Nothing
inst/doc/Data_processing-Archive_tcpl_v2.R
In tcpl: ToxCast Data Analysis Pipeline
## ----eval = TRUE, echo = FALSE, message = FALSE-------------------------------
library(htmlTable)
library(tcpl)
library(data.table)
## ----eval = TRUE, echo = FALSE, message = FALSE, results = "hide"-------------
## This chunk copies the tcplLite local directory to the temp directory used in installation
## to comply with CRAN policies on not writing to the installation directory
tmpdir <- tempdir()
#dbfile <- file.path(system.file(package = "tcpl"), "csv")
#file.copy(from = dbfile, tmpdir, recursive = TRUE)
dbfile_temp <- file.path(tmpdir, "csv")
dir.create(dbfile_temp, showWarnings = F)
tcplConf(db = dbfile_temp, drvr = 'tcplLite')
## ----eval = TRUE, echo = FALSE, message = FALSE-------------------------------
tcplRegister(what='spid', flds = list(spid=c("Tox21_303655", "Tox21_110011", "Tox21_400081", "DMSO", "Tox21_400037"),
chid=c("22364", "23463", "24102", "21735", "20283"),
tested_conc_unit=c('uM', 'uM', 'uM', 'uM', 'uM')
) )
tcplRegister(what='chid', flds=list(chid = c("22364", "23463" , "24102", "21735","20283"),
casn = c("521-18-6", "150-30-1", "22224-92-6", "67-68-5", "95-83-0"),
chnm = c("5alpha-Dihydrotestosterone","Phenylalanine","Fenamiphos",
"Dimethyl sulfoxide","4-Chloro-1,2-diaminobenzene"),
dsstox_substance_id = c("DTXSID9022364", "DTXSID9023463", "DTXSID3024102", "DTXSID2021735", "DTXSID5020283"),
code = c("C521186","C150301","C22224926", "C67685","C95830")))
## ----eval = TRUE, message = FALSE---------------------------------------------
## Add a new assay source, call it CTox,
## that produced the data
tcplRegister(what = "asid", flds = list(asid = 1,
asnm = "CTox"))
## ----eval = TRUE--------------------------------------------------------------
tcplLoadAsid()
## ----eval = TRUE, message = FALSE---------------------------------------------
tcplRegister(what = "aid",
flds = list(asid = 1,
anm = "TOX21_ERa_BLA_Agonist",
assay_footprint = "1536 well"))
## ----eval = TRUE, message = FALSE---------------------------------------------
tcplRegister(what = "acid",
flds = list(aid = 1,
acnm = "TOX21_ERa_BLA_Agonist_ratio"))
tcplRegister(what = "aeid",
flds = list(acid = c(1, 1),
aenm = c("TOX21_ERa_BLA_Agonist_ratio_gain",
"TOX21_ERa_BLA_Agonist_ratio_loss"),
normalized_data_type =
rep("percent_activity", 1),
export_ready = c(1, 1),
burst_assay = c(0, 0),
fit_all = c(0, 0)))
## ----eval = TRUE--------------------------------------------------------------
data(chdat, package = "tcpl")
setDT(chdat)
head(chdat)
## ----eval = TRUE, message = FALSE---------------------------------------------
## Register the unique chemicals
cmap <- tcplLoadChem() # Chemicals already registered
chdat.register <- chdat[!(chdat$code %in% cmap$code)] # Chemicals in chdat that are not registered yet
tcplRegister(what = "chid",
flds = chdat.register[,
unique(.SD),
.SDcols = c("casn", "chnm", "dsstox_substance_id", "code", "chid")])
## ----eval = TRUE, message = FALSE---------------------------------------------
tcplRegister(what = "spid",
flds = merge(chdat[ , list(spid, casn)],
chdat.register[ , list(casn, chid)],
by = "casn")[ , list(spid, chid)])
## ----eval = FALSE-------------------------------------------------------------
# grp1 <- cmap[chid %% 2 == 0, unique(chid)]
# grp2 <- cmap[chid %% 2 == 1, unique(chid)]
# tcplRegister(what = "clib",
# flds = list(clib = "group_1", chid = grp1))
## ----eval = FALSE-------------------------------------------------------------
# tcplRegister(what = "clib",
# flds = list(clib = "group_2", chid = grp2))
## ----eval = FALSE-------------------------------------------------------------
# tcplRegister(what = "clib",
# flds = list(clib = "other", chid = 1:2))
## ----eval = FALSE-------------------------------------------------------------
# tcplLoadClib(field = "chid", val = 1:2)
## ----eval = TRUE--------------------------------------------------------------
data(mcdat, package = 'tcpl')
setDT(mcdat)
## ----eval = TRUE, message = FALSE---------------------------------------------
tcplRegister(what = "acsn",
flds = list(acid = 1, acsn = "TCPL-MC-Demo"))
## ----eval = TRUE, message = FALSE---------------------------------------------
## Cannot process a concentration value of 0; use .01 as a dummy value
mcdat$conc[mcdat$conc == 0] <- .01
tcplWriteLvl0(dat = mcdat, type = "mc")
## ----eval = TRUE--------------------------------------------------------------
tcplLoadData(lvl = 0, fld = "acid", val = 1, type = "mc")
## ----warning = FALSE, echo = FALSE--------------------------------------------
Type <- c('SC', 'SC', 'MC', 'MC', 'MC', 'MC', 'MC', 'MC')
Level <- c('Lvl1', 'Lvl2', 'Lvl1', 'Lvl2', 'Lvl3', 'Lvl4', 'Lvl5', 'Lvl6')
InputID <- c('acid', 'aeid', 'acid', 'acid', 'acid', 'aeid', 'aeid', 'aeid')
MethodID <- c('aeid', 'aeid', 'N/A', 'acid', 'aeid', 'N/A', 'aeid', 'aeid')
Table <- data.frame(Type, Level, InputID, MethodID)
library(htmlTable)
htmlTable(Table,
rnames = FALSE ,
caption="Table 1: Processing checklist.",
tfoot = " The Input ID column indicates the ID used for each processing step; Method ID indicates the ID used for assigning methods for data processing, when necessary. SC = single-concentration; MC = multiple-concentration.")
