Nothing
## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(
collapse=TRUE,
comment="#>",
warning=FALSE,
error=FALSE,
eval=FALSE
)
## ----library, message=FALSE, warning=FALSE, error=FALSE-----------------------
# library(BiocStyle)
# library(HPAanalyze)
# library(dplyr)
# library(ggplot2)
## -----------------------------------------------------------------------------
# data <- hpaDownload(downloadList = "histology",
# version = "v18")
## -----------------------------------------------------------------------------
# gene_list_2 <- c("TP53", "EGFR", "CD44", "PTEN", "IDH1", "IDH2", "CYCS")
#
# # Panel 2A
# tissue_list_2 <- c("skin 1", "cerebellum", "breast")
#
# plot_2a <-
# hpaVisTissue(data = data,
# targetGene = gene_list_2,
# targetTissue = tissue_list_2,
# color = c("#eff3ff", "#bdd7e7","#6baed6", "#2171b5"))
#
# ggsave(filename = "plot_2a.pdf",
# plot = plot_2a,
# device = "pdf")
#
# # Panel 2B
# cancer_list_2 <- c("breast cancer", "glioma", "lymphoma", "prostate cancer")
#
# plot_2b <-
# hpaVisPatho(data = data,
# targetGene = gene_list_2,
# targetCancer = cancer_list_2)
#
# ggsave(filename = "plot_2b.pdf",
# plot = plot_2b,
# device = "pdf",
# width = 7,
# height = 5)
#
# # Panel 2C
# plot_2c <-
# hpaVisSubcell(data = data,
# targetGene = gene_list_2,
# color = c("white", "black"),
# reliability = c("enhanced", "supported", "approved"))
#
# ggsave(filename = "plot_2c.pdf",
# plot = plot_2c,
# device = "pdf")
## -----------------------------------------------------------------------------
# gene_list_3 <-
# c("GFAP", "EGFR", "PDGFRA", "PIK3CA", "PTEN", "BRAF", "MDM2", "MDM4", "CDK4")
#
# # Panel 3A
# tissue_list_3 <- c("hippocampus", "cerebral cortex")
#
# plot_3a <-
# hpaVisTissue(data = data,
# targetGene = gene_list_3,
# targetTissue = tissue_list_3,
# color = c("#eff3ff", "#bdd7e7","#6baed6", "#2171b5"))
#
# ggsave(filename = "plot_3a.pdf",
# plot = plot_3a,
# device = "pdf",
# width = 7,
# height = 5)
#
# # Panel 3B
# plot_3b <-
# hpaVisPatho(data = data,
# targetGene = gene_list_3,
# targetCancer = "glioma")
#
# ggsave(filename = "plot_3b.pdf",
# plot = plot_3b,
# device = "pdf",
# width = 7,
# height = 5)
#
# # Panel 3C
# gene_list_3c <- c("PTEN", "H3F3A", "DAXX", "PML")
#
# plot_3c <-
# hpaVisSubcell(data = data,
# targetGene = gene_list_3c,
# color = c("white", "black"),
# reliability = c("enhanced", "supported", "approved"))
#
# ggsave(filename = "plot_3c.pdf",
# plot = plot_3c,
# device = "pdf",
# width = 4,
# height = 3)
## -----------------------------------------------------------------------------
# gene_list_4 <- c("GCH1", "PTS", "SPR", "DHFR")
#
# # Panel 4A
# tissue_list_4 <- c("hippocampus", "cerebral cortex", "caudate")
#
# plot_4a <-
# hpaVisTissue(data = data,
# targetGene = gene_list_4,
# targetTissue = tissue_list_4,
# color = c("#eff3ff", "#bdd7e7","#6baed6", "#2171b5"))
#
# ggsave(filename = "plot_4a.pdf",
# plot = plot_4a,
# device = "pdf",
# width = 5,
# height = 4)
#
# # Panel 4B
# plot_4b <-
# hpaVisPatho(data = data,
# targetGene = gene_list_4,
# targetCancer = "glioma")
#
# ggsave(filename = "plot_4b.pdf",
# plot = plot_4b,
# device = "pdf",
# width = 5,
# height = 4)
#
# # Panel 4C
# # Figure was generated with the GlioVis portal http://gliovis.bioinfo.cnio.es/
# # Accessed: June 19, 2019
# #
# # Plotting:
# # Navigate through tabs: Explore > Survival > Kaplan-Meier > Plot
# #
# # Parameters:
# # - Dataset: Adult Rembrandt
# # - Gene: SPR or DHFR
# # - Histology: All
# # - Subtype: All
# # - Cutoff: Median
# # - Plot options: use default options
# # - Download: use default options
# #
# # Retrieving plotting data: (same parameters)
# # Navigate through tabs: Explore > Survival > Kaplan-Meier > Plot
# # Buttons: Download > CSV
#
# # Panel 4D
# plot_4d <-
# hpaVisSubcell(data = data,
# targetGene = gene_list_4,
# color = c("white", "black"),
# reliability = c("enhanced", "supported", "approved"))
#
