| mc_vignette {tcpl} | R Documentation |
List with multi-concentration data for the vignette
Description
This dataset is a list with 6 data.tables (mc0,mc1,mc2,mc3,mc4,mc5).
Usage
mc_vignette
Format
-
mc0 A data frame with 78 rows and 18 columns containing level 0 formatted raw data.
- spid
Sample ID
- chid
Unique chemical ID number for tcpl
- casn
Chemical Abstract Service(CAS) number
- chnm
Chemical name
- dsstox_substance_id
Chemical-specific DTXSID
- code
CAS number compressed into numeric string
- acid
Assay Component ID
- acnm
Assay Component Name
- m0id
Level 0 (mc0) ID
- apid
Assay plate ID
- rowi
Row Index
- coli
Column Index
- wllt
Well Type
- wllq
Well Quality (0 or 1)
- conc
Concentration in micromolar
- rval
Raw assay component readout value
- srcf
Source file containing the raw data
- conc_unit
Concentration Units
-
mc1 A data frame with 78 rows and 21 columns containing level 1 replicate and concentration level indicated data.
- spid
Sample ID
- chid
Unique chemical ID number for tcpl
- casn
Chemical Abstract Service(CAS) number
- chnm
Chemical name
- dsstox_substance_id
Chemical-specific DTXSID
- code
CAS number compressed into numeric string
- acid
Assay Component ID
- acnm
Assay Component Name
- m0id
Level 0 (mc0) ID
- m1id
Level 1 (mc1) ID
- apid
Assay plate ID
- rowi
Row Index
- coli
Column Index
- wllt
Well Type
- wllq
Well Quality (0 or 1)
- conc
Concentration in micromolar
- rval
Raw assay component readout value
- cndx
Concentration index defined by ranking the unique concentrations, with the lowest concentration starting at 1.
- repi
Temporary replicate ID is defined, the data are scanned from top to bottom and increment the replicate index every time a replicate ID is duplicated
- srcf
Source file containing the raw data
- conc_unit
Concentration Units
-
mc2 A data frame with 78 rows and 20 columns containing level 2 assay component-specific corrections.
- spid
Sample ID
- chid
Unique chemical ID number for tcpl
- casn
Chemical Abstract Service(CAS) number
- chnm
Chemical name
- dsstox_substance_id
Chemical-specific DTXSID
- code
CAS number compressed into numeric string
- acid
Assay Component ID
- acnm
Assay Component Name
- m0id
Level 0 (mc0) ID
- m1id
Level 1 (mc1) ID
- m2id
Level 2 (mc2) ID
- apid
Assay plate ID
- rowi
Row Index
- coli
Column Index
- wllt
Well Type
- conc
Concentration in micromolar
- cval
Corrected Value
- cndx
Concentration index defined by ranking the unique concentrations, with the lowest concentration starting at 1.
- repi
Temporary replicate ID is defined, the data are scanned from top to bottom and increment the replicate index every time a replicate ID is duplicated
- conc_unit
Concentration Units
-
mc3 A data frame with 78 rows and 22 columns containing level 3 assay endpoint normalized data.
- spid
Sample ID
- chid
Unique chemical ID number for tcpl
- casn
Chemical Abstract Service(CAS) number
- chnm
Chemical name
- dsstox_substance_id
Chemical-specific DTXSID
- code
CAS number compressed into numeric string
- aeid
Assay Component Endpoint ID
- aenm
Assay endpoint name (i.e., assay_component_endpoint_name)
- m0id
Level 0 (mc0) ID
- m1id
Level 1 (mc1) ID
- m2id
Level 2 (mc2) ID
- m3id
Level 3 (mc3) ID
- logc
Log base 10 concentration
- resp
Normalized response value
- cndx
Concentration index defined by ranking the unique concentrations, with the lowest concentration starting at 1.
- wllt
Well Type
- apid
Assay plate ID
- rowi
Row Index
- coli
Column Index
- repi
Temporary replicate ID is defined, the data are scanned from top to bottom and increment the replicate index every time a replicate ID is duplicated
- resp_unit
Response Units
- conc_unit
Concentration Units
-
mc4 A data frame with 5 rows and 149 columns containing level 4 concentration-response fitting data (all fits).
