of folds for k-fold cross-validation. +# KFOLDS=5 +KFOLDS=$3 +### (4) Number of replications of the k-fold cross-validation each representing a random sorting of the samples hence yielding different ways of partitioning the data. +# NREPS=3 +NREPS=$4 +### (5) Full path to the location of the executable Rscript gp.R +# DIR='/group/pasture/Jeff/gp/exec' +DIR=$5 +################################################################################################### +### Edit the code below, if and only if you have read the documentation or familiar with `src/*.R`: +################################################################################################### +### Define the trait and population to include +N_POPS=$(tail -n+2 $PHENOTYPE_DATA_TSV | cut -f2 - | sort | uniq | wc -l) +TRAIT_IDX=$(echo "((${SLURM_ARRAY_TASK_ID}-1) / ${N_POPS}) + 1" | bc) +POP_IDX=$(echo "${SLURM_ARRAY_TASK_ID} % ${N_POPS}" | bc) +if [ "${POP_IDX}" -eq 0 ] +then + POP_IDX=${N_POPS} +fi +COLUMN_ID=$(echo 2 + ${TRAIT_IDX} | bc) +TRAIT=$(head -n1 $PHENOTYPE_DATA_TSV | cut -f${COLUMN_ID}) +POP=$(tail -n+2 $PHENOTYPE_DATA_TSV | cut -f2 - | sort | uniq | head -n${POP_IDX} | tail -n1) +### Skip leave-one-population-out cross-validation if there is only one population +if [ "${N_POPS}" -eq 1 ] +then + BOOL_ACROSS=FALSE +else + if [ "${POP_IDX}" -eq 1 ] + then + BOOL_ACROSS=TRUE + else + BOOL_ACROSS=FALSE + fi +fi +### Output directories +DIR_OUT_MAIN=${DIR}/output +DIR_OUT=${DIR_OUT_MAIN}/output-${TRAIT}-${POP} +mkdir $DIR_OUT +### Log messages +echo JOB_${SLURM_ARRAY_TASK_ID}-TRAIT_${TRAIT}-POP_${POP} > ${DIR_OUT}/job_info-${TRAIT}-${POP}.log +echo "========================================== +------------------------------------------- + Job Info +------------------------------------------- +SLURM_JOB_ID = $SLURM_JOB_ID +SLURM_JOB_NAME = $SLURM_JOB_NAME +SLURM_JOB_NODELIST = $SLURM_JOB_NODELIST +SLURM_SUBMIT_HOST = $SLURM_SUBMIT_HOST +SLURM_SUBMIT_DIR = $SLURM_SUBMIT_DIR +SLURM_NTASKS = $SLURM_NTASKS +SLURM_ARRAY_TASK_ID = $SLURM_ARRAY_TASK_ID +------------------------------------------- + Variables +------------------------------------------- +GENOTYPE_DATA_RDS : $GENOTYPE_DATA_RDS +PHENOTYPE_DATA_TSV : $PHENOTYPE_DATA_TSV +KFOLDS : $KFOLDS +NREPS : $NREPS +TRAIT : $TRAIT +------------------------------------------- + Output directory +------------------------------------------- +${DIR_OUT} +==========================================" >> ${DIR_OUT}/job_info-${TRAIT}-${POP}.log + +### Load the conda environment +module load Miniconda3/22.11.1-1 +conda init bash +source ~/.bashrc +conda activate genomic_selection + +### Run within and across population replicated k-fold cross-validation and prediction of missing phenotypes +time \ +Rscript ${DIR}/gp.R \ + --fname-geno $GENOTYPE_DATA_RDS \ + --fname-pheno $PHENOTYPE_DATA_TSV \ + --population $POP \ + --dir-output $DIR_OUT \ + --pheno-idx-col-y $COLUMN_ID \ + --bool-within TRUE \ + --bool-across $BOOL_ACROSS \ + --n-folds $KFOLDS \ + --n-reps $NREPS \ + --bool-parallel TRUE \ + --max-mem-Gb $SLURM_MEM_PER_NODE \ + --n-threads $SLURM_CPUS_PER_TASK \ + --verbose TRUE >> ${DIR_OUT}/job_info-${TRAIT}-${POP}.log +### Clean-up +mv ${DIR_OUT}/GENOMIC_PREDICTIONS_OUTPUT-*.Rds ${DIR_OUT_MAIN} +mv ${DIR_OUT}/job_info-${TRAIT}-${POP}.log ${DIR_OUT_MAIN} +rm -R ${DIR_OUT} diff --git a/exec/tests/grape.Rds b/exec/tests/grape.Rds new file mode 100644 index 0000000000000000000000000000000000000000..af372fbec4713159575a1457954c9258221ca9c3 GIT binary patch literal 147501 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