#
# Neuronal data from Gasparoni et al., 2017
#
#.libPaths("/DEEP_fhgfs/projects/plutsik/Rlib_clean_RnBeads/")
DATA.DIR="/DEEP_fhgfs/projects/plutsik/projects/neuron/"
PROJECT.DIR = "/TL/deep/projects/work/mscherer/projects/MeDeCom/test/"
#data<-read.table(file.path(DATA.DIR, "20170419_GasSort_GuiSort_manuscriptData.txt"))
#pd<-read.table(file.path(DATA.DIR, "20170419_GasSort_GuiSort_manuscriptSampleSheet.txt"), sep='\t', header=TRUE)
#probe.list<-rownames(data)
library(DecompPipeline)
library(RnBeads)
#rnb.options(disk.dump.big.matrices=FALSE)
#rnb.set<-RnBeadSet(pd, probe.list, as.matrix(data))
PROJECT.DIR = "/TL/deep/projects/work/mscherer/projects/MeDeCom/test/"
rnb.set <- load.rnb.set("/TL/deep/projects/nobackup/mage/data/publicationData/processed/TCGA_OV___AH/rnbeads_report/rnbSet_unnormalized/")
res<-prepare_data(
RNB_SET=rnb.set,
WORK_DIR=file.path(PROJECT.DIR),
SAMPLE_SELECTION_COL=NA,
SAMPLE_SELECTION_GREP=NA,
PHENO_COLUMNS="bcr",
ID_COLUMN=NULL,
NORMALIZATION="none",
REF_CT_COLUMN=NA,
REF_RNB_SET="/DEEP_fhgfs/projects/mscherer/data/450K/Reinius_Blood_Reference_unnormalized.zip",
REF_RNB_CT_COLUMN="tissue/cell type",
PREPARE_TRUE_PROPORTIONS=FALSE,
TRUE_A_TOKEN=NA,
HOUSEMAN_A_TOKEN=NA,
ESTIMATE_HOUSEMAN_PROP=FALSE,
FILTER_BEADS=!is.null(rnb.set@covg.sites),
FILTER_INTENSITY=inherits(rnb.set, "RnBeadRawSet"),
FILTER_NA=T,
FILTER_CONTEXT=TRUE,
FILTER_SNP=TRUE,
FILTER_SOMATIC=TRUE,
FILTER_CROSS_REACTIVE=T,
snp.list="/DEEP_fhgfs/projects/mscherer/data/EPIC/Radar_Genetik/commonSNPs137.txt",
execute.lump=T,
remove.ICA = T,
dist.snps = T,
conf.fact.ICA = "vital_status"
)
cg_subsets<-prepare_CG_subsets(
rnb.set=res$rnb.set.filtered,
MARKER_SELECTION=c("random","var"),#,"edec_stage0","pheno","houseman2012"),#,"houseman2014","jaffe2014","rowFstat","random","pca","var","hybrid","range","custom","pcadapt","all"),
WD=file.path(PROJECT.DIR,"data","foo_foo_none"),
N_MARKERS = 4242,
REF_DATA_SET = "/DEEP_fhgfs/projects/mscherer/data/450K/Reinius_Blood_Reference_unnormalized.zip",
REF_PHENO_COLUMN = "tissue/cell type",
N_PRIN_COMP = 2,
RANGE_DIFF = 0.1,
REMOVE_CORRELATED = T,
CUSTOM_MARKER_FILE = "/DEEP_fhgfs/projects/mscherer/data/Aussois/MeDeCom/marker_file_Sophie.txt",
K.prior=2
)
md.res <- start.edec.analysis(
rnb.set=res$rnb.set.filtered,
work.dir=file.path(PROJECT.DIR),
cg_groups=cg_subsets,
Ks=2:10,
factorviz.outputs=T
)
#
# Neuronal data from Gasparoni et al., 2017
#
#.libPaths("/DEEP_fhgfs/projects/plutsik/Rlib_clean_RnBeads/")
