updated publications

_quarto.yml

@@ -3,13 +3,16 @@ project:
 
 website:
   title: "LNSC Browser"
+
   navbar:
     search: true
     left:
-      - projects.qmd
+      - text: Projects
+        file: projects.qmd
       - atlases.qmd
       - pubs.qmd
       - investigators.qmd
+
   search:
     location: navbar
     type: textbox
@@ -19,6 +22,7 @@ format:
     theme: darkly
     css: styles.css
     toc: true
+    toc-depth: 1
 
 editor: visual
 

atlases/2021-walsh/index.qmd

@@ -1,7 +1,9 @@
 ---
 title: Molecular tracking devices quantify antigen distribution and archiving in the murine lymph node
-image: 2021-walsh.jpg
-categories: [project-2, core-c, core-d]
+image: /images/2021-walsh.jpg
+date: 'April 12, 2021'
+
+categories: [project-2, core-b, core-c, core-d]
 about:
   id: about
   template: jolla

authors.yml

@@ -1,10 +1,3 @@
-Ryan Sheridan:
-  suffix: PhD
-  links:
-    publications: https://orcid.org/0000-0003-4012-3147
-    website: https://github.com/sheridar
-    email: mailto:[email protected]
-  project: core-d
 Thomas Morrison:
   suffix: PhD
   links:
@@ -40,7 +33,9 @@ Beth Tamburini:
   links:
     website: https://medschool.cuanschutz.edu/gastroenterology/research/research-laboratories/beth-jiron-tamburini-lab
     email: mailto:[email protected]
-  project: project-2
+  project:
+  - project-2
+  - core-b
   bio: The overarching goal of my research program is to understand how the lymphatic
     stroma recognize and react to stimuli within the lymph to guide the immune response.
     My initial studies of lymphatic stroma were focused on understanding the mechanisms
@@ -59,6 +54,7 @@ Beth Tamburini:
     in developing this research program. This collaborative research program as proven
     to be well suited for the training and success of the graduate students and post-docs
     in my laboratory.
+  image: /home/rmsheridan/Projects/lnsc-cell-browser/images/beth-tamburini.jpg
 Jenna Guthmiller:
   suffix: PhD
   links:
@@ -88,6 +84,7 @@ Jenna Guthmiller:
     conserved, albeit non-protective antigens. Together, these studies highlight the
     importance of understanding how preexisting antibodies influence the generation
     of broadly protective immunity.
+  image: /home/rmsheridan/Projects/lnsc-cell-browser/images/jenna-guthmiller.jpeg
 Jay Hesselberth:
   suffix: PhD
   links:
@@ -110,6 +107,13 @@ Jay Hesselberth:
     et al.). More recently, we have applied nanopore RNA sequencing to characterize
     the landscape of RNA repair events in budding yeast.
   image: /home/rmsheridan/Projects/lnsc-cell-browser/images/jay-hesselberth.png
+Ryan Sheridan:
+  suffix: PhD
+  links:
+    publications: https://orcid.org/0000-0003-4012-3147
+    website: https://github.com/sheridar
+    email: mailto:[email protected]
+  project: core-d
 Jennifer Matsuda:
   suffix: PhD
   links:
@@ -161,3 +165,22 @@ Nicholas May: []
 Heather Hickman: []
 Tadg Forward: []
 Aspen Martin: []
+Susan Elmore: []
+Tonya Colpitts: []
+Austin Gillen: []
+Michael Kriss: []
+Kent Riemondy: []
+Ronald Schuyler: []
+Hugo Rosen: []
+Madison Kraus: []
+Ira Fleming: []
+Aspen Uecker-Martin: []
+Ju-Sim Kim: []
+Lin Liu: []
+Sashi Kant: []
+David Orlicky: []
+Siva Uppalapati: []
+Alyssa Margolis: []
+Michael McClelland: []
+Jessica Jones-Carson: []
+Andres Vazquez-Torres: []

funs.R

@@ -82,12 +82,20 @@
 
   # Set publication key based on first author and key
   # this is used to create page directories
-  yr <- html %>%
+  date <- html %>%
     html_element("span.cit") %>%
     html_text2() %>%
-    str_extract("^[0-9]{4}(?= )")
+    str_extract("^[^;]+")
 
-  if (is.na(yr)) cli_abort("Error extracting year from pubmed link")
+  if (is.na(date)) cli_abort("Error extracting date from pubmed link")
+
+  date <- date %>%
+    as.Date(format = "%Y %b %d")
+
+  yr <- year(date)
+
+  date <- date %>%
+    format("%B %d, %Y")
 
   athr1 <- athrs[1] %>%
     str_extract("[^ ]+$") %>%
@@ -99,6 +107,7 @@
   res <- list(
     key      = key,
     title    = ttl,
+    date     = date,
     year     = yr,
     authors  = athrs,
     abstract = abst

index.qmd

@@ -14,31 +14,51 @@ library(here)
 
 source(here("funs.R"))
 