## ----eval= FALSE--------------------------------------------------------------
# ## For illustrative purposes, assign level 2 MC methods to
# ## ACIDs 97, 98, and 99. First check for available methods.
# mthds <- tcplMthdList(lvl = 2, type = "mc")
# mthds[1:2]
# ## Assign some methods to ACID 97, 98, and 99
# tcplMthdAssign(lvl = 2,
# id = 97:99,
# mthd_id = c(3, 4, 2),
# ordr = 1:3,
# type = "mc")
# tcplMthdLoad(lvl = 2, id = 97:99, type = "mc")
# ## Methods can be cleared one at a time for the given id(s)
# tcplMthdClear(lvl = 2, id = 99, mthd_id = 2, type = "mc")
# tcplMthdLoad(lvl = 2, id = 99, type = "mc")
# ## Or all methods can be cleared for the given id(s)
# tcplMthdClear(lvl = 2, id = 97:98, type = "mc")
# tcplMthdLoad(lvl = 2, id = 97:98, type = "mc")
## ----warning = FALSE, echo = FALSE--------------------------------------------
output <-
matrix(c("1. bval.apid.nwlls.med", "2. resp.fc", "1. bval.apid.lowconc.med", "2. bval.apid.pwlls.med",
"3. resp.log2", "4. resp.mult.neg1", "3. resp.pc", "4. resp.multneg1 ",
"1. bval.apid.lowconc.med", "2. resp.fc", "1. bval.spid.lowconc.med", "2. pval.apid.mwlls.med",
"3. resp.log2", "4. \t", "3. resp.pc", "4. \t" ,
"1. none", "2. resp.log10", "1. none", "2. resp.multneg1",
"3. resp.blineshift.50.spid", "4. \t", "3. \t", "4. \t"),
ncol=4, byrow = TRUE)
library(htmlTable)
htmlTable(output,
rnames = FALSE,
rgroup = c("Scheme 1",
"Scheme 2", "Scheme3"),
n.rgroup = c(2,2),
cgroup = c("Fold-Change", "\\%Control"),
n.cgroup = c(2,2),
caption="Table 2: Example normalization method assignments.")
## ----warning = FALSE, echo = FALSE--------------------------------------------
Level <- c(" Lvl 0", "Lvl 1 ", "Lvl 2 ")
Description <- c("Pre-processing: Vendor/dataset-specific pre-processing to organize heterogeneous raw data to the uniform format for processing by the *tcpl* package†",
"Normalize: Apply assay endpoint-specific normalization listed in the \'sc1_aeid\' table to the raw data to define response",
"Activity Call: Collapse replicates by median response, define the response cutoff based on methods in the \'sc2_aeid\' table, and determine activity"
)
output <-
data.frame(Level, Description)
library(htmlTable)
htmlTable(output,
rnames = FALSE ,
css.cell = ' padding-bottom: 5px; vertical-align:top; padding-right: 10px;min-width: 5em ',
align = 'l',
align.header = 'l',
caption="Table 3: Summary of the tcpl single-concentration pipeline.",
tfoot="† Level 0 pre-processing is outside the scope of this package")
## ----eval = FALSE-------------------------------------------------------------
# tcplLoadAeid(fld = "acid", val = 2)
## ----eval = FALSE-------------------------------------------------------------
# tcplMthdAssign(lvl = 1,
# id = 1:2,
# mthd_id = c(1, 11, 13),
# ordr = 1:3,
# type = "sc")
#
## ----eval = FALSE-------------------------------------------------------------
# tcplMthdAssign(lvl = 1,
# id = 2,
# mthd_id = 16,
# ordr = 1,
# type = "sc")
## ----eval = FALSE-------------------------------------------------------------
# ## Do level 1 processing for acid 1
# sc1_res <- tcplRun(id = 1, slvl = 1, elvl = 1, type = "sc")
## ----eval = FALSE-------------------------------------------------------------
# ## Assign a cutoff value of log2(1.2)
# tcplMthdAssign(lvl = 2,
# id = 1,
# mthd_id = 3,
# type = "sc")
## ----eval = FALSE-------------------------------------------------------------
# ## Do level 2 processing for acid 1
# sc2_res <- tcplRun(id = 1, slvl = 2, elvl = 2, type = "sc")
## ----warning = FALSE, echo = FALSE--------------------------------------------
Level <- c("Lvl 0 ", "Lvl 1", "Lvl 2", "Lvl 3", "Lvl 4", "Lvl 5", "Lvl 6")
Description <- c("Pre-processing: Vendor/dataset-specific pre-processing to organize heterogeneous raw data to the uniform format for processing by the *tcpl* package†",
"Index: Defne the replicate and concentration indices to facilitate
all subsequent processing",
"Transform: Apply assay component-specifc transformations
listed in the \'mc2_acid\' table to the raw data to defne the
corrected data",
"Normalize: Apply assay endpoint-specifc normalization listed in
the \'mc3_aeid\' table to the corrected data to define response",
"Fit: Model the concentration-response data utilizing three
objective functions: (1) constant, (2) hill, and (3) gain-loss",
"Model Selection/Acitivty Call: Select the winning model, define
the response cutoff based on methods in the \'mc5_aeid\' table, and
determine activity",
"Flag: Flag potential false positive and false negative endings based
on methods in the \'mc6_aeid\' table"
)
output <-
data.frame(Level, Description)
library(htmlTable)
htmlTable(output,
rnames = FALSE ,
css.cell = ' padding-bottom: 5px; vertical-align:top; padding-right: 10px;min-width: 5em ',
align = 'l',
align.header = 'l',
caption="Table 4: Summary of the tcpl multiple-concentration pipeline.",
tfoot="† Level 0 pre-processing is outside the scope of this package")
## ----eval = TRUE, message = FALSE---------------------------------------------
## Do level 1 processing for acid 1
mc1_res <- tcplRun(id = 1, slvl = 1, elvl = 1, type = "mc")
## ----eval = TRUE--------------------------------------------------------------
## Load the level 1 data and look at the cndx and repi values
m1dat <- tcplLoadData(lvl = 1,
fld = "acid",
val = 1,
type = "mc")
m1dat <- tcplPrepOtpt(m1dat)
setkeyv(m1dat, c("repi", "cndx"))
m1dat[chnm == "Bisphenol A",
list(chnm, conc, cndx, repi)]
## ----eval = TRUE, warning = FALSE, message = FALSE, fig.width = 30, fig.height= 20----
tcplPlotPlate(dat = m1dat, apid = "4009721")