DATA.DIR="/DEEP_fhgfs/projects/plutsik/projects/neuron/"
PROJECT.DIR = "/TL/deep/projects/work/mscherer/projects/MeDeCom/test/"
#data<-read.table(file.path(DATA.DIR, "20170419_GasSort_GuiSort_manuscriptData.txt"))
#pd<-read.table(file.path(DATA.DIR, "20170419_GasSort_GuiSort_manuscriptSampleSheet.txt"), sep='\t', header=TRUE)
#probe.list<-rownames(data)
library(DecompPipeline)
library(RnBeads)
#rnb.options(disk.dump.big.matrices=FALSE)
#rnb.set<-RnBeadSet(pd, probe.list, as.matrix(data))
rnb.set <- load.rnb.set("/TL/deep/projects/nobackup/mage/data/publicationData/processed/TCGA_OV___AH/rnbeads_report/rnbSet_unnormalized/")
res<-prepare_data(
RNB_SET=rnb.set,
WORK_DIR=file.path(PROJECT.DIR),
SAMPLE_SELECTION_COL=NA,
SAMPLE_SELECTION_GREP=NA,
PHENO_COLUMNS="bcr",
ID_COLUMN=NULL,
NORMALIZATION="none",
REF_CT_COLUMN=NA,
REF_RNB_SET="/DEEP_fhgfs/projects/mscherer/data/450K/Reinius_Blood_Reference_unnormalized.zip",
REF_RNB_CT_COLUMN="tissue/cell type",
PREPARE_TRUE_PROPORTIONS=FALSE,
TRUE_A_TOKEN=NA,
HOUSEMAN_A_TOKEN=NA,
ESTIMATE_HOUSEMAN_PROP=FALSE,
FILTER_BEADS=!is.null(rnb.set@covg.sites),
FILTER_INTENSITY=inherits(rnb.set, "RnBeadRawSet"),
FILTER_NA=T,
FILTER_CONTEXT=TRUE,
FILTER_SNP=TRUE,
FILTER_SOMATIC=TRUE,
FILTER_CROSS_REACTIVE=T,
snp.list="/DEEP_fhgfs/projects/mscherer/data/EPIC/Radar_Genetik/commonSNPs137.txt"
)
cg_subsets<-prepare_CG_subsets(
rnb.set=res$rnb.set.filtered,
MARKER_SELECTION=c("edec_stage0"),
WD=file.path(PROJECT.DIR,"data","foo_foo_none"),
N_MARKERS = 4242,
REF_DATA_SET = "/DEEP_fhgfs/projects/mscherer/data/450K/Reinius_Blood_Reference_unnormalized.zip",
REF_PHENO_COLUMN = "tissue/cell type"
# N_PRIN_COMP = 2,
# RANGE_DIFF = 0.1,
# CUSTOM_MARKER_FILE = "/DEEP_fhgfs/projects/mscherer/data/Aussois/MeDeCom/marker_file_Sophie.txt",
# K.prior=2
)
# md.res <- start.refreeewas.analysis(
# rnb.set=res$rnb.set.filtered,
# work.dir=file.path(PROJECT.DIR),
# cg_groups=cg_subsets,
# Ks=2:10,
# factorviz.outputs=T
# )
# md.res<-start_medecom_analysis(
# rnb.set=res$rnb.set.filtered,
# WORK_DIR=file.path(PROJECT.DIR),
# cg_groups=cg_subsets,
# Ks=2:10,
# LAMBDA_GRID=c(0,10^(-5:-1)),
# SAMPLE_SUBSET=NULL,
# K_FIXED=NULL,
# WRITE_FILES=TRUE,
# startT=NULL,
# startA=NULL,
# CLUSTER_SUBMIT=FALSE,
# CLUSTER_RDIR=NA,
# CLUSTER_HOSTLIST="*",
# CLUSTER_MEMLIMIT="5G",
# # MAX_JOBS=1000,
# # WAIT_TIME="30m",
# # PORTIONS=FALSE,
# # JOB_FILE=NA,
# CLEANUP=FALSE
# )
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.