+# Read yamls
 proj_yml <- read_yaml(here("projects.yml"))
 pub_yml  <- read_yaml(here("pubs.yml"))
 athr_yml <- read_yaml(here("authors.yml"))
 lnk_cls  <- "{.link-box}"
 
+# Create links for each project
 links <- .create_project_links(proj_yml, athr_yml, pub_yml, lnk_cls)
 
+# Split into projects and cores
+# maintain order provided in yaml
+proj_type <- proj_yml %>%
+  names() %>%
+  str_extract("^[^-]+") %>%
+  str_to_title() %>%
+  str_c("s") %>%
+  factor(levels = unique(.))
+
+proj_yml <- proj_yml %>%
+  split(proj_type)
+
+# Create section text
 text <- proj_yml %>%
   imap(~ {
-    ttl_lnk <- .x$title %>%
-      str_to_lower() %>%
-      str_replace_all("( |, )", "-") %>%
-      str_c("[", .x$title, "](projects.qmd#", ., "){.bold-link}")
+    ttl <- str_c("## ", .y, "\n\n")
     
-    str_c(
-      "* ", ttl_lnk, "  \n",
-      links[[.y]],   "  \n",
-      .x$short,      "\n\n"
-    )
+    .x %>%
+      imap(~ {
+        ttl_lnk <- .x$title %>%
+          str_to_lower() %>%
+          str_replace_all("( |, )", "-") %>%
+          str_c("[", .x$title, "](projects.qmd#", ., "){.bold-link}")
+        
+        str_c(
+          "* ", ttl_lnk, "  \n",
+          links[[.y]],   "  \n",
+          .x$short,      "\n\n"
+        )
+      }) %>%
+      str_c(collapse = "") %>%
+      str_c(ttl, .)
   }) %>%
   str_c(collapse = "")
 ```
 
-The theme uniting our program is that lymph node stromal cells (LNSC)s are an understudied and untapped source of immunomodulatory control. LNSCs are comprised of diverse populations of fibroblasts and endothelial cells. LNSCs coordinate lymphocyte entry into the lymph node (LN), facilitate lymphocyte trafficking into distinct LN niches, regulate lymphocyte survival, and promote LN expansion. Our overall hypothesis is that viral and antigen acquisition by LNSCs shapes immunity by programming pathogen and vaccine specific responses, and that LNSCs can be manipulated by pathogens and vaccines to guide immune outcomes.
-
-## Projects
+Lymph node stromal cells (LNSC)s are an understudied and untapped source of immunomodulatory control. LNSCs are comprised of diverse populations of fibroblasts and endothelial cells. LNSCs coordinate lymphocyte entry into the lymph node (LN), facilitate lymphocyte trafficking into distinct LN niches, regulate lymphocyte survival, and promote LN expansion. The goal of this program is to investigate how viral and antigen acquisition by LNSCs shape immunity and how LNSCs can be manipulated by pathogens and vaccines to guide immune outcomes.
 
 `r text`

investigators.qmd

@@ -34,7 +34,7 @@ text <- athr_yml %>%
     if (!is.null(.x$suffix)) sfx <- str_c(", ", .x$suffix)
     
     res <- str_c(
-      "## ", .y, sfx, "\n\n",
+      "<h2>", .y, sfx, "</h2>\n\n",
       lnks,           "\n\n",
       .x$bio,         "\n\n"
     )
@@ -45,14 +45,10 @@ text <- athr_yml %>%
       
       html_head <- str_c(
         "<div class='investigator-image'>\n",
-        "  <img src='", img, "'>\n",
-        "  <p>\n"
+        "  <img src='", img, "'>\n"
       )
       
-      html_foot <- str_c(
-        "  </p>\n",
-        "</div>"
-      )
+      html_foot <- "</div>"
       
       res <- str_c(
         html_head, res,

pre-build.R

@@ -1,7 +1,7 @@
 # Run this script prior to building site to:
 # * Scrape publication information and generate publication pages
 # * Update authors.yml based on publication information
-# * Serach for author images and update authors.yml
+# * Search for author images and update authors.yml
 
 library(yaml)
 library(tidyverse)
@@ -45,8 +45,13 @@ link_info <- list(