## ----eval = TRUE, message = FALSE---------------------------------------------
tcplMthdAssign(lvl = 2,
id =1,
mthd_id = 1,
ordr = 1,
type = "mc")
## ----eval = TRUE, warning = FALSE, message = FALSE---------------------------
## Do level 2 processing for acid 1
mc2_res <- tcplRun(id = 1, slvl = 2, elvl = 2, type = "mc")
## ----eval = TRUE--------------------------------------------------------------
## Look at the assay endpoints for acid 1
tcplLoadAeid(fld = "acid", val = 1)
## ----eval = TRUE, message = FALSE---------------------------------------------
tcplMthdAssign(lvl = 3,
id = 1:2,
mthd_id = c(17, 9, 7),
ordr = 1:3, type = "mc")
## ----eval = TRUE,warning = FALSE, message = FALSE-----------------------------
## Do level 3 processing for acid 1
mc3_res <- tcplRun(id = 1, slvl = 3, elvl = 3, type = "mc")
## ----eval = TRUE, message = FALSE, warning = FALSE----------------------------
## Do level 4 processing for aeids 1&2 and load the data
tcplMthdAssign(lvl = 4, id = 1:2, mthd_id = c(1,2), type = "mc" )
mc4_res <- tcplRun(id = 1:2, slvl = 4, elvl = 4, type = "mc")
## ----eval = TRUE--------------------------------------------------------------
## Load the level 4 data
m4dat <- tcplPrepOtpt(tcplLoadData(lvl = 4, type = "mc"))
## List the first m4ids where the hill model converged
## for AEID 1
m4dat[hill == 1 & aeid == 1, head(m4id)]
## ----eval = TRUE, fig.width = 15, fig.height= 10------------------------------
## Plot a fit for m4id 7
tcplPlotM4ID(m4id = 7, lvl = 4)
## ----eval = TRUE, warning = FALSE---------------------------------------------
## Assign a cutoff value of 6*bmad
tcplMthdAssign(lvl = 5,
id = 1:2,
mthd_id = 6,
ordr = 1,
type = "mc")
## ----eval = TRUE--------------------------------------------------------------
par(family = "mono", mar = rep(1, 4), pty = "m")
plot.new()
plot.window(xlim = c(0, 30), ylim = c(-30, 100))
axis(side = 2, lwd = 2, col = "gray35")
rect(xleft = par()$usr[1],
xright = par()$usr[2],
ybottom = -15,
ytop = 15,
border = NA,
col = "gray45",
density = 15,
angle = 45)
abline(h = 26, lwd = 3, lty = "dashed", col = "gray30")
tmp <- list(modl = "gnls", gnls_ga = 12, gnls_tp = 80,
gnls_gw = 0.18, gnls_lw = 0.7, gnls_la = 25)
tcplAddModel(pars = tmp, lwd = 3, col = "dodgerblue2")
abline(v = 8.46, lwd = 3, lty = "solid", col = "firebrick")
text(x = 8.46, y = par()$usr[4]*0.9,
font = 2, labels = "ACB", cex = 2, pos = 2, srt = 90)
abline(v = 10.24, lwd = 3, lty = "solid", col = "yellow2")
text(x = 10.24, y = par()$usr[4]*0.9,
font = 2, labels = "ACC", cex = 2, pos = 2, srt = 90)
abline(v = 12, lwd = 3, lty = "solid", col = "dodgerblue2")
text(x = 12, y = par()$usr[4]*0.9,
font = 2, labels = "AC50", cex = 2, pos = 2, srt = 90)
points(x = c(8.46, 10.24, 12), y = c(15, 26, 40),
pch = 21, cex = 2, col = "gray30", lwd = 2,
bg = c("firebrick", "yellow2", "dodgerblue2"))
## ----eval = TRUE--------------------------------------------------------------
mc5_fit_categories <- fread(system.file("/example/mc5_fit_categories.csv",
package = "tcpl"),
sep = ",",
header = TRUE)
tcplPlotFitc(mc5_fit_categories)
## ----eval = TRUE, warning = FALSE, message = FALSE----------------------------
## Do level 5 processing for aeids 1&2 and load the data
mc5_res <- tcplRun(id = 1:2, slvl = 5, elvl = 5, type = "mc")
## ----eval = TRUE, fig.width = 15, fig.height= 10------------------------------
tcplPlotM4ID(m4id = 4, lvl = 5)
## ----eval = TRUE--------------------------------------------------------------
m5dat <- tcplLoadData(lvl = 5, type = "mc")
tcplPlotFitc(fitc = m5dat$fitc)
## ----eval = TRUE--------------------------------------------------------------
head(m5dat[fitc == 21,
list(m4id, hill_tp, gnls_tp,
max_med, coff, hitc)])
## ----eval = TRUE, fig.width = 15, fig.height= 10------------------------------
tcplPlotM4ID(m4id = 3, lvl = 5)
## ----eval = TRUE, warning = FALSE, message = FALSE, error = TRUE--------------
## Clear old methods
tcplMthdClear(lvl = 6, id = 1:2, type = "mc")
tcplMthdAssign(lvl = 6, id = 1:2,
mthd_id = c(6:8, 10:12, 15:16),
type = "mc")
tcplMthdLoad(lvl = 6, id = 1, type = "mc")
## ----eval = TRUE, warning = FALSE, error = TRUE-------------------------------
## Do level 6 processing
mc6_res <- tcplRun(id = 1:2, slvl = 5, elvl = 6, type = "mc")
## ----eval = TRUE, warning = FALSE---------------------------------------------
m6dat <- tcplLoadData(lvl = 6, type = "mc")
## ----eval = TRUE--------------------------------------------------------------
m6dat[m4id == 6]
## ----eval = TRUE, fig.width = 15, fig.height= 10------------------------------
tcplPlotM4ID(m4id = 6, lvl = 6)
## ----eval = FALSE, echo = FALSE, message = FALSE------------------------------
# rm(list=ls())
# library(htmlTable)
# library(tcpl)
# library(data.table)
## ----eval = TRUE, echo = FALSE, message = FALSE-------------------------------
sample <- data.table (spid = c("Tox21_400088", "Tox21_303655", "Tox21_110011", "Tox21_400081",
"DMSO", "Tox21_400037"),
chid= c("20182", "22364", "23463", "24102", "21735", "20283"),
stkc = c("", "", "", "", "", ""),
stkc_unit = c("", "", "", "", "", ""),
tested_conc_unit= c("", "", "", "", "", ""),
spid_legacy = c("", "", "", "", "", ""))
assay <- data.table(aid=numeric(), asid=numeric(), assay_name= character(), assay_desc= character(), timepoint_hr=numeric(), organism_id=numeric(), organism= character(), tissue= character(), cell_format= character(), cell_free_component_source= character(), cell_short_name= character(), cell_growth_mode= character(), assay_footprint= character(), assay_format_type= character(), assay_format_type_sub= character(), content_readout_type= character(), dilution_solvent= character(), dilution_solvent_percent_max= character()
