Commit 784d8492 authored by Gael  MILLOT's avatar Gael MILLOT
Browse files

v6.0.0 release updated

parent 39527951
......@@ -25,7 +25,7 @@ Download the desired Tagged version, never the current master.
Open rogge_12231.conf
Set the parameters
Start the job using a command like:
STARTTIME_SH=$(date) ; JOB_ID_SH=$(date -d "$STARTTIME_SH" +%s) ; sh /pasteur/homes/gmillot/Git_versions_to_use/rogge_12231-v5.0.0/rogge_12231_workflow.sh -c /pasteur/homes/gmillot/Git_versions_to_use/rogge_12231-v5.0.0/rogge_12231.conf | tee /pasteur/homes/gmillot/rogge12231/${JOB_ID_SH}_workflow_log &
STARTTIME_SH=$(date) ; JOB_ID_SH=$(date -d "$STARTTIME_SH" +%s) ; sh /pasteur/homes/gmillot/Git_versions_to_use/rogge_12231-v6.0.0/rogge_12231_workflow.sh -c /pasteur/homes/gmillot/Git_versions_to_use/rogge_12231-v6.0.0/rogge_12231.conf | tee /pasteur/homes/gmillot/rogge12231/${JOB_ID_SH}_workflow_log &
#### FILE DESCRIPTION
......@@ -60,6 +60,11 @@ Check for updated versions (most recent tags) at https://gitlab.pasteur.fr/gmill
#### WHAT'S NEW IN
## v6.0.0
Bug regarding the randomness fixed
## v5.0.0
Gene filtering added
......
......@@ -15,8 +15,8 @@ alias R_conf='module load gcc/4.9.4 R/3.5.0 ; Rscript'
export r_main_functions_conf=/pasteur/homes/gmillot/Git_versions_to_use/cute_little_R_functions-v4.5.0/cute_little_R_functions.R
# export r_main_functions_conf=https://gitlab.pasteur.fr/gmillot/cute_little_R_functions/raw/v4.5.0/cute_little_R_functions.R
export bash_main_functions_conf=/pasteur/homes/gmillot/Git_versions_to_use/little_bash_functions-v1.1.0/little_bash_functions.sh
export r_main_conf=/pasteur/homes/gmillot/Git_versions_to_use/rogge_12231-v5.0.0/rogge_12231_main_analysis.R
export r_compil_conf=/pasteur/homes/gmillot/Git_versions_to_use/rogge_12231-v5.0.0/rogge_12231_data_compilation.R
export r_main_conf=/pasteur/homes/gmillot/Git_versions_to_use/rogge_12231-v6.0.0/rogge_12231_main_analysis.R
export r_compil_conf=/pasteur/homes/gmillot/Git_versions_to_use/rogge_12231-v6.0.0/rogge_12231_data_compilation.R
#_______________________________________________________________________________________________
# GENERAL PARAMETERS
......@@ -49,7 +49,7 @@ R_RANDOM_SEED="TRUE" #♥ if FALSE, set.seed(1) is systematically used at the be
# "valid_boot" limma and rf training are run once but bootstrap of the validation set 9 indiv (df.nano$cohort_id == "cohortR") using LOOP_NB_CONF parameter
# "full_cross_validation" rows of the dataset are randomly split in two (no replacement), according to CROSS_VALID_RATIO, forming the discovery and validation set
R_ANALYSIS_KIND="valid_boot"
CROSS_VALID_RATIO=0.8 # proportion (nb indiv randomly selected (wo replacement) for the discovery set) / (total number of indiv)
CROSS_VALID_RATIO=0.8375 # proportion (nb indiv randomly selected (wo replacement) for the discovery set) / (total number of indiv)
# -> the validation set is formed by the remaining indiv, with proportion 1 - CROSS_VALID_RATIO
################ other
......
......@@ -49,7 +49,7 @@ for(i in 1:length(param.list)){
################################ DEBUG
activate.pdf <- TRUE # leave it here active !!! Required for cluster computation (used to derive rogge_12231_manual_graph_adjustment.R from this code)
debug2 <- '
rm(list = ls())
erase.objects <- TRUE
......@@ -72,7 +72,7 @@ cut.off.freq.for.selected.genes <- 0.01 # graph file parameter
# data.frame(PARAM = tempo.arg.names, ARG = args) # for debug mode
# activate.pdf <- TRUE ; cat(paste0("\n\n================\n\nERROR: ACTIVE GRAPH FILE PARAMETERS\n\n================\n\n")) # graph file parameter
......
......@@ -90,9 +90,9 @@ ml.bootstrap.nb <- 2
label.size <- 6
optional.text <- ""
slurm.loop.nb <- 1
analysis.kind <- "longit"
cross.valid.ratio <- 0.8
random.seed <- FALSE
analysis.kind <- "valid_boot"
cross.valid.ratio <- 0.8375
random.seed <- TRUE
'
# eval(parse(text = debug2)) ; cat(paste0("\n\n================\n\nERROR: ACTIVE DEBUG VALUES\n\n================\n\n")) ; stop()
......@@ -249,6 +249,7 @@ pdf.nb <- dev.cur()
################ randomness ignition
if(random.seed == TRUE){
set.seed(NULL) # to inactivate any potential seed set, otherwise sample(x = 0:(2^31-1), size = 1) will always give the same
used.set.seed1 <- sample(x = 0:(2^31-1), size = 1)
}else{
used.set.seed1 <- 1
......@@ -309,7 +310,7 @@ seb <- log2(df.nano[, i_seb]) # log2 of the SEB columns
# ```{r mix, cache=TRUE}
# a <- c(unlist(lps), unlist(seb))
# fixed random seed required for mixtools::normalmixEM. BEWARE: I had to put a new random seed after this gene filtering step
# fixed random seed required for mixtools::normalmixEM. BEWARE: I had to put a set.seed(NULL) after this gene filtering step
used.set.seed_normalmix <- 12345
set.seed(used.set.seed_normalmix)
tempo.cat <- paste0("BEWARE: NON RANDOM set.seed(", used.set.seed_normalmix, ") SYSTEMATICALLY ACTIVATED FOR GENE FILTERING STEP")
......@@ -410,6 +411,7 @@ backup.name <- c(backup.name, "df.nano")
# resetting the random.seed because of the fixed one used.set.seed_normalmix <- 12345 added for gene filtering
if(random.seed == TRUE){
set.seed(NULL) # to inactivate any potential seed set, otherwise sample(x = 0:(2^31-1), size = 1) will always give the same
used.set.seed2 <- sample(x = 0:(2^31-1), size = 1)
}else{
used.set.seed2 <- 1
......@@ -719,6 +721,7 @@ fun_export_data(path = path.out, data = "################################ VALIDA
# ```{r train, warning=FALSE} #### 20190313 checked compared to ReproducibleCode_20190109.Rmd
if(random.seed == TRUE){
set.seed(NULL) # to inactivate any potential seed set, otherwise sample(x = 0:(2^31-1), size = 1) will always give the same
used.set.seed3 <- sample(x = 0:(2^31-1), size = 1)
}else{
used.set.seed3 <- 1
......@@ -1073,6 +1076,7 @@ for(i0 in 1:pages.print.nb){
# ```{r learners_freq, results='asis', cache=TRUE}
if(random.seed == TRUE){
set.seed(NULL) # to inactivate any potential seed set, otherwise sample(x = 0:(2^31-1), size = 1) will always give the same
used.set.seed4 <- sample(x = 0:(2^31-1), size = 1)
}else{
used.set.seed4 <- 1
......
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