 # Template to write index.qmd
 index_qmd <- "---\ntitle: {ttl}\n"
 
+# Check for duplicated publications
+dup_pubs <- pub_yml %>%
+  map_chr(pluck, "pubmed") %>%
+  duplicated()
+
 # Create index.qmd for each pub entry
-pub_yml_new <- pub_yml %>%
+pub_yml_new <- pub_yml[!dup_pubs] %>%
   imap(~ {
     pub_info <- .x
 
@@ -55,7 +60,7 @@ pub_yml_new <- pub_yml %>%
 
     # Scrape missing info from pubmed
     pub_attrs <- c(
-      "key", "title", "year",
+      "key", "title", "date", "year",
       "authors", "abstract", "image"
     )
 
@@ -91,7 +96,7 @@ pub_yml_new <- pub_yml %>%
 
       if (length(img) > 1) img <- img[[1]]
 
-    } else if (file.exists(pub_info$image)) {
+    } else if (file.exists(str_remove(pub_info$image, "^/"))) {
       img <- pub_info$image
 
     } else {
@@ -102,20 +107,18 @@ pub_yml_new <- pub_yml %>%
       download.file(img_dwnld, img)
     }
 
-    img_nm  <- basename(img)
-    img_lnk <- here(pub, img_nm)
+    img <- str_remove(img, here())  # image path should be relative to site
 
     # Conditionally add image field to index.qmd
-    if (!is_empty(img_lnk)) {
-      index_qmd <- str_c(index_qmd, "image: {img_nm}\n")
-
-      if (!file.exists(img_lnk)) file.link(img, img_lnk)
+    if (!is_empty(img)) {
+      index_qmd <- str_c(index_qmd, "image: {img}\n")
 
-      pub_info$image <- img_lnk
+      pub_info$image <- img
     }
 
     index_qmd <- str_c(
       index_qmd,
+      "date: '{pub_info$date}'\n\n",
       "categories: [{cats_str}]\n",
       "about:\n",
       "  id: about\n",
@@ -198,7 +201,7 @@ pub_yml_new <- pub_yml %>%
 # Write updated pubs.yml
 # this will have info scraped from pubmed
 if (!identical(pub_yml, pub_yml_new)) {
-  pub_yml %>%
+  pub_yml_new %>%
     write_yaml(here("pubs.yml"))
 }
 
@@ -230,6 +233,83 @@ athr_yml_new <- athr_yml %>%
   })
 
 if (!identical(athr_yml, athr_yml_new)) {
-  athr_yml %>%
+  athr_yml_new %>%
     write_yaml(here("authors.yml"))
 }
+
+
+# TIMELINE ----
+
+# Filter for authors to label
+lab_athr <- athr_yml_new %>%
+  keep(~ !is.null(.x$project)) %>%
+  names()
+
+tl_dat <- pub_yml_new %>%
+  map_dfr(~ {
+    athrs <- .x$authors
+    athrs <- athrs[athrs %in% lab_athr]
+    athrs <- str_extract(athrs, "[^ ]+$")
+
+    tibble(
+      key     = .x$key,
+      date    = as.Date(str_c(.x$year, "-01-01")),
+      authors = str_c(athrs, collapse = ", "),
+      pmid    = str_extract(.x$pubmed, "[0-9]+(/|)$")
+    )
+  })
+
+# Format publication data
+tl_dat <- tl_dat %>%
+  mutate(
+    authors = str_wrap(authors, width = 10),
+    pmid    = str_remove(pmid, "/$"),
+    pmid    = str_c("PMID ", pmid),
+    lab     = str_c(authors, "\n", pmid),
+    year    = as.character(year(date))
+  ) %>%
+  group_by(date, year) %>%
+  summarize(lab = str_c(lab, collapse = "\n\n"), .groups = "drop")
+
+# Create publication timeline
+tl <- tl_dat %>%
+  ggplot(aes(date, 0)) +
+  geom_line(
+    linewidth = 3
+  ) +
+  geom_point(
+    # shape = 25,
+    size  = 6,
+    fill  = "black"
+  ) +
+  geom_text(
+    aes(y = 0.35, label = year),
+    size     = 24 / .pt,
+    color    = "white"
+    # fontface = "bold"
+  ) +
+  geom_text(
+    aes(y = -0.25, label = lab),
+    hjust    = 0,
+    vjust    = 1,
+    size     = 12 / .pt,
+    color    = "white"
+    # fontface = "italic"
+  ) +
+  coord_cartesian(
+    xlim = c(min(tl_dat$date), max(tl_dat$date) + years(1)),
+    ylim = c(-3, 0.6)
+  ) +
+  theme_void() +
+  theme(
+    plot.background = element_rect(fill = "#303030", color = "#303030")
+  )
+
+ggsave(
+  tl,
+  filename = here(img_dir, "pub_tl.png"),
+  width    = 18,
+  height   = 5,
+  dpi      = 300,
+  device   = "png"
+)