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initial_benchmark_framework.Rmd
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initial_benchmark_framework.Rmd
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---
title: "Initial Benchmark Framework"
output:
html_notebook:
toc: true
---
```{r setup}
source("project_settings.R")
source("functions.R")
```
December 28, 2019
https://github.com/large-scale-gxe-methods/gem-workflow/blob/master/gem_workflow.wdl
# Current WDL
Note, in google cloud, the size of the local-disk is ignored. 'local-disk' is the best option for I/O intensive applications.
```
task run_tests {
File genofile
Float? maf = 0.001
File? samplefile
File phenofile
String sample_id_header
String outcome
Boolean binary_outcome
String covar_headers
String int_covar_num
String? delimiter = ","
String? missing = "NaN"
Boolean robust
Int? stream_snps = 20
Float? tol = 0.000001
Int? memory = 10
Int? cpu = 4
Int? disk = 20
String pheno = if binary_outcome then "1" else "0"
String robust01 = if robust then "1" else "0"
command {
echo -e "SAMPLE_ID_HEADER\n${sample_id_header}\n"\
"PHENOTYPE\n${pheno}\n"\
"PHENO_HEADER\n${outcome}\n"\
"COVARIATES_HEADERS\n${covar_headers}\n"\
"MISSING\n${missing}\n"\
"ROBUST\n${robust01}\n"\
"STREAM_SNPS\n${stream_snps}\n"\
"NUM_OF_INTER_COVARIATE\n${int_covar_num}\n"\
"LOGISTIC_CONVERG_TOL\n${tol}\n"\
"DELIMINATOR\n${delimiter}\n"\
"GENO_FILE_PATH\n${genofile}\n"\
"PHENO_FILE_PATH\n${phenofile}\n"\
"SAMPLE_FILE_PATH\n${samplefile}\n"\
"OUTPUT_PATH\ngem_res"\
> GEM_Input.param
echo "" > resource_usage.log
dstat -c -d -m --nocolor 10 1>>resource_usage.log &
/GEM/GEM -param GEM_Input.param -maf ${maf}
}
runtime {
docker: "quay.io/large-scale-gxe-methods/gem-workflow"
memory: "${memory} GB"
cpu: "${cpu}"
disks: "local-disk ${disk} HDD"
}
output {
File param_file = "GEM_Input.param"
File out = "gem_res"
File resource_usage = "resource_usage.log"
}
}
```
# 1000G benchmarks
## cpus 2 - 8; stream_snps 20 - 2000 (Chromosome 2)
https://app.terra.bio/#workspaces/largescale-gxe-methods/GEM-showcase/job_history/60487ecf-3f8b-4654-a17d-4bc1bead4685
### cpu 2; stream_snps 20
```{r}
if(!file.exists("benchmark1000G.RData")) {
benchmark1000G <- NA
benchmark1000G_4 <- NA
benchmark1000G_2 <- NA
benchmark1000G_3 <- NA
benchmark1000G_5 <- NA
benchmark1000G_5_1 <- NA
benchmark1000G_6 <- NA
benchmark1000G_7 <- NA
benchmark1000G_8 <- NA
benchmark1000G_8_1 <- NA
benchmark1000G_9 <- NA
benchmark1000G_10 <- NA
} else {
load("benchmark1000G.RData")
}
```
```{r fig.height=5,fig.width=12}
benchmark1000G <- do_plots(path_to_workflow = "gs://fc-5fe875e4-6194-4747-8b9d-c2e459422651/60487ecf-3f8b-4654-a17d-4bc1bead4685/run_GEM/2fceb9a5-260c-4350-877e-cddc555c8858/call-run_tests",
cpus=2,
disk="25G",
memory="15G",
maf=0.005,