# ggsave(filename = "plot_4d.pdf",
# plot = plot_4d,
# device = "pdf",
# width = 4,
# height = 3)
## -----------------------------------------------------------------------------
# hpaSubset(data = data,
# targetGene = "SLC2A3",
# targetTissue = c("hippocampus", "cerebral cortex", "caudate"),
# targetCellType = "glial cells",
# targetCancer = "glioma")
#
# # $normal_tissue
# # # A tibble: 3 x 6
# # ensembl gene tissue cell_type level reliability
# # <chr> <chr> <chr> <chr> <chr> <chr>
# # 1 ENSG00000059804 SLC2A3 caudate glial cells Not detected Approved
# # 2 ENSG00000059804 SLC2A3 cerebral cortex glial cells Not detected Approved
# # 3 ENSG00000059804 SLC2A3 hippocampus glial cells Not detected Approved
# #
# # $pathology
# # # A tibble: 1 x 11
# # ensembl gene cancer high medium low not_detected prognostic_favo~
# # <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
# # 1 ENSG00~ SLC2~ glioma 1 2 1 8 NA
# # # ... with 3 more variables: unprognostic_favorable <dbl>,
# # # prognostic_unfavorable <dbl>, unprognostic_unfavorable <dbl>
# #
# # $subcellular_location
# # # A tibble: 1 x 11
# # ensembl gene reliability enhanced supported approved uncertain single_cell_var~
# # <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
# # 1 ENSG00~ SLC2~ Approved NA NA Plasma ~ NA NA
# # # ... with 3 more variables: single_cell_var_spatial <chr>,
# # # cell_cycle_dependency <chr>, go_id <chr>
#
#
# SLC2A3xml <- hpaXmlGet("SLC2A3", version = "v18")
#
# SLC2A3_ab <- hpaXmlAntibody(SLC2A3xml)
# SLC2A3_ab
# # id releaseDate releaseVersion RRID
# # <chr> <chr> <chr> <chr>
# # 1 CAB002763 2006-03-13 1.2 NA
# # 2 HPA006539 2008-02-15 3.1 AB_1078984
#
# SLC2A3_expr <- hpaXmlTissueExpr(SLC2A3xml)
# str(SLC2A3_expr[[1]])
# # Classes ‘tbl_df’, ‘tbl’ and 'data.frame': 330 obs. of 18 variables:
# # $ patientId : chr "2212" "2374" "2068" "2154" ...
# # $ age : chr "35" "44" "38" "66" ...
# # $ sex : chr "Male" "Female" "Male" "Female" ...
# # $ staining : chr NA NA NA NA ...
# # $ intensity : chr NA NA NA NA ...
# # $ quantity : chr NA NA NA NA ...
# # $ location : chr NA NA NA NA ...
# # $ imageUrl : chr "http://v18.proteinatlas.org/images/2763/6778_B_4_5.jpg" "http://v18.proteinatlas.org/images/2763/6778_B_5_5.jpg" "http://v18.proteinatlas.org/images/2763/6778_A_3_2.jpg" "http://v18.proteinatlas.org/images/2763/6778_A_1_2.jpg" ...
# # $ snomedCode1 : chr "M-00100" "M-00100" "M-00100" "M-00100" ...
# # $ snomedCode2 : chr "T-93000" "T-93000" "T-66000" "T-66000" ...
# # $ snomedCode3 : chr NA NA NA NA ...
# # $ snomedCode4 : chr NA NA NA NA ...
# # $ snomedCode5 : chr NA NA NA NA ...
# # $ tissueDescription1: chr "Normal tissue, NOS" "Normal tissue, NOS" "Normal tissue, NOS" "Normal tissue, NOS" ...
# # $ tissueDescription2: chr "Adrenal gland" "Adrenal gland" "Appendix" "Appendix" ...
# # $ tissueDescription3: chr NA NA NA NA ...
# # $ tissueDescription4: chr NA NA NA NA ...
# # $ tissueDescription5: chr NA NA NA NA ...
#
# dir.create("img")
#
# SLC2A3_norm <-
# SLC2A3_expr[[1]] %>%
# filter(tissueDescription1 == "Normal tissue, NOS") %>%
# filter(tissueDescription2 %in% c("Cerebral cortex", "Hippocampus", "Lateral ventricle wall"))
#
# for (i in 1:nrow(SLC2A3_norm)) {
# download.file(SLC2A3_norm$imageUrl[i],
# destfile = paste0("img/", SLC2A3_ab$id[1], "_",
# SLC2A3_norm$patientId[i], "_",
# SLC2A3_norm$tissueDescription2[i], "_",
# SLC2A3_norm$staining[i],
# ".jpg"),
# mode = "wb")
# }
#
# SLC2A3_glioma <-
# SLC2A3_expr[[1]] %>%
# filter(tissueDescription1 %in% c("Glioma, malignant, High grade", "Glioma, malignant, Low grade", "Glioma, malignant, NOS"))
#
# for (i in 1:nrow(SLC2A3_glioma)) {
# download.file(SLC2A3_glioma$imageUrl[i],
# destfile = paste0("img/", SLC2A3_ab$id[1], "_",
# SLC2A3_glioma$patientId[i], "_",
# SLC2A3_glioma$tissueDescription1[i], "_",
# SLC2A3_glioma$staining[i],
# ".jpg"),
# mode = "wb")
# }
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