)
assay_component <- data.table(acid=numeric(), aid=numeric(), assay_component_name= character(), assay_component_desc= character(), assay_component_target_desc= character(), parameter_readout_type= character(), assay_design_type= character(), assay_design_type_sub = character(),biological_process_target = character(),detection_technology_type = character(),detection_technology_type_sub= character(), detection_technology= character(), signal_direction_type= character(),key_assay_reagent_type= character(),
key_assay_reagent = character(),technological_target_type= character(), technological_target_type_sub= character() )
assay_component_endpoint <- data.table(aeid=numeric(), acid=numeric(), assay_component_endpoint_name= character(), export_ready=numeric(), internal_ready= character(), assay_component_endpoint_desc= character(), assay_function_type= character(), normalized_data_type= character(), analysis_direction= character(), burst_assay= character(), key_positive_control= character(), signal_direction= character(), intended_target_type= character(), intended_target_type_sub= character(), intended_target_family= character(), intended_target_family_sub= character(), fit_all=numeric())
assay_component_map <- data.table(acid =numeric(), acsn = character())
assay_source <- data.table(asid=numeric(), assay_source_name= character(), assay_source_long_name= character(), assay_source_desc= character())
chemical <- data.table(chid = c("20182", "22364", "23463" , "24102", "21735","20283"),
casn = c("80-05-7", "521-18-6", "150-30-1", "22224-92-6", "67-68-5", "95-83-0"),
chnm = c("Bisphenol A", "5alpha-Dihydrotestosterone","Phenylalanine","Fenamiphos",
"Dimethyl sulfoxide","4-Chloro-1,2-diaminobenzene"),
dsstox_substance_id = c("DTXSID7020182", "DTXSID9022364", "DTXSID9023463", "DTXSID3024102", "DTXSID2021735", "DTXSID5020283"),
code = c("C80057", "C521186","C150301","C22224926", "C67685","C95830"))
mc0 <- data.table(m0id =numeric(), acid =numeric(), spid = character(), apid = character(), rowi =numeric(),
coli =numeric(), wllt = character(), wllq =numeric(), conc = character(), rval = character(),
srcf =character(), created_date = character(), modified_date = character(),
modified_by = character())
mc1 <- data.table(m1id = character(),m0id =numeric(), acid = character(), cndx = character(), repi = character(), created_date = character(),
modified_date = character(), modified_by = character())
mc2 <- data.table(m2id = character(),m0id =numeric(), acid = character(),m1id =numeric(), cval = character(), created_date = character(),
modified_date = character(), modified_by = character())
mc3 <- data.table(m3id =numeric(), aeid =numeric(),m0id =numeric(), acid = character(),m1id =numeric(),m2id =numeric(), bval = character(), pval = character(),
logc = character(), resp = character(), created_date = character(), modified_date = character(), modified_by = character())
mc4 <- data.table(m4id =numeric(), aeid =numeric(), spid = character(), bmad = character(), resp_max = character(), resp_min = character(), max_mean = character(), max_mean_conc = character(), max_med = character(), max_med_conc = character(), logc_max = character(), logc_min = character(), cnst = character(), hill = character(), hcov = character(), gnls = character(), gcov = character(), cnst_er = character(), cnst_aic = character(), cnst_rmse = character(), cnst_prob = character(), hill_tp = character(), hill_tp_sd = character(), hill_ga = character(), hill_ga_sd = character(), hill_gw = character(), hill_gw_sd = character(), hill_er = character(), hill_er_sd = character(), hill_aic = character(), hill_rmse = character(), hill_prob = character(), gnls_tp = character(), gnls_tp_sd = character(), gnls_ga = character(), gnls_ga_sd = character(), gnls_gw = character(), gnls_gw_sd = character(), gnls_la = character(), gnls_la_sd = character(), gnls_lw = character(), gnls_lw_sd = character(), gnls_er = character(), gnls_er_sd = character(), gnls_aic = character(), gnls_rmse = character(), gnls_prob = character(), nconc = character(), npts = character(), nrep = character(), nmed_gtbl = character(), tmpi = character(), created_date = character(), modified_date = character(), modified_by = character())
mc5 <- data.table(m5id =numeric(), m4id =numeric(), aeid =numeric(), modl = character(), hitc = character(), fitc = character(), coff = character(), actp = character(), modl_er = character(), modl_tp = character(), modl_ga = character(), modl_gw = character(), modl_la = character(), modl_lw = character(), modl_prob = character(), modl_rmse = character(), modl_acc = character(), modl_acb = character(), modl_ac10 = character(), created_date = character(), modified_date = character(), modified_by = character())
mc6 <- data.table (m6id =numeric(), m5id =numeric(), m4id =numeric(), aeid =numeric(), mc6_mthd_id = character(), flag = character(), fval = character(), fval_unit = character(), created_date = character(), modified_date = character(), modified_by = character())
dir <- dbfile_temp
write.csv(mc0, file = file.path(dir,"mc0.csv"), row.names = F)
write.csv(mc1, file = file.path(dir,"mc1.csv"), row.names = F)
write.csv(mc2, file = file.path(dir,"mc2.csv"), row.names = F)
write.csv(mc3, file = file.path(dir,"mc3.csv"), row.names = F)
write.csv(mc4, file = file.path(dir,"mc4.csv"), row.names = F)
write.csv(mc5, file = file.path(dir,"mc5.csv"), row.names = F)
write.csv(mc6, file = file.path(dir,"mc6.csv"), row.names = F)
write.csv(sample, file = file.path(dir,"sample.csv"), row.names = F)
write.csv(assay, file = file.path(dir,"assay.csv"), row.names = F)