stream_snps="20",
run_tests_runtime="0h 9m",
plot_description="1000G simulated data\nGEM Showcase\nSubmitted: Dec 30, 1:52 PM",plot_data = benchmark1000G,chr="chr2_")
```
### cpu 2; stream_snps 100
```{r fig.height=5,fig.width=12}
benchmark1000G_2 <- do_plots(path_to_workflow = "gs://fc-5fe875e4-6194-4747-8b9d-c2e459422651/60487ecf-3f8b-4654-a17d-4bc1bead4685/run_GEM/499eb476-637f-4d00-82f7-ffbe00f3bc2d/call-run_tests",
cpus=2,
disk="25G",
memory="15G",
maf=0.005,
stream_snps="100",
run_tests_runtime="0h 11m",
plot_description="1000G simulated data\nGEM Showcase\nSubmitted: Dec 30, 1:52 PM",plot_data = benchmark1000G_2,chr="chr2_")
```
### cpu 2; stream_snps 200
```{r fig.height=5,fig.width=12}
benchmark1000G_3 <- do_plots(path_to_workflow = "gs://fc-5fe875e4-6194-4747-8b9d-c2e459422651/60487ecf-3f8b-4654-a17d-4bc1bead4685/run_GEM/9fea2a53-7f09-4530-8e3d-b03490f14924/call-run_tests",
cpus=2,
disk="25G",
memory="15G",
maf=0.005,
stream_snps="200",
run_tests_runtime="0h 11m",
plot_description="1000G simulated data\nGEM Showcase\nSubmitted: Dec 30, 1:52 PM",plot_data = benchmark1000G_3,chr="chr2_")
```
### cpu 2; stream_snps 1000
```{r fig.height=5,fig.width=12}
benchmark1000G_4 <- do_plots(path_to_workflow = "gs://fc-5fe875e4-6194-4747-8b9d-c2e459422651/60487ecf-3f8b-4654-a17d-4bc1bead4685/run_GEM/3281f361-ae77-4e6c-801f-2e5d0daa56e0/call-run_tests",
cpus=2,
disk="25G",
memory="15G",
maf=0.005,
stream_snps="1000",
run_tests_runtime="0h 25m",
plot_description="1000G simulated data\nGEM Showcase\nSubmitted: Dec 30, 1:52 PM",plot_data = benchmark1000G_4,chr="chr2_")
```
### cpu 4; stream_snps 20
```{r fig.height=5,fig.width=12}
benchmark1000G_5 <- do_plots(path_to_workflow = "gs://fc-5fe875e4-6194-4747-8b9d-c2e459422651/60487ecf-3f8b-4654-a17d-4bc1bead4685/run_GEM/235b2c99-58d9-4c8b-8cc0-89a91eaa1717/call-run_tests",
cpus=4,
disk="25G",
memory="15G",
maf=0.005,
stream_snps="20",
run_tests_runtime="0h 9m",
plot_description="1000G simulated data\nGEM Showcase\nSubmitted: Dec 30, 1:52 PM",plot_data = benchmark1000G_5,chr="chr2_")
```
### cpu 4; stream_snps 100
```{r fig.height=5,fig.width=12}
benchmark1000G_5_1 <- do_plots(path_to_workflow = "gs://fc-5fe875e4-6194-4747-8b9d-c2e459422651/60487ecf-3f8b-4654-a17d-4bc1bead4685/run_GEM/204a4ae0-d8dc-47a5-a208-24eafa4eaca6/call-run_tests",
cpus=4,
disk="25G",
memory="15G",
maf=0.005,
stream_snps="100",
run_tests_runtime="0h 10m",
plot_description="1000G simulated data\nGEM Showcase\nSubmitted: Dec 30, 1:52 PM",plot_data = benchmark1000G_5_1,chr="chr2_")
```
### cpu 4; stream_snps 200
```{r fig.height=5,fig.width=12}
benchmark1000G_6 <- do_plots(path_to_workflow = "gs://fc-5fe875e4-6194-4747-8b9d-c2e459422651/60487ecf-3f8b-4654-a17d-4bc1bead4685/run_GEM/ecf63837-8057-4b15-b8ee-f10727d3c43a/call-run_tests",