- spid
Sample ID
- chid
Unique chemical ID number for tcpl
- casn
Chemical Abstract Service(CAS) number
- chnm
Chemical name
- dsstox_substance_id
Chemical-specific DTXSID
- code
CAS number compressed into numeric string
- aeid
Assay Component Endpoint ID
- aenm
Assay endpoint name (i.e., assay_component_endpoint_name)
- m4id
Level 4 (mc4) ID
- bmad
The median absolute deviation of all treatment wells (default option) or blank wells
- resp_max
Maximum observed response
- resp_min
Minimum observed response
- max_mean
Maximum mean response
- max_mean_conc
Concentration of the maximum mean response
- max_med
Maximum median response
- max_med_conc
Concentration of the maximum median response
- logc_max
Maximum concentration on the log scale
- logc_min
Minimum concentration on the log scale
- nconc
The total number of concentration groups
- npts
Total number of observed responses (i.e. data points in the concentration series)
- nrep
Number of replicates in concentration groups
- nmed_gtbl
The number of median responses greater than 3BMAD
- cnst_success
Success indicator for the Constant model; 1 if the optimization was successful, otherwise 0
- cnst_aic
Akaike Information Criteria (AIC) for the Constant model
- cnst_rme
Root mean square error for the Constant model
- cnst_er
Error term for the Constant model
- hill_success
Success indicator for the Hill model; 1 if the optimization was successful, otherwise 0
- hill_aic
Akaike Information Criteria (AIC) for the Hill model
- hill_cov
Success indicator for the Hill model covariance calculation; 1 if the Hessian matrix inversion is successful, otherwise 0
- hill_rme
Root mean square erro for the Hill model
- hill_tp
The top parameter indicating the maximal estimated response
- hill_ga
The gain parameter for the Hill model, gain AC50
- hill_p
The power parameter for the Hill model
- hill_er
Error term for the Hill model
- hill_tp_sd
Standard deviation of the Hill model top parameter
- hill_ga_sd
Standard deviation of the Hill model gain parameter
- hill_p_sd
Standard deviation of the Hill model power parameter
- hill_er_sd
Standard deviation of the Hill model error term
- hill_top
The maximal response on the resulting Hill model fit
- hill_ac50
Concentration at 50% of the maximal response on the Hill model fit
- gnls_success
Success indicator for the Gain-loss model; 1 if the optimization was successful, otherwise 0
- gnls_aic
Akaike Information Criteria (AIC) for the Gain-loss model
- gnls_cov
Success indicator for the Gain-loss model covariance calculation; 1 if the Hessian matrix inversion is successful, otherwise 0
- gnls_rme
Root mean square erro for the Gain-loss model
- gnls_tp
The top parameter indicating the maximal estimated response
- gnls_ga
The gain parameter for the Gain-loss model, gain AC50
- gnls_p
The gain power parameter for the Gain-loss model
- gnls_la
The loss parameter for the Gain-loss model, loss AC50
- gnls_q
The loss power parameter for the Gain-loss model
- gnls_er
Error term for the Gain-loss model
- gnls_tp_sd
Standard deviation of the Gain-loss model top parameter
- gnls_ga_sd
Standard deviation of the Gain-loss model gain parameter
- gnls_p_sd
Standard deviation of the Gain-loss model gain power parameter
- gnls_la_sd
Standard deviation of the Gain-loss model loss parameter
- gnls_q_sd
Standard deviation of the Gain-loss model loss power parameter
- gnls_er_sd
Standard deviation of the Gain-loss model error term
- gnls_top
The maximal response on the resulting Gain-loss model fit
- gnls_ac50
Concentration at 50% of the maximal response on the Gain-loss model fit, gain AC50
- gnls_ac50_loss
Concentration at 50% of the maximal response on the Gain-loss model fit, loss AC50
- poly1_success
Success indicator for the Polynomial 1 model; 1 if the optimization was successful, otherwise 0
- poly1_aic
Akaike Information Criteria (AIC) for the Polynomial 1 model
- poly1_cov
Success indicator for the Polynomial 1 model covariance calculation; 1 if the Hessian matrix inversion is successful, otherwise 0
- poly1_rme
Root mean square erro for the Polynomial 1 model
- poly1_a
The y-scale parameter for the Polynomial 1 model
- poly1_er
Error term for the Polynomial 1 model
- poly1_a_sd
Standard deviation of the Polynomial 1 model y-scale parameter
- poly1_er_sd
Standard deviation of the Polynomial 1 model error term
- poly1_top
The maximal response on the resulting Polynomial 1 model fit
- poly1_ac50
Concentration at 50% of the maximal response on the Polynomial 1 model fit
- poly2_success