write.csv(assay_component, file = file.path(dir,"assay_component.csv"), row.names = F)
write.csv(assay_component_map, file = file.path(dir,"assay_component_map.csv"), row.names = F)
write.csv(assay_component_endpoint, file = file.path(dir,"assay_component_endpoint.csv"), row.names = F)
write.csv(assay_source, file = file.path(dir,"assay_source.csv"), row.names = F)
write.csv(chemical, file = file.path(dir,"chemical.csv"), row.names = F)
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## ----eval = TRUE, echo = FALSE, message = FALSE-------------------------------
library(htmlTable)
library(tcpl)
library(data.table)
## ----eval = TRUE, echo = FALSE, message = FALSE, results = "hide"-------------
## This chunk copies the tcplLite local directory to the temp directory used in installation
## to comply with CRAN policies on not writing to the installation directory
tmpdir <- tempdir()
#dbfile <- file.path(system.file(package = "tcpl"), "csv")
#file.copy(from = dbfile, tmpdir, recursive = TRUE)
dbfile_temp <- file.path(tmpdir, "csv")
dir.create(dbfile_temp, showWarnings = F)
tcplConf(db = dbfile_temp, drvr = 'tcplLite')
## ----eval = TRUE, echo = FALSE, message = FALSE-------------------------------
tcplRegister(what='spid', flds = list(spid=c("Tox21_303655", "Tox21_110011", "Tox21_400081", "DMSO", "Tox21_400037"),
chid=c("22364", "23463", "24102", "21735", "20283"),
tested_conc_unit=c('uM', 'uM', 'uM', 'uM', 'uM')
) )
tcplRegister(what='chid', flds=list(chid = c("22364", "23463" , "24102", "21735","20283"),
casn = c("521-18-6", "150-30-1", "22224-92-6", "67-68-5", "95-83-0"),
chnm = c("5alpha-Dihydrotestosterone","Phenylalanine","Fenamiphos",
"Dimethyl sulfoxide","4-Chloro-1,2-diaminobenzene"),
dsstox_substance_id = c("DTXSID9022364", "DTXSID9023463", "DTXSID3024102", "DTXSID2021735", "DTXSID5020283"),
code = c("C521186","C150301","C22224926", "C67685","C95830")))
## ----eval = TRUE, message = FALSE---------------------------------------------
## Add a new assay source, call it CTox,
## that produced the data
tcplRegister(what = "asid", flds = list(asid = 1,
asnm = "CTox"))
## ----eval = TRUE--------------------------------------------------------------
tcplLoadAsid()
## ----eval = TRUE, message = FALSE---------------------------------------------
tcplRegister(what = "aid",
flds = list(asid = 1,
anm = "TOX21_ERa_BLA_Agonist",
assay_footprint = "1536 well"))
## ----eval = TRUE, message = FALSE---------------------------------------------
tcplRegister(what = "acid",
flds = list(aid = 1,
acnm = "TOX21_ERa_BLA_Agonist_ratio"))
tcplRegister(what = "aeid",
flds = list(acid = c(1, 1),
aenm = c("TOX21_ERa_BLA_Agonist_ratio_gain",
"TOX21_ERa_BLA_Agonist_ratio_loss"),
normalized_data_type =
rep("percent_activity", 1),
export_ready = c(1, 1),
burst_assay = c(0, 0),
fit_all = c(0, 0)))
## ----eval = TRUE--------------------------------------------------------------
data(chdat, package = "tcpl")
setDT(chdat)
head(chdat)
## ----eval = TRUE, message = FALSE---------------------------------------------
## Register the unique chemicals
cmap <- tcplLoadChem() # Chemicals already registered
chdat.register <- chdat[!(chdat$code %in% cmap$code)] # Chemicals in chdat that are not registered yet
tcplRegister(what = "chid",
flds = chdat.register[,
unique(.SD),
.SDcols = c("casn", "chnm", "dsstox_substance_id", "code", "chid")])
## ----eval = TRUE, message = FALSE---------------------------------------------
tcplRegister(what = "spid",
flds = merge(chdat[ , list(spid, casn)],
chdat.register[ , list(casn, chid)],
by = "casn")[ , list(spid, chid)])
## ----eval = FALSE-------------------------------------------------------------
# grp1 <- cmap[chid %% 2 == 0, unique(chid)]
# grp2 <- cmap[chid %% 2 == 1, unique(chid)]
# tcplRegister(what = "clib",
# flds = list(clib = "group_1", chid = grp1))
## ----eval = FALSE-------------------------------------------------------------
# tcplRegister(what = "clib",
# flds = list(clib = "group_2", chid = grp2))
## ----eval = FALSE-------------------------------------------------------------
# tcplRegister(what = "clib",
# flds = list(clib = "other", chid = 1:2))
## ----eval = FALSE-------------------------------------------------------------
# tcplLoadClib(field = "chid", val = 1:2)
## ----eval = TRUE--------------------------------------------------------------
data(mcdat, package = 'tcpl')
setDT(mcdat)
## ----eval = TRUE, message = FALSE---------------------------------------------
tcplRegister(what = "acsn",
flds = list(acid = 1, acsn = "TCPL-MC-Demo"))
## ----eval = TRUE, message = FALSE---------------------------------------------
## Cannot process a concentration value of 0; use .01 as a dummy value
mcdat$conc[mcdat$conc == 0] <- .01
tcplWriteLvl0(dat = mcdat, type = "mc")
## ----eval = TRUE--------------------------------------------------------------
tcplLoadData(lvl = 0, fld = "acid", val = 1, type = "mc")
## ----warning = FALSE, echo = FALSE--------------------------------------------
Type <- c('SC', 'SC', 'MC', 'MC', 'MC', 'MC', 'MC', 'MC')
Level <- c('Lvl1', 'Lvl2', 'Lvl1', 'Lvl2', 'Lvl3', 'Lvl4', 'Lvl5', 'Lvl6')
InputID <- c('acid', 'aeid', 'acid', 'acid', 'acid', 'aeid', 'aeid', 'aeid')
MethodID <- c('aeid', 'aeid', 'N/A', 'acid', 'aeid', 'N/A', 'aeid', 'aeid')
Table <- data.frame(Type, Level, InputID, MethodID)
library(htmlTable)
htmlTable(Table,
rnames = FALSE ,
caption="Table 1: Processing checklist.",
tfoot = " The Input ID column indicates the ID used for each processing step; Method ID indicates the ID used for assigning methods for data processing, when necessary. SC = single-concentration; MC = multiple-concentration.")
