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Introduce teal_data class #75

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Introduce teal_data class #75

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83713f6
exploratory
gogonzo Oct 4, 2023
b34e0ed
early-dev
gogonzo Oct 4, 2023
663c156
efficacy and obtain teal.data:::default_cdisc_keys
gogonzo Oct 4, 2023
f0d2dc3
longitudinal
gogonzo Oct 4, 2023
794250b
patient profile
gogonzo Oct 4, 2023
e7ef8eb
RNA-seq
gogonzo Oct 4, 2023
e3ba0d9
safety
gogonzo Oct 4, 2023
698a4e8
Merge branch 'main' into teal_data@main
gogonzo Oct 19, 2023
468f66a
fix cdisc_data and join_keys calls
gogonzo Oct 25, 2023
af53bf6
remove thrash
gogonzo Oct 25, 2023
67a9a7a
push code into teal_data with qenv mechanism (#90)
chlebowa Oct 27, 2023
054fd51
remove load_all
gogonzo Oct 27, 2023
7946d5d
libraries
gogonzo Oct 31, 2023
8409985
logo to the top
gogonzo Oct 31, 2023
aeeec7d
tidyup options call
gogonzo Oct 31, 2023
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26 changes: 10 additions & 16 deletions RNA-seq/app.R
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Original file line number Diff line number Diff line change
Expand Up @@ -7,25 +7,19 @@ options(shiny.useragg = FALSE)

nest_logo <- "https://raw.githubusercontent.com/insightsengineering/hex-stickers/main/PNG/nest.png"

# code>
mae <- hermes::multi_assay_experiment
mae_data <- dataset("MAE", mae)

adtte <- scda::synthetic_cdisc_data("rcd_2022_06_27")$adtte %>%
ADTTE <- scda::synthetic_cdisc_data("rcd_2022_06_27")$adtte %>%
dplyr::mutate(is_event = CNSR == 0)

data <- teal_data(
dataset(
"ADTTE",
adtte,
code = 'adtte <- scda::synthetic_cdisc_data("rcd_2022_06_27")$adtte %>%
dplyr::mutate(is_event = CNSR == 0)'
),
dataset("MAE", mae)
)
MAE <- hermes::multi_assay_experiment

app <- init(
data = data,
data = teal_data(
ADTTE = ADTTE, MAE = MAE,
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code = quote({
ADTTE <- scda::synthetic_cdisc_data("rcd_2022_06_27")$adtte %>%
dplyr::mutate(is_event = CNSR == 0)
MAE <- hermes::multi_assay_experiment
})
),
modules = modules(
tm_front_page(
label = "App Info",
Expand Down
324 changes: 154 additions & 170 deletions early-dev/app.R
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Original file line number Diff line number Diff line change
Expand Up @@ -12,6 +12,7 @@ options(shiny.useragg = FALSE)

nest_logo <- "https://raw.githubusercontent.com/insightsengineering/hex-stickers/main/PNG/nest.png"


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Usually there is only one blank line between nest_logo and everything that comes after

Suggested change

ADSL <- synthetic_cdisc_data("latest")$adsl

# derive ADSL treatment duration
Expand Down Expand Up @@ -187,181 +188,164 @@ fact_vars_asl <- names(Filter(isTRUE, sapply(ADSL, is.factor)))
date_vars_asl <- names(ADSL)[vapply(ADSL, function(x) inherits(x, c("Date", "POSIXct", "POSIXlt")), logical(1))]
demog_vars_asl <- names(ADSL)[!(names(ADSL) %in% c("USUBJID", "STUDYID", date_vars_asl))]

# create cdisc_dataset objects to pass into app

adsl <- cdisc_dataset(
dataname = "ADSL",
x = ADSL,
code = 'ADSL <- synthetic_cdisc_data("latest")$adsl
adsl_labels <- teal.data::col_labels(ADSL, fill = FALSE)
ADSL <- ADSL %>%
mutate(
TRTDURD = as.numeric(as.Date(TRTEDTM) - as.Date(TRTSDTM)) + 1,
DTHFL = ifelse(!is.na(DTHDT), "Y", NA),
EOSSTT = factor(EOSSTT, levels = c("COMPLETED", "ONGOING", "DISCONTINUED"))
) %>%
teal.data::col_relabel(
TRTDURD = "Treatment Duration in Days",
DTHFL = "Death Flag",
DCSREAS = "Reason for Study Discontinuation",
EOSSTT = "End of Study Status"
) %>%
droplevels()
teal.data::col_labels(ADSL)[c(names(adsl_labels))] <- adsl_labels'
)

