In the 2022 tsv files here (that are pointed to on the prediction page) we are missing titer data for subject_id 98 and 113.
This is for a female wP and male aP respectively. What is weird is that you have subject_id 98 in the TSV Submission template file and not 113.
Accessing the full datasets from the API endpoints again shows subject_id 113 is missing but 98 is there in the titer data.
From the full datasets (2020_dataset, 2021_dataset and 2022_dataset) we are missing subject_id “2” “8” “82” “87” “88” “113”
library(jsonlite)
library(dplyr)
subject <- read_json("https://www.cmi-pb.org/api/subject", simplifyVector = TRUE)
specimen <- read_json("https://www.cmi-pb.org/api/specimen", simplifyVector = TRUE)
titer <- read_json("https://www.cmi-pb.org/api/plasma_ab_titer", simplifyVector = TRUE)
# Join these tables to annotate which specimen
# and subject each titer measurement relates to:
meta <- inner_join(specimen, subject)
abdata <- inner_join(titer, meta)
# Check on which subject_ids are misssing:
ori.subject.ids <- names(table(subject$subject_id))
got.subject.ids <- names(table(abdata$subject_id))
ori.subject.ids[ !ori.subject.ids %in% got.subject.ids]
## [1] "2" "8" "82" "87" "88" "113"
Thanks!