## ----eval= FALSE--------------------------------------------------------------
# ## For illustrative purposes, assign level 2 MC methods to
# ## ACIDs 97, 98, and 99. First check for available methods.
# mthds <- tcplMthdList(lvl = 2, type = "mc")
# mthds[1:2]
# ## Assign some methods to ACID 97, 98, and 99
# tcplMthdAssign(lvl = 2,
# id = 97:99,
# mthd_id = c(3, 4, 2),
# ordr = 1:3,
# type = "mc")
# tcplMthdLoad(lvl = 2, id = 97:99, type = "mc")
# ## Methods can be cleared one at a time for the given id(s)
# tcplMthdClear(lvl = 2, id = 99, mthd_id = 2, type = "mc")
# tcplMthdLoad(lvl = 2, id = 99, type = "mc")
# ## Or all methods can be cleared for the given id(s)
# tcplMthdClear(lvl = 2, id = 97:98, type = "mc")
# tcplMthdLoad(lvl = 2, id = 97:98, type = "mc")
## ----warning = FALSE, echo = FALSE--------------------------------------------
output <-
matrix(c("1. bval.apid.nwlls.med", "2. resp.fc", "1. bval.apid.lowconc.med", "2. bval.apid.pwlls.med",
"3. resp.log2", "4. resp.mult.neg1", "3. resp.pc", "4. resp.multneg1 ",
"1. bval.apid.lowconc.med", "2. resp.fc", "1. bval.spid.lowconc.med", "2. pval.apid.mwlls.med",
"3. resp.log2", "4. \t", "3. resp.pc", "4. \t" ,
"1. none", "2. resp.log10", "1. none", "2. resp.multneg1",
"3. resp.blineshift.50.spid", "4. \t", "3. \t", "4. \t"),
ncol=4, byrow = TRUE)
library(htmlTable)
htmlTable(output,
rnames = FALSE,
rgroup = c("Scheme 1",
"Scheme 2", "Scheme3"),
n.rgroup = c(2,2),
cgroup = c("Fold-Change", "\\%Control"),
n.cgroup = c(2,2),
caption="Table 2: Example normalization method assignments.")
## ----warning = FALSE, echo = FALSE--------------------------------------------
Level <- c(" Lvl 0", "Lvl 1 ", "Lvl 2 ")
Description <- c("Pre-processing: Vendor/dataset-specific pre-processing to organize heterogeneous raw data to the uniform format for processing by the *tcpl* package†",
"Normalize: Apply assay endpoint-specific normalization listed in the \'sc1_aeid\' table to the raw data to define response",
"Activity Call: Collapse replicates by median response, define the response cutoff based on methods in the \'sc2_aeid\' table, and determine activity"
)
output <-
data.frame(Level, Description)
library(htmlTable)
htmlTable(output,
rnames = FALSE ,
css.cell = ' padding-bottom: 5px; vertical-align:top; padding-right: 10px;min-width: 5em ',
align = 'l',
align.header = 'l',
caption="Table 3: Summary of the tcpl single-concentration pipeline.",
tfoot="† Level 0 pre-processing is outside the scope of this package")
## ----eval = FALSE-------------------------------------------------------------
# tcplLoadAeid(fld = "acid", val = 2)
## ----eval = FALSE-------------------------------------------------------------
# tcplMthdAssign(lvl = 1,
# id = 1:2,
# mthd_id = c(1, 11, 13),
# ordr = 1:3,
# type = "sc")
#
## ----eval = FALSE-------------------------------------------------------------
# tcplMthdAssign(lvl = 1,
# id = 2,
# mthd_id = 16,
# ordr = 1,
# type = "sc")
## ----eval = FALSE-------------------------------------------------------------
# ## Do level 1 processing for acid 1
# sc1_res <- tcplRun(id = 1, slvl = 1, elvl = 1, type = "sc")
## ----eval = FALSE-------------------------------------------------------------
# ## Assign a cutoff value of log2(1.2)
# tcplMthdAssign(lvl = 2,
# id = 1,
# mthd_id = 3,
# type = "sc")
## ----eval = FALSE-------------------------------------------------------------
# ## Do level 2 processing for acid 1
# sc2_res <- tcplRun(id = 1, slvl = 2, elvl = 2, type = "sc")
## ----warning = FALSE, echo = FALSE--------------------------------------------
Level <- c("Lvl 0 ", "Lvl 1", "Lvl 2", "Lvl 3", "Lvl 4", "Lvl 5", "Lvl 6")
Description <- c("Pre-processing: Vendor/dataset-specific pre-processing to organize heterogeneous raw data to the uniform format for processing by the *tcpl* package†",
"Index: Defne the replicate and concentration indices to facilitate
all subsequent processing",
"Transform: Apply assay component-specifc transformations
listed in the \'mc2_acid\' table to the raw data to defne the
corrected data",
"Normalize: Apply assay endpoint-specifc normalization listed in
the \'mc3_aeid\' table to the corrected data to define response",
"Fit: Model the concentration-response data utilizing three
objective functions: (1) constant, (2) hill, and (3) gain-loss",
"Model Selection/Acitivty Call: Select the winning model, define
the response cutoff based on methods in the \'mc5_aeid\' table, and
determine activity",
"Flag: Flag potential false positive and false negative endings based
on methods in the \'mc6_aeid\' table"
)
output <-
data.frame(Level, Description)
library(htmlTable)
htmlTable(output,
rnames = FALSE ,
css.cell = ' padding-bottom: 5px; vertical-align:top; padding-right: 10px;min-width: 5em ',
align = 'l',
align.header = 'l',
caption="Table 4: Summary of the tcpl multiple-concentration pipeline.",
tfoot="† Level 0 pre-processing is outside the scope of this package")
## ----eval = TRUE, message = FALSE---------------------------------------------
## Do level 1 processing for acid 1
mc1_res <- tcplRun(id = 1, slvl = 1, elvl = 1, type = "mc")
## ----eval = TRUE--------------------------------------------------------------
## Load the level 1 data and look at the cndx and repi values
m1dat <- tcplLoadData(lvl = 1,
fld = "acid",
val = 1,
type = "mc")
m1dat <- tcplPrepOtpt(m1dat)
setkeyv(m1dat, c("repi", "cndx"))
m1dat[chnm == "Bisphenol A",
list(chnm, conc, cndx, repi)]
## ----eval = TRUE, warning = FALSE, message = FALSE, fig.width = 30, fig.height= 20----
tcplPlotPlate(dat = m1dat, apid = "4009721")
## ----eval = TRUE, message = FALSE---------------------------------------------
tcplMthdAssign(lvl = 2,
id =1,
mthd_id = 1,
ordr = 1,
type = "mc")