cpus=4,
disk="25G",
memory="15G",
maf=0.005,
stream_snps="200",
run_tests_runtime="0h 12m",
plot_description="1000G simulated data\nGEM Showcase\nSubmitted: Dec 30, 1:52 PM",plot_data = benchmark1000G_6,chr="chr2_")
```
### cpu 4; stream_snps 1000
```{r fig.height=5,fig.width=12}
benchmark1000G_7 <- do_plots(path_to_workflow = "gs://fc-5fe875e4-6194-4747-8b9d-c2e459422651/60487ecf-3f8b-4654-a17d-4bc1bead4685/run_GEM/711e6f86-e98b-4250-ba9e-eb404faeae43/call-run_tests",
cpus=4,
disk="25G",
memory="15G",
maf=0.005,
stream_snps="1000",
run_tests_runtime="0h 28m",
plot_description="1000G simulated data\nGEM Showcase\nSubmitted: Dec 30, 1:52 PM",plot_data = benchmark1000G_7,chr="chr2_")
```
### cpu 8; stream_snps 20
```{r fig.height=5,fig.width=12}
benchmark1000G_8 <- do_plots(path_to_workflow = "gs://fc-5fe875e4-6194-4747-8b9d-c2e459422651/60487ecf-3f8b-4654-a17d-4bc1bead4685/run_GEM/fa0083f9-b3a9-4209-a666-394c0cbeef31/call-run_tests",
cpus=8,
disk="25G",
memory="15G",
maf=0.005,
stream_snps="20",
run_tests_runtime="0h 9m",
plot_description="1000G simulated data\nGEM Showcase\nSubmitted: Dec 30, 1:52 PM",plot_data = benchmark1000G_8,chr="chr2_")
```
### cpu 8; stream_snps 100
```{r fig.height=5,fig.width=12}
benchmark1000G_8_1 <- do_plots(path_to_workflow = "gs://fc-5fe875e4-6194-4747-8b9d-c2e459422651/60487ecf-3f8b-4654-a17d-4bc1bead4685/run_GEM/6293ea50-69e6-4610-a9e5-db3f667b0946/call-run_tests",
cpus=8,
disk="25G",
memory="15G",
maf=0.005,
stream_snps="100",
run_tests_runtime="0h 11m",
plot_description="1000G simulated data\nGEM Showcase\nSubmitted: Dec 30, 1:52 PM",plot_data = benchmark1000G_8_1,chr="chr2_")
```
### cpu 8; stream_snps 200
```{r fig.height=5,fig.width=12}
benchmark1000G_9 <- do_plots(path_to_workflow = "gs://fc-5fe875e4-6194-4747-8b9d-c2e459422651/60487ecf-3f8b-4654-a17d-4bc1bead4685/run_GEM/e8130931-c5e3-4126-8a9a-02b69da28251/call-run_tests",
cpus=8,
disk="25G",
memory="15G",
maf=0.005,
stream_snps="200",
run_tests_runtime="0h 10m",
plot_description="1000G simulated data\nGEM Showcase\nSubmitted: Dec 30, 1:52 PM",plot_data = benchmark1000G_9,chr="chr2_")
```
### cpu 8; stream_snps 1000
```{r fig.height=5,fig.width=12}
benchmark1000G_10 <- do_plots(path_to_workflow = "gs://fc-5fe875e4-6194-4747-8b9d-c2e459422651/60487ecf-3f8b-4654-a17d-4bc1bead4685/run_GEM/f539cfe0-236e-4afe-8ff9-acc5cbaf87db/call-run_tests",
cpus=8,
disk="25G",
memory="15G",
maf=0.005,
stream_snps="1000",
run_tests_runtime="0h 19m",
plot_description="1000G simulated data\nGEM Showcase\nSubmitted: Dec 30, 1:52 PM",plot_data = benchmark1000G_10,chr="chr2_")
```
```{r}
save(list=ls()[grep(pattern="benchmark",ls())],file="benchmark1000G.RData")
```
# UK Biobank - chromosome 22 - subset 10K
## Stream SNPs: 40
https://app.terra.bio/#workspaces/largescale-gxe-implementation/ukb_gene_diet/job_history/03225dc7-2579-4a31-a3b0-6a114e20d90f
