xDefineEQTL is supposed to extract eQTL-gene pairs given a list
of SNPs or a customised eQTL mapping data.
xDefineEQTL(data = NULL, include.eQTL = c(NA, "JKscience_CD14",
"JKscience_LPS2", "JKscience_LPS24", "JKscience_IFN", "JKscience_TS2A",
"JKscience_TS2A_CD14", "JKscience_TS2A_LPS2", "JKscience_TS2A_LPS24",
"JKscience_TS2A_IFN", "JKscience_TS2B", "JKscience_TS2B_CD14",
"JKscience_TS2B_LPS2", "JKscience_TS2B_LPS24", "JKscience_TS2B_IFN",
"JKscience_TS3A", "JKng_bcell", "JKng_bcell_cis", "JKng_bcell_trans",
"JKng_mono", "JKng_mono_cis", "JKng_mono_trans", "JKpg_CD4",
"JKpg_CD4_cis", "JKpg_CD4_trans", "JKpg_CD8", "JKpg_CD8_cis",
"JKpg_CD8_trans", "JKnc_neutro", "JKnc_neutro_cis",
"JKnc_neutro_trans", "WESTRAng_blood", "WESTRAng_blood_cis",
"WESTRAng_blood_trans", "JK_nk", "JK_nk_cis", "JK_nk_trans",
"GTEx_V4_Adipose_Subcutaneous", "GTEx_V4_Artery_Aorta",
"GTEx_V4_Artery_Tibial", "GTEx_V4_Esophagus_Mucosa",
"GTEx_V4_Esophagus_Muscularis", "GTEx_V4_Heart_Left_Ventricle",
"GTEx_V4_Lung", "GTEx_V4_Muscle_Skeletal", "GTEx_V4_Nerve_Tibial",
"GTEx_V4_Skin_Sun_Exposed_Lower_leg", "GTEx_V4_Stomach",
"GTEx_V4_Thyroid", "GTEx_V4_Whole_Blood",
"GTEx_V6p_Adipose_Subcutaneous",
"GTEx_V6p_Adipose_Visceral_Omentum", "GTEx_V6p_Adrenal_Gland",
"GTEx_V6p_Artery_Aorta", "GTEx_V6p_Artery_Coronary",
"GTEx_V6p_Artery_Tibial",
"GTEx_V6p_Brain_Anterior_cingulate_cortex_BA24",
"GTEx_V6p_Brain_Caudate_basal_ganglia",
"GTEx_V6p_Brain_Cerebellar_Hemisphere", "GTEx_V6p_Brain_Cerebellum",
"GTEx_V6p_Brain_Cortex", "GTEx_V6p_Brain_Frontal_Cortex_BA9",
"GTEx_V6p_Brain_Hippocampus", "GTEx_V6p_Brain_Hypothalamus",
"GTEx_V6p_Brain_Nucleus_accumbens_basal_ganglia",
"GTEx_V6p_Brain_Putamen_basal_ganglia",
"GTEx_V6p_Breast_Mammary_Tissue",
"GTEx_V6p_Cells_EBVtransformed_lymphocytes",
"GTEx_V6p_Cells_Transformed_fibroblasts", "GTEx_V6p_Colon_Sigmoid",
"GTEx_V6p_Colon_Transverse",
"GTEx_V6p_Esophagus_Gastroesophageal_Junction",
"GTEx_V6p_Esophagus_Mucosa", "GTEx_V6p_Esophagus_Muscularis",
"GTEx_V6p_Heart_Atrial_Appendage", "GTEx_V6p_Heart_Left_Ventricle",
"GTEx_V6p_Liver", "GTEx_V6p_Lung", "GTEx_V6p_Muscle_Skeletal",
"GTEx_V6p_Nerve_Tibial", "GTEx_V6p_Ovary", "GTEx_V6p_Pancreas",
"GTEx_V6p_Pituitary", "GTEx_V6p_Prostate",
"GTEx_V6p_Skin_Not_Sun_Exposed_Suprapubic",
"GTEx_V6p_Skin_Sun_Exposed_Lower_leg",
"GTEx_V6p_Small_Intestine_Terminal_Ileum", "GTEx_V6p_Spleen",
"GTEx_V6p_Stomach", "GTEx_V6p_Testis", "GTEx_V6p_Thyroid",
"GTEx_V6p_Uterus", "GTEx_V6p_Vagina", "GTEx_V6p_Whole_Blood",
"eQTLGen",
"eQTLGen_cis", "eQTLGen_trans", "scRNAseq_eQTL_Bcell",