adae <- cdisc_dataset(
dataname = "ADAE",
x = ADAE,
keys = c("STUDYID", "USUBJID", "AETERM", "AESEQ"),
code = 'ADAE <- synthetic_cdisc_data("latest")$adae
# derive common flags for AEs
ADAE <- ADAE %>%
mutate_at(
c("AESOC", "AEBODSYS", "AEHLT", "AEDECOD", "AETERM", "AELLT"),
as.character
) %>%
mutate(
RELFL = ifelse(AEREL == "Y", "Y", "N"),
CTC35FL = ifelse(AETOXGR %in% c("3", "4", "5"), "Y", "N"),
SERFL = ifelse(AESER == "Y", "Y", "N"),
RELSERFL = ifelse(AEREL == "Y" & AESER == "Y", "Y", "N"),
AEREL1 = (AEREL == "Y" & ACTARM == "A: Drug X"),
AEREL2 = (AEREL == "Y" & ACTARM == "B: Placebo"),
ASTDT = as.Date(ASTDTM),
AENDT = as.Date(AENDTM)
) %>%
teal.data::col_relabel(
RELFL = "Related AE",
CTC35FL = "Grade >=3 AE",
SERFL = "Serious AE",
RELSERFL = "Related Serious AE",
AEREL1 = "AE related to A: Drug X",
AEREL2 = "AE related to B: Placebo",
ASTDT = "Analysis Start Date",
AENDT = "Analysis End Date",
AESOC = "Primary System Organ Class",
AEBODSYS = "Body System or Organ Class",
AEHLT = "High Level Term",
AEDECOD = "Dictionary-Derived Term",
AETERM = "Reported Term for the Adverse Event",
AELLT = "Lowest Level Term"
)',
vars = list(ADSL = adsl)
)

adcm <- cdisc_dataset(
dataname = "ADCM",
x = ADCM,
code = 'ADCM <- synthetic_cdisc_data("latest")$adcm
ADCM <- ADCM %>%
mutate(
ASTDT = as.Date(ASTDTM),
AENDT = as.Date(AENDTM)
) %>%
teal.data::col_relabel(
ASTDT = "Analysis Start Date",
AENDT = "Analysis End Date"
)',
vars = list(ADSL = adsl)
)

adex <- cdisc_dataset(
dataname = "ADEX",
x = ADEX,
code = 'ADEX <- synthetic_cdisc_data("latest")$adex
ADEX <- ADEX %>%
mutate(
ASTDT = as.Date(ASTDTM),
AENDT = as.Date(AENDTM)
) %>%
teal.data::col_relabel(
ASTDT = "Analysis Start Date",
AENDT = "Analysis End Date"
)',
vars = list(ADSL = adsl)
)

adtr <- cdisc_dataset(
dataname = "ADTR",
x = ADTR,
keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
code = 'ADTR <- synthetic_cdisc_data("latest")$adtr
adtr_labels <- teal.data::col_labels(ADTR, fill = FALSE)
ADTR <- ADTR %>%
mutate(
PCHG = ifelse(AVISIT == "BASELINE", 0, PCHG),
CHG = ifelse(AVISIT == "BASELINE", 0, CHG),
AVAL = ifelse(AVISIT == "BASELINE", BASE, AVAL),
AVALC = ifelse(AVISIT == "BASELINE", as.character(BASE), AVALC)
) %>%
dplyr::filter(AVISIT != "SCREENING")
teal.data::col_labels(ADTR) <- adtr_labels',
var = list(ADSL = adsl)
)

adtrwf <- cdisc_dataset(
dataname = "ADTRWF",
x = ADTRWF,
keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
code = 'ADTRWF <- ADTR %>%
dplyr::filter(AVISIT != "BASELINE")
teal.data::col_labels(ADTRWF) <- teal.data::col_labels(ADTR, fill = FALSE)',
vars = list(ADTR = adtr)
)