https://job-manager.dsde-prod.broadinstitute.org/jobs/0265bc89-0f70-41c6-a800-d9fd5b255882
```{r fig.height=5,fig.width=12}
benchmark_ukb10k_1 <- do_plots(path_to_workflow = "gs://fc-secure-006196ce-f92c-4096-80cf-80a7277524dc/03225dc7-2579-4a31-a3b0-6a114e20d90f/run_GEM/0265bc89-0f70-41c6-a800-d9fd5b255882/call-run_tests",
cpus=8,
disk="25G",
memory="50G",
maf=0.005,
stream_snps=40,
plot_description="UK Biobank Chr22 - subset 10K\nlargescale-gxe-implementation/ukb_gene_diet\nExploring stream_snps\nSubmitted:Dec 23, 2019, 4:36 PM")
```
## Stream SNPs: 200
https://app.terra.bio/#workspaces/largescale-gxe-implementation/ukb_gene_diet/job_history/03225dc7-2579-4a31-a3b0-6a114e20d90f
https://job-manager.dsde-prod.broadinstitute.org/jobs/fe6a1f5b-b727-47c2-80b1-eba1fd1ee529
```{r fig.height=5,fig.width=12}
benchmark_ukb10k_2 <- do_plots(path_to_workflow = "gs://fc-secure-006196ce-f92c-4096-80cf-80a7277524dc/03225dc7-2579-4a31-a3b0-6a114e20d90f/run_GEM/fe6a1f5b-b727-47c2-80b1-eba1fd1ee529/call-run_tests",
cpus=8,
disk="25G",
memory="50G",
maf=0.005,
stream_snps=200,
plot_description="UK Biobank Chr22 - subset 10K\nlargescale-gxe-implementation/ukb_gene_diet\nExploring stream_snps\nSubmitted:Dec 23, 2019, 4:36 PM")
```
# UK Biobank - chromosome 22 - ALL SNPs
## Stream SNPs: 200
https://app.terra.bio/#workspaces/largescale-gxe-implementation/ukb_gene_diet/job_history/14905b3a-4c32-467f-a435-43b285e74628
https://job-manager.dsde-prod.broadinstitute.org/jobs/d9a741c3-6d10-4716-a733-43f3f94a9cb7
```{r fig.height=5,fig.width=12}
benchmark_ukb_1 <- do_plots(path_to_workflow = "gs://fc-secure-006196ce-f92c-4096-80cf-80a7277524dc/14905b3a-4c32-467f-a435-43b285e74628/run_GEM/d9a741c3-6d10-4716-a733-43f3f94a9cb7/call-run_tests",
cpus=32,
disk="50G",
memory="25G",
maf=0.005,
stream_snps=200,
run_tests_runtime="6h 11m",
plot_description="UK Biobank Chr22\nlargescale-gxe-implementation/ukb_gene_diet\nTest: Stream_200\nSubmitted:Dec 23, 2019, 5:19 PM")
```
## Stream SNPs: 200 - Increased Memory
https://app.terra.bio/#workspaces/largescale-gxe-implementation/ukb_gene_diet/job_history/15023ed0-ac28-4e7d-b32a-3f93810b6164
https://job-manager.dsde-prod.broadinstitute.org/jobs/35babd3d-8b0a-4d5a-9068-2c2c50f6590a
```{r fig.height=5,fig.width=12}
benchmark_ukb_2 <- do_plots(path_to_workflow = "gs://fc-secure-006196ce-f92c-4096-80cf-80a7277524dc/15023ed0-ac28-4e7d-b32a-3f93810b6164/run_GEM/35babd3d-8b0a-4d5a-9068-2c2c50f6590a/call-run_tests",
cpus=32,
disk="50G",
memory="60G",
maf=0.005,
stream_snps=200,
run_tests_runtime="6h 2m",
plot_description="UK Biobank Chr22\nlargescale-gxe-implementation/ukb_gene_diet\nTest: Stream_200, 60GB memory\nSubmitted:Dec 23, 2019, 5:19 PM")
```