"scRNAseq_eQTL_CD4", "scRNAseq_eQTL_CD8", "scRNAseq_eQTL_cMono",
"scRNAseq_eQTL_DC", "scRNAseq_eQTL_Mono", "scRNAseq_eQTL_ncMono",
"scRNAseq_eQTL_NK", "scRNAseq_eQTL_PBMC", "jpRNAseq_eQTL_Bcell",
"jpRNAseq_eQTL_CD4", "jpRNAseq_eQTL_CD8", "jpRNAseq_eQTL_Mono",
"jpRNAseq_eQTL_NK", "jpRNAseq_eQTL_PBMC", "Pi_eQTL_Bcell",
"Pi_eQTL_Blood", "Pi_eQTL_CD14", "Pi_eQTL_CD4", "Pi_eQTL_CD8",
"Pi_eQTL_IFN", "Pi_eQTL_LPS2", "Pi_eQTL_LPS24", "Pi_eQTL_Monocyte",
"Pi_eQTL_Neutrophil", "Pi_eQTL_NK", "Pi_eQTL_shared_CD14",
"Pi_eQTL_shared_IFN", "Pi_eQTL_shared_LPS2", "Pi_eQTL_shared_LPS24"),
eQTL.customised = NULL, verbose = TRUE,
RData.location = "http://galahad.well.ox.ac.uk/bigdata")NULL or an input vector containing SNPs. If NULL, all SNPs will be considered. If a input vector containing SNPs, SNPs should be provided as dbSNP ID (ie starting with rs). Alternatively, they can be in the format of 'chrN:xxx', where N is either 1-22 or X, xxx is number; for example, 'chr16:28525386'
genes modulated by eQTL (also Lead SNPs or in LD with Lead SNPs) are also included. By default, it is 'NA' to disable this option. Otherwise, those genes modulated by eQTL will be included. Pre-built eQTL datasets are detailed in the section 'Note'
a user-input matrix or data frame with 4 columns: 1st column for SNPs/eQTLs, 2nd column for Genes, 3rd for eQTL mapping significance level (p-values or FDR), and 4th for contexts (required even though only one context is input). Alternatively, it can be a file containing these 4 columns. It is designed to allow the user analysing their eQTL data. This customisation (if provided) will populate built-in eQTL data; mysql -e "use pi; SELECT rs_id_dbSNP147_GRCh37p13,gene_name,pval_nominal,Tissue FROM GTEx_V7_pair WHERE rs_id_dbSNP147_GRCh37p13!='.';" > /var/www/bigdata/eQTL.customised.txt
logical to indicate whether the messages will be displayed in the screen. By default, it sets to true for display
the characters to tell the location of built-in
RData files. See xRDataLoader for details
a data frame with following columns:
SNP: eQTLs
Gene: eQTL-containing genes
Sig: the eQTL mapping significant level
Context: the context in which eQTL data was generated
# NOT RUN {
# Load the library
library(XGR)
# }
# NOT RUN {
RData.location <- "http://galahad.well.ox.ac.uk/bigdata"
# }
# NOT RUN {
# a) provide the SNPs with the significance info
data(ImmunoBase)
gr <- ImmunoBase$AS$variants
data <- gr$Variant
# b) define eQTL genes
df_SGS <- xDefineEQTL(data, include.eQTL="JKscience_TS2A",
RData.location=RData.location)
# }
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