## ----eval = TRUE, warning = FALSE, message = FALSE---------------------------
## Do level 2 processing for acid 1
mc2_res <- tcplRun(id = 1, slvl = 2, elvl = 2, type = "mc")
## ----eval = TRUE--------------------------------------------------------------
## Look at the assay endpoints for acid 1
tcplLoadAeid(fld = "acid", val = 1)
## ----eval = TRUE, message = FALSE---------------------------------------------
tcplMthdAssign(lvl = 3,
id = 1:2,
mthd_id = c(17, 9, 7),
ordr = 1:3, type = "mc")
## ----eval = TRUE,warning = FALSE, message = FALSE-----------------------------
## Do level 3 processing for acid 1
mc3_res <- tcplRun(id = 1, slvl = 3, elvl = 3, type = "mc")
## ----eval = TRUE, message = FALSE, warning = FALSE----------------------------
## Do level 4 processing for aeids 1&2 and load the data
tcplMthdAssign(lvl = 4, id = 1:2, mthd_id = c(1,2), type = "mc" )
mc4_res <- tcplRun(id = 1:2, slvl = 4, elvl = 4, type = "mc")
## ----eval = TRUE--------------------------------------------------------------
## Load the level 4 data
m4dat <- tcplPrepOtpt(tcplLoadData(lvl = 4, type = "mc"))
## List the first m4ids where the hill model converged
## for AEID 1
m4dat[hill == 1 & aeid == 1, head(m4id)]
## ----eval = TRUE, fig.width = 15, fig.height= 10------------------------------
## Plot a fit for m4id 7
tcplPlotM4ID(m4id = 7, lvl = 4)
## ----eval = TRUE, warning = FALSE---------------------------------------------
## Assign a cutoff value of 6*bmad
tcplMthdAssign(lvl = 5,
id = 1:2,
mthd_id = 6,
ordr = 1,
type = "mc")
## ----eval = TRUE--------------------------------------------------------------
par(family = "mono", mar = rep(1, 4), pty = "m")
plot.new()
plot.window(xlim = c(0, 30), ylim = c(-30, 100))
axis(side = 2, lwd = 2, col = "gray35")
rect(xleft = par()$usr[1],
xright = par()$usr[2],
ybottom = -15,
ytop = 15,
border = NA,
col = "gray45",
density = 15,
angle = 45)
abline(h = 26, lwd = 3, lty = "dashed", col = "gray30")
tmp <- list(modl = "gnls", gnls_ga = 12, gnls_tp = 80,
gnls_gw = 0.18, gnls_lw = 0.7, gnls_la = 25)
tcplAddModel(pars = tmp, lwd = 3, col = "dodgerblue2")
abline(v = 8.46, lwd = 3, lty = "solid", col = "firebrick")
text(x = 8.46, y = par()$usr[4]*0.9,
font = 2, labels = "ACB", cex = 2, pos = 2, srt = 90)
abline(v = 10.24, lwd = 3, lty = "solid", col = "yellow2")
text(x = 10.24, y = par()$usr[4]*0.9,
font = 2, labels = "ACC", cex = 2, pos = 2, srt = 90)
abline(v = 12, lwd = 3, lty = "solid", col = "dodgerblue2")
text(x = 12, y = par()$usr[4]*0.9,
font = 2, labels = "AC50", cex = 2, pos = 2, srt = 90)
points(x = c(8.46, 10.24, 12), y = c(15, 26, 40),
pch = 21, cex = 2, col = "gray30", lwd = 2,
bg = c("firebrick", "yellow2", "dodgerblue2"))
## ----eval = TRUE--------------------------------------------------------------
mc5_fit_categories <- fread(system.file("/example/mc5_fit_categories.csv",
package = "tcpl"),
sep = ",",
header = TRUE)
tcplPlotFitc(mc5_fit_categories)
## ----eval = TRUE, warning = FALSE, message = FALSE----------------------------
## Do level 5 processing for aeids 1&2 and load the data
mc5_res <- tcplRun(id = 1:2, slvl = 5, elvl = 5, type = "mc")
## ----eval = TRUE, fig.width = 15, fig.height= 10------------------------------
tcplPlotM4ID(m4id = 4, lvl = 5)
## ----eval = TRUE--------------------------------------------------------------
m5dat <- tcplLoadData(lvl = 5, type = "mc")
tcplPlotFitc(fitc = m5dat$fitc)
## ----eval = TRUE--------------------------------------------------------------
head(m5dat[fitc == 21,
list(m4id, hill_tp, gnls_tp,
max_med, coff, hitc)])
## ----eval = TRUE, fig.width = 15, fig.height= 10------------------------------
tcplPlotM4ID(m4id = 3, lvl = 5)
## ----eval = TRUE, warning = FALSE, message = FALSE, error = TRUE--------------
## Clear old methods
tcplMthdClear(lvl = 6, id = 1:2, type = "mc")
tcplMthdAssign(lvl = 6, id = 1:2,
mthd_id = c(6:8, 10:12, 15:16),
type = "mc")
tcplMthdLoad(lvl = 6, id = 1, type = "mc")
## ----eval = TRUE, warning = FALSE, error = TRUE-------------------------------
## Do level 6 processing
mc6_res <- tcplRun(id = 1:2, slvl = 5, elvl = 6, type = "mc")
## ----eval = TRUE, warning = FALSE---------------------------------------------
m6dat <- tcplLoadData(lvl = 6, type = "mc")
## ----eval = TRUE--------------------------------------------------------------
m6dat[m4id == 6]
## ----eval = TRUE, fig.width = 15, fig.height= 10------------------------------
tcplPlotM4ID(m4id = 6, lvl = 6)
## ----eval = FALSE, echo = FALSE, message = FALSE------------------------------
# rm(list=ls())
# library(htmlTable)
# library(tcpl)
# library(data.table)
## ----eval = TRUE, echo = FALSE, message = FALSE-------------------------------
sample <- data.table (spid = c("Tox21_400088", "Tox21_303655", "Tox21_110011", "Tox21_400081",
"DMSO", "Tox21_400037"),
chid= c("20182", "22364", "23463", "24102", "21735", "20283"),
stkc = c("", "", "", "", "", ""),
stkc_unit = c("", "", "", "", "", ""),
tested_conc_unit= c("", "", "", "", "", ""),
spid_legacy = c("", "", "", "", "", ""))
assay <- data.table(aid=numeric(), asid=numeric(), assay_name= character(), assay_desc= character(), timepoint_hr=numeric(), organism_id=numeric(), organism= character(), tissue= character(), cell_format= character(), cell_free_component_source= character(), cell_short_name= character(), cell_growth_mode= character(), assay_footprint= character(), assay_format_type= character(), assay_format_type_sub= character(), content_readout_type= character(), dilution_solvent= character(), dilution_solvent_percent_max= character()
)
assay_component <- data.table(acid=numeric(), aid=numeric(), assay_component_name= character(), assay_component_desc= character(), assay_component_target_desc= character(), parameter_readout_type= character(), assay_design_type= character(), assay_design_type_sub = character(),biological_process_target = character(),detection_technology_type = character(),detection_technology_type_sub= character(), detection_technology= character(), signal_direction_type= character(),key_assay_reagent_type= character(),