Success indicator for the Polynomial 2 model; 1 if the optimization was successful, otherwise 0
- poly2_aic
Akaike Information Criteria (AIC) for the Polynomial 2 model
- poly2_cov
Success indicator for the Polynomial 2 model covariance calculation; 1 if the Hessian matrix inversion is successful, otherwise 0
- poly2_rme
Root mean square erro for the Polynomial 2 model
- poly2_a
The y-scale parameter for the Polynomial 2 model
- poly2_b
The x-scale parameter for the Polynomial 2 model
- poly2_er
Error term for the Polynomial 2 model
- poly2_a_sd
Standard deviation of the Polynomial 2 model y-scale parameter
- poly2_b_sd
Standard deviation of the Polynomial 2 model x-scale parameter
- poly2_er_sd
Standard deviation of the Polynomial 2 model error term
- poly2_top
The maximal response on the resulting Polynomial 2 model fit
- poly2_ac50
Concentration at 50% of the maximal response on the Polynomial 2 model fit
- pow_success
Success indicator for the Power model; 1 if the optimization was successful, otherwise 0
- pow_aic
Akaike Information Criteria (AIC) for the Power model
- pow_cov
Success indicator for the Power model covariance calculation; 1 if the Hessian matrix inversion is successful, otherwise 0
- pow_rme
Root mean square erro for the Power model
- pow_a
The y-scale parameter for the Power model
- pow_p
The power parameter for the Power model
- pow_er
Error term for the Power model
- pow_a_sd
Standard deviation of the Power model y-scale parameter
- pow_p_sd
Standard deviation of the Power model power parameter
- pow_er_sd
Standard deviation of the Power model error term
- pow_top
The maximal response on the resulting Power model fit
- pow_ac50
Concentration at 50% of the maximal response on the Power model fit
- exp2_success
Success indicator for the Exponential 2 model; 1 if the optimization was successful, otherwise 0
- exp2_aic
Akaike Information Criteria (AIC) for the Exponential 2 model
- exp2_cov
Success indicator for the Exponential 2 model covariance calculation; 1 if the Hessian matrix inversion is successful, otherwise 0
- exp2_rme
Root mean square erro for the Exponential 2 model
- exp2_a
The y-scale parameter for the Exponential 2 model
- exp2_b
The x-scale parameter for the Exponential 2 model
- exp2_er
Error term for the Exponential 2 model
- exp2_a_sd
Standard deviation of the Exponential 2 model y-scale parameter
- exp2_b_sd
Standard deviation of the Exponential 2 model x-scale parameter
- exp2_er_sd
Standard deviation of the Exponential 2 model error term
- exp2_top
The maximal response on the resulting Exponential 2 model fit
- exp2_ac50
Concentration at 50% of the maximal response on the Exponential 2 model fit
- exp3_success
Success indicator for the Exponential 3 model; 1 if the optimization was successful, otherwise 0
- exp3_aic
Akaike Information Criteria (AIC) for the Exponential 3 model
- exp3_cov
Success indicator for the Exponential 3 model covariance calculation; 1 if the Hessian matrix inversion is successful, otherwise 0
- exp3_rme
Root mean square erro for the Exponential 3 model
- exp3_a
The y-scale parameter for the Exponential 3 model
- exp3_b
The x-scale parameter for the Exponential 3 model
- exp3_p
The power parameter for the Exponential 3 model
- exp3_er
Error term for the Exponential 3 model
- exp3_a_sd
Standard deviation of the Exponential 3 model y-scale parameter
- exp3_b_sd
Standard deviation of the Exponential 3 model x-scale parameter
- exp3_p_sd
Standard deviation of the Exponential 3 model power parameter
- exp3_er_sd
Standard deviation of the Exponential 3 model error term
- exp3_top
The maximal response on the resulting Exponential 3 model fit
- exp3_ac50
Concentration at 50% of the maximal response on the Exponential 3 model fit
- exp4_success
Success indicator for the Exponential 4 model; 1 if the optimization was successful, otherwise 0
- exp4_aic
Akaike Information Criteria (AIC) for the Exponential 4 model
- exp4_cov
Success indicator for the Exponential 4 model covariance calculation; 1 if the Hessian matrix inversion is successful, otherwise 0
- exp4_rme
Root mean square erro for the Exponential 4 model
- exp4_tp
The top parameter indicating the maximal estimated response
- exp4_ga
The gain parameter for the Exponential 4 model, gain AC50
- exp4_er
Error term for the Exponential 4 model
- exp4_tp_sd
Standard deviation of the Exponential 4 model top parameter
- exp4_ga_sd
Standard deviation of the Exponential 4 model gain parameter
- exp4_er_sd
Standard deviation of the Exponential 4 model error term
- exp4_top
