PubMedViz.Rmd

---
title: "PubMedVizR"
author: "Dan Kerchner"
date: "2023-03-31"
output: pdf_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

This script requires in input file called `search_params.csv`, which has the following columns:  
  
`mainterm` (e.g. microbiom*)  
`subterm` (e.g. 16S)  
`startyear` (e.g. 2000)  
`endyear` (e.g. 2022)  

```{r}
library(rentrez)
library(ggplot2)

terms_df <- read.csv('search_params.csv')

# Returns paper count for a single year matching term AND subterm
search_term_subterm_year <- function(term, subterm, year){
  query <- paste(term, "AND", subterm, "AND (", year, "[PDAT])")
  entrez_search(db="pubmed", term=query, retmax=0)$count
}

df <- data.frame()
for(i in 1:nrow(terms_df)) {
    row <- terms_df[i,]
  
    for (year in row$start_year:row$end_year) {
        papers_count <- search_term_subterm_year(term=row$term, subterm=row$subterm, year = year)
        result_i_df <- data.frame(term = row$term, subterm = row$subterm, year = year, count = papers_count)
        df <- rbind(df, result_i_df)
    }
}

ggplot(data = df) +
  geom_area(aes(x = year, y = count, fill = subterm), alpha = 0.5) +
  theme(axis.text.x = element_text(angle = 90)) +
  facet_wrap(~ term, scales = c("free"), ncol = 2) # or just free_y
```