key_assay_reagent = character(),technological_target_type= character(), technological_target_type_sub= character() )
assay_component_endpoint <- data.table(aeid=numeric(), acid=numeric(), assay_component_endpoint_name= character(), export_ready=numeric(), internal_ready= character(), assay_component_endpoint_desc= character(), assay_function_type= character(), normalized_data_type= character(), analysis_direction= character(), burst_assay= character(), key_positive_control= character(), signal_direction= character(), intended_target_type= character(), intended_target_type_sub= character(), intended_target_family= character(), intended_target_family_sub= character(), fit_all=numeric())
assay_component_map <- data.table(acid =numeric(), acsn = character())
assay_source <- data.table(asid=numeric(), assay_source_name= character(), assay_source_long_name= character(), assay_source_desc= character())
chemical <- data.table(chid = c("20182", "22364", "23463" , "24102", "21735","20283"),
casn = c("80-05-7", "521-18-6", "150-30-1", "22224-92-6", "67-68-5", "95-83-0"),
chnm = c("Bisphenol A", "5alpha-Dihydrotestosterone","Phenylalanine","Fenamiphos",
"Dimethyl sulfoxide","4-Chloro-1,2-diaminobenzene"),
dsstox_substance_id = c("DTXSID7020182", "DTXSID9022364", "DTXSID9023463", "DTXSID3024102", "DTXSID2021735", "DTXSID5020283"),
code = c("C80057", "C521186","C150301","C22224926", "C67685","C95830"))
mc0 <- data.table(m0id =numeric(), acid =numeric(), spid = character(), apid = character(), rowi =numeric(),
coli =numeric(), wllt = character(), wllq =numeric(), conc = character(), rval = character(),
srcf =character(), created_date = character(), modified_date = character(),
modified_by = character())
mc1 <- data.table(m1id = character(),m0id =numeric(), acid = character(), cndx = character(), repi = character(), created_date = character(),
modified_date = character(), modified_by = character())
mc2 <- data.table(m2id = character(),m0id =numeric(), acid = character(),m1id =numeric(), cval = character(), created_date = character(),
modified_date = character(), modified_by = character())
mc3 <- data.table(m3id =numeric(), aeid =numeric(),m0id =numeric(), acid = character(),m1id =numeric(),m2id =numeric(), bval = character(), pval = character(),
logc = character(), resp = character(), created_date = character(), modified_date = character(), modified_by = character())
mc4 <- data.table(m4id =numeric(), aeid =numeric(), spid = character(), bmad = character(), resp_max = character(), resp_min = character(), max_mean = character(), max_mean_conc = character(), max_med = character(), max_med_conc = character(), logc_max = character(), logc_min = character(), cnst = character(), hill = character(), hcov = character(), gnls = character(), gcov = character(), cnst_er = character(), cnst_aic = character(), cnst_rmse = character(), cnst_prob = character(), hill_tp = character(), hill_tp_sd = character(), hill_ga = character(), hill_ga_sd = character(), hill_gw = character(), hill_gw_sd = character(), hill_er = character(), hill_er_sd = character(), hill_aic = character(), hill_rmse = character(), hill_prob = character(), gnls_tp = character(), gnls_tp_sd = character(), gnls_ga = character(), gnls_ga_sd = character(), gnls_gw = character(), gnls_gw_sd = character(), gnls_la = character(), gnls_la_sd = character(), gnls_lw = character(), gnls_lw_sd = character(), gnls_er = character(), gnls_er_sd = character(), gnls_aic = character(), gnls_rmse = character(), gnls_prob = character(), nconc = character(), npts = character(), nrep = character(), nmed_gtbl = character(), tmpi = character(), created_date = character(), modified_date = character(), modified_by = character())
mc5 <- data.table(m5id =numeric(), m4id =numeric(), aeid =numeric(), modl = character(), hitc = character(), fitc = character(), coff = character(), actp = character(), modl_er = character(), modl_tp = character(), modl_ga = character(), modl_gw = character(), modl_la = character(), modl_lw = character(), modl_prob = character(), modl_rmse = character(), modl_acc = character(), modl_acb = character(), modl_ac10 = character(), created_date = character(), modified_date = character(), modified_by = character())
mc6 <- data.table (m6id =numeric(), m5id =numeric(), m4id =numeric(), aeid =numeric(), mc6_mthd_id = character(), flag = character(), fval = character(), fval_unit = character(), created_date = character(), modified_date = character(), modified_by = character())
dir <- dbfile_temp
write.csv(mc0, file = file.path(dir,"mc0.csv"), row.names = F)
write.csv(mc1, file = file.path(dir,"mc1.csv"), row.names = F)
write.csv(mc2, file = file.path(dir,"mc2.csv"), row.names = F)
write.csv(mc3, file = file.path(dir,"mc3.csv"), row.names = F)
write.csv(mc4, file = file.path(dir,"mc4.csv"), row.names = F)
write.csv(mc5, file = file.path(dir,"mc5.csv"), row.names = F)
write.csv(mc6, file = file.path(dir,"mc6.csv"), row.names = F)
write.csv(sample, file = file.path(dir,"sample.csv"), row.names = F)
write.csv(assay, file = file.path(dir,"assay.csv"), row.names = F)
write.csv(assay_component, file = file.path(dir,"assay_component.csv"), row.names = F)
write.csv(assay_component_map, file = file.path(dir,"assay_component_map.csv"), row.names = F)
write.csv(assay_component_endpoint, file = file.path(dir,"assay_component_endpoint.csv"), row.names = F)
write.csv(assay_source, file = file.path(dir,"assay_source.csv"), row.names = F)
write.csv(chemical, file = file.path(dir,"chemical.csv"), row.names = F)
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