# 99. Code for figures from HPAanalyze paper

Anh N. Tran1*

1DataGrata LLC

*trannhatanh89@gmail.com

#### 6/18/2019

    library(BiocStyle)
    library(HPAanalyze)
    library(dplyr)
    library(ggplot2)

    data <- hpaDownload(downloadList = "histology",
                        version = "v18")

# 1 Figure 2

    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")

# 2 Figure 3

    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)

# 3 Figure 4

    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)

# 4 Figure 5

    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")
    }

# 5 Copyright

Anh Tran, 2018-2023

Please cite: Tran, A.N., Dussaq, A.M., Kennell, T. et al. HPAanalyze: an R package that facilitates the retrieval and analysis of the Human Protein Atlas data. BMC Bioinformatics 20, 463 (2019) https://doi.org/10.1186/s12859-019-3059-z