adrs <- cdisc_dataset(
dataname = "ADRS",
x = ADRS,
code = 'ADRS <- synthetic_cdisc_data("latest")$adrs
adrs_labels <- teal.data::col_labels(ADRS, fill = FALSE)
ADRS <- ADRS %>%
filter(PARAMCD %in% c("BESRSPI", "INVET")) %>%
mutate(ADT = as.Date(ADTM)) %>%
droplevels()
teal.data::col_labels(ADRS) <- c(adrs_labels, "Analysis Date")',
vars = list(ADSL = adsl)
)

adrsswim <- cdisc_dataset(
dataname = "ADRSSWIM",
x = ADRSSWIM,
keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
code = 'ADRSSWIM <- synthetic_cdisc_data("latest")$adrs %>%
dplyr::filter(PARAMCD == "OVRINV") %>%
arrange(USUBJID)',
vars = list(ADSL = adsl)
)

adlb <- cdisc_dataset(
dataname = "ADLB",
x = ADLB,
code = 'ADLB <- synthetic_cdisc_data("latest")$adlb
ADLB <- ADLB %>%
mutate(
ADT = as.Date(ADTM),
LBSTRESN = as.numeric(LBSTRESC)
) %>%
teal.data::col_relabel(
ADT = "Analysis Date",
LBSTRESN = "Numeric Result/Finding in Standard Units"
)',
vars = list(ADSL = adsl)
keys_list <- teal.data:::default_cdisc_keys
jk <- teal.data::join_keys(
teal.data::join_key("ADSL", "ADSL", keys = get_cdisc_keys("ADSL")),
teal.data::join_key("ADAE", "ADAE", keys = get_cdisc_keys("ADAE")),
teal.data::join_key("ADCM", "ADCM", keys = get_cdisc_keys("ADCM")),
teal.data::join_key("ADEX", "ADEX", keys = get_cdisc_keys("ADEX")),
teal.data::join_key("ADRS", "ADRS", keys = get_cdisc_keys("ADRS")),
teal.data::join_key("ADLB", "ADLB", keys = get_cdisc_keys("ADLB")),
teal.data::join_key("ADTR", "ADTR", keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")),
teal.data::join_key("ADTRWF", "ADTRWF", keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")),
teal.data::join_key("ADRSSWIM", "ADRSSWIM", keys = get_cdisc_keys("ADRS")),
teal.data::join_key("ADAE", keys_list[["ADAE"]]$parent, keys = keys_list[["ADAE"]]$foreign),
teal.data::join_key("ADCM", keys_list[["ADCM"]]$parent, keys = keys_list[["ADCM"]]$foreign),
teal.data::join_key("ADEX", keys_list[["ADEX"]]$parent, keys = keys_list[["ADEX"]]$foreign),
teal.data::join_key("ADRS", keys_list[["ADRS"]]$parent, keys = keys_list[["ADRS"]]$foreign),
teal.data::join_key("ADLB", keys_list[["ADLB"]]$parent, keys = keys_list[["ADLB"]]$foreign),
teal.data::join_key("ADTR", "ADSL", keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")),
teal.data::join_key("ADTRWF", "ADSL", keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")),
teal.data::join_key("ADRSSWIM", keys_list[["ADRS"]]$parent, keys = keys_list[["ADRS"]]$foreign)
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)

## Setup App
app <- teal::init(
data = cdisc_data(
adsl,
adae,
adex,
adcm,
adtr,
adtrwf,
adrs,
adrsswim,
adlb,
check = TRUE
ADSL = ADSL,
ADAE = ADAE,
ADCM = ADCM,
ADEX = ADEX,
ADTR = ADTR,
ADTRWF = ADTRWF,
ADRS = ADRS,
ADRSSWIM = ADRSSWIM,
ADLB = ADLB,
code = quote({
ADSL <- synthetic_cdisc_data("latest")$adsl

# derive ADSL treatment duration
adsl_labels <- teal.data::col_labels(ADSL, fill = FALSE)
ADSL <- ADSL %>%
mutate(
TRTDURD = as.numeric(as.Date(TRTEDTM) - as.Date(TRTSDTM)) + 1,
DTHFL = ifelse(!is.na(DTHDT), "Y", NA),
EOSSTT = factor(EOSSTT, levels = c("COMPLETED", "ONGOING", "DISCONTINUED"))
) %>%
teal.data::col_relabel(
TRTDURD = "Treatment Duration in Days",
DTHFL = "Death Flag",
DCSREAS = "Reason for Study Discontinuation",
EOSSTT = "End of Study Status"
) %>%
droplevels()
teal.data::col_labels(ADSL)[c(names(adsl_labels))] <- adsl_labels