The maximal response on the resulting Exponential 4 model fit
- exp4_ac50
Concentration at 50% of the maximal response on the Exponential 4 model fit
- exp5_success
Success indicator for the Exponential 5 model; 1 if the optimization was successful, otherwise 0
- exp5_aic
Akaike Information Criteria (AIC) for the Exponential 5 model
- exp5_cov
Success indicator for the Exponential 5 model covariance calculation; 1 if the Hessian matrix inversion is successful, otherwise 0
- exp5_rme
Root mean square erro for the Exponential 5 model
- exp5_tp
The top parameter indicating the maximal estimated response
- exp5_ga
The gain parameter for the Exponential 5 model, gain AC50
- exp5_p
The power parameter for the Exponential 5 model
- exp5_er
Error term for the Exponential 5 model
- exp5_tp_sd
Standard deviation of the Exponential 5 model top parameter
- exp5_ga_sd
Standard deviation of the Exponential 5 model gain parameter
- exp5_p_sd
Standard deviation of the Exponential 5 model power parameter
- exp5_er_sd
Standard deviation of the Exponential 5 model error term
- exp5_top
The maximal response on the resulting Exponential 5 model fit
- exp5_ac50
Concentration at 50% of the maximal response on the Exponential 5 model fit
- all_onesd
Standard deviation of the baseline response for all models
- all_bmed
Median noise estimation of the baseline response for all models
- resp_unit
Response Units
- conc_unit
Concentration Units
-
mc5 A data frame with 5 rows and 54 columns containing level 5 best curve-fit and hitcall data.
- spid
Sample ID
- chid
Unique chemical ID number for tcpl
- casn
Chemical Abstract Service(CAS) number
- chnm
Chemical name
- dsstox_substance_id
Chemical-specific DTXSID
- code
CAS number compressed into numeric string
- aeid
Assay Component Endpoint ID
- aenm
Assay endpoint name (i.e., assay_component_endpoint_name)
- m5id
Level 5 (mc5) ID
- m4id
Level 4 (mc4) ID
- bmad
The median absolute deviation of all treatment wells (default option) or blank wells
- resp_max
Maximum observed response
- resp_min
Minimum observed response
- max_mean
Maximum mean response
- max_mean_conc
Concentration of the maximum mean response
- max_med
Maximum median response
- max_med_conc
Concentration of the maximum median response
- logc_max
Maximum concentration on the log scale
- logc_min
Minimum concentration on the log scale
- nconc
The total number of concentration groups
- npts
Total number of observed responses (i.e. data points in the concentration series)
- nrep
Number of replicates in concentration groups
- nmed_gtbl
The number of median responses greater than 3BMAD
- hitc
Hitcall
- modl
Best model fit from tcplFit2 curve-fitting
- fitc
Fit category
- coff
Cutoff
- top_over_cutoff
Ratio of the top of the best model fit curve and the cutoff
- rmse
Root mean squared error
- a
The y-scale parameter for poly1, poly2, pow, exp2, or exp3 model
- er
Error term
- bmr
Benchmark response
- bmdl
Lower 95% confidence bound on the benchmark dose/concentration estimate
- caikwt
Akaike Information Criteria weight of constant model relative to the best model fit
- mll
Maximum log-likelihood of the best model fit
- hitcall
Continuous hitcall
- ac50
Concentration where 50% of the maximal response occurs - if 'modl' is the Hill or Gain-loss model this is for the "gain" side of the response
- top
The maximal response on the best model curve fit - i.e. top of the curve fit
- ac5
Concentration where 5% of the maximal response occurs
- ac10
Concentration where 10% of the maximal response occurs
- ac20
Concentration where 20% of the maximal response occurs
- acc
Concentration where the efficacy cutoff response occurs
- ac1sd
Concentration where one standard deviation of the background response occurs
- bmd
Benchmark response/concentration estimate - concentration where the benchmark response occurs
- bmdu
Upper 95% confidence bound on the benchmark dose/concentration estimate
- tp
The top curve parameter for the exp4, exp5, hill, or gnls model
- ga
The gain parameter for the hill or gnls model - gain AC50
- p
The power parameter for the pow, exp3, exp5, gnls, or hill model - for gnls this is the gain power parameter
- q
The loss power parameter for the gnls model
- la
The loss parameter for the gnls model, loss AC50
- ac50_loss
Concentration where 50% of the maximal response occurs - if 'modl' is the Hill or Gain-loss model this is for the "loss" side of the response
- b
The x-scale parameter for poly2, exp2, or exp3 model
- resp_unit
Response Units
- conc_unit
Concentration Units