ADAE <- synthetic_cdisc_data("latest")$adae

# derive common flags for AEs
adae_labels <- teal.data::col_labels(ADAE, fill = FALSE)
ADAE <- ADAE %>%
mutate_at(c("AESOC", "AEBODSYS", "AEHLT", "AEDECOD", "AETERM", "AELLT"), as.character) %>%
mutate(
RELFL = ifelse(AEREL == "Y", "Y", "N"),
CTC35FL = ifelse(AETOXGR %in% c("3", "4", "5"), "Y", "N"),
SERFL = ifelse(AESER == "Y", "Y", "N"),
RELSERFL = ifelse(AEREL == "Y" & AESER == "Y", "Y", "N"),
AEREL1 = (AEREL == "Y" & ACTARM == "A: Drug X"),
AEREL2 = (AEREL == "Y" & ACTARM == "B: Placebo"),
ASTDT = as.Date(ASTDTM),
AENDT = as.Date(AENDTM)
) %>%
teal.data::col_relabel(
RELFL = "Related AE",
CTC35FL = "Grade >=3 AE",
SERFL = "Serious AE",
RELSERFL = "Related Serious AE",
AEREL1 = "AE related to A: Drug X",
AEREL2 = "AE related to B: Placebo",
ASTDT = "Analysis Start Date",
AENDT = "Analysis End Date",
AESOC = "Primary System Organ Class",
AEBODSYS = "Body System or Organ Class",
AEHLT = "High Level Term",
AEDECOD = "Dictionary-Derived Term",
AETERM = "Reported Term for the Adverse Event",
AELLT = "Lowest Level Term"
)

ADCM <- synthetic_cdisc_data("latest")$adcm

# process ADCM
ADCM <- ADCM %>%
mutate(
ASTDT = as.Date(ASTDTM),
AENDT = as.Date(AENDTM)
) %>%
teal.data::col_relabel(
ASTDT = "Analysis Start Date",
AENDT = "Analysis End Date"
)

ADEX <- synthetic_cdisc_data("latest")$adex

# process ADEX
ADEX <- ADEX %>%
mutate(
ASTDT = as.Date(ASTDTM),
AENDT = as.Date(AENDTM)
) %>%
teal.data::col_relabel(
ASTDT = "Analysis Start Date",
AENDT = "Analysis End Date"
)

ADTR <- synthetic_cdisc_data("latest")$adtr

# process ADTR
adtr_labels <- teal.data::col_labels(ADTR, fill = FALSE)
ADTR <- ADTR %>%
mutate(
PCHG = ifelse(AVISIT == "BASELINE", 0, PCHG),
CHG = ifelse(AVISIT == "BASELINE", 0, CHG),
AVAL = ifelse(AVISIT == "BASELINE", BASE, AVAL),
AVALC = ifelse(AVISIT == "BASELINE", as.character(BASE), AVALC)
) %>%
filter(AVISIT != "SCREENING")
teal.data::col_labels(ADTR) <- adtr_labels

ADTRWF <- ADTR %>%
filter(AVISIT != "BASELINE")
teal.data::col_labels(ADTRWF) <- teal.data::col_labels(ADTR, fill = FALSE)


# process ADRS
ADRSSWIM <- synthetic_cdisc_data("latest")$adrs %>%
filter(PARAMCD == "OVRINV") %>%
arrange(USUBJID)

ADRS <- synthetic_cdisc_data("latest")$adrs
adrs_labels <- teal.data::col_labels(ADRS, fill = FALSE)
ADRS <- ADRS %>%
filter(PARAMCD %in% c("BESRSPI", "INVET")) %>%
mutate(ADT = as.Date(ADTM)) %>%
droplevels()
teal.data::col_labels(ADRS) <- c(adrs_labels, "Analysis Date")

ADLB <- synthetic_cdisc_data("latest")$adlb

# process ADLB
ADLB <- ADLB %>%
mutate(
ADT = as.Date(ADTM),
LBSTRESN = as.numeric(LBSTRESC)
) %>%
teal.data::col_relabel(
ADT = "Analysis Date",
LBSTRESN = "Numeric Result/Finding in Standard Units"
)
}),
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join_keys = jk
),
filter = teal_slices(
count_type = "all",
Expand Down
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