getexpdata: Get data of NTB experiments in customized format
In volkmannp/ntbgraphics: Visualization of NTB Data

Description Usage Arguments Value Author(s) Examples

View source: R/getexpdata.R

A function that imports an NTB dataset and prepares the data for plotting and analysis as dataframe or matrix. For right formatting of your files, please consider the "ReadMe for ntbgraphics".

getexpdata(
  directory,
  analysis = c("2arm_ko", "2arm_tg", "2arm_sd", "2arm_treat", "4arm_sd_ko",
    "4arm_sd_tg", "4arm_treat_ko", "4arm_treat_tg"),
  ordercolumns = c("ntb", "rdoc", "manual"),
  ordercolumns_manual = FALSE,
  exclude.animals = FALSE,
  orderlevelcond = c("other", "gtblock", "etblock", "2rev"),
  acceptable.nas = "unlimited",
  return.matrix = FALSE,
  return.matrix.mean = FALSE,
  healthy_norm = FALSE,
  naomit = FALSE,
  directional = FALSE,
  absoluteval = FALSE
)

`directory`	specifies file directory of 'Meta Behavior' and 'Animal List' files within quotation marks (mind correct spelling of both files and 'directory'!); no default
`analysis`	specifies the kind of experiment performed within quotation marks; "2arm_ko","2arm_tg", "2arm_sd", "2arm_treat", "4arm_sd_ko", "4arm_sd_tg", "4arm_treat_ko", "4arm_treat_tg" (tg for transgenic, ko for knockout; 4arm_sd_x assumes a stress paradigm with social defeat (sd) and housing or handling control (hc) as control; 4arm_treat_x assumes a treatment paradigm with treated (treat) and untreated (untreat) animals; 2arm_x assumes wildtype controls (wt) for tg and ko, housing or handling controls (hc) for sd and untreated controls (untreat) for treated animals; ('analysis' defines the kind of experiment performed, respectively the kind of analysis preferred - you can easily perform 2arm analysis for 4arm experiments looking only at the groups of interest, but not the other way around); default: "2arm_ko"
`ordercolumns`	defines the order paradigm of experiment column appearance in final table within quotation marks: "ntb", "rdoc", "manual"; RFID and Condition are always listed first and need no specification; order of experiments may be chronological with "ntb", follow RDoC clustering with "rdoc" or be customized manually with "manual" (-> use 'ordercolumns_manual' for exact appearance; there, you may also choose to exclude experiments); default: "ntb"
`ordercolumns_manual`	customizes order of appearance and appearance itself of experiment columns in final table (experiments that are not listed will not be included); only if 'ordercolumns' = "manual"; user has to provide a vector containing characters within quotation marks (e.g. by using c("Meanspeed", "SerialLearn")) with all experiments he wants to include into the final tabel with desired order; no need for specification if 'ordercolumns' is not "manual" default: FALSE
`exclude.animals`	excluding animals from analysis by RFID; user has to provide a vector containing characters within quotation marks (e.g. by using c("900200000067229", "900200000065167")) with all animals he wants to exclude from the final table; if FALSE is provided, no animal will be excluded; default: FALSE
`orderlevelcond`	defines order of factor levels of conditions within quotation marks: "other", "gtblock", "etblock", "2rev"; (might be important when it comes to plotting or displaying your data grouped by condition in a defined order): "other" for alphabetical order in case of 4arm; also for default order of 2arm experiments (which lists the 'control' first, then the 'condition'); "gtblock" for order wt_x, wt_y, tg_x, tg_y; "etblock" for order x_hc, y_hc, x_sd, y_sd; "2rev" for inverse order of 2arm default only, meaning listing the 'condition' first, then the 'control'; default: "other"
`acceptable.nas`	defines the maximum number of NAs allowed within the same row; if number of actual NAs within one row is bigger than the number provided, the row will be excluded from table and following analyses; if the number of acceptable NAs should be unlimited, no value has to be provided; default: "unlimited"
`return.matrix`	boolean that defines if the standard dataframe or a z-scored matrix should be provided; by default, getexpdata generates a dataframe containing raw joined animal and experiment information; 'return.matrix' can further process the dataframe with customizable functions to return a z-scored matrix, for e.g. heatmapping, pca and tsne; default: FALSE
`healthy_norm`	boolean that specifies if mean matrix should be normalized to healthy controls by subtracting all values by the healthy controls; only if return.matrix and return.matrix.mean are TRUE; not possible for 2arm experiments; default: FALSE
`naomit`	boolean that specifies if each columns with any number of NAs bigger than 0 should be excluded; only applied and useful if 'return.matrix' is TRUE; may appear redundant concerning earlier listed 'acceptable.nas', but gives user the opportunity, to save settings within function with different needs for dataframe and (probably later needed) matrix; default: FALSE
`directional`	specifies which directionality paradigm should be applied; several options are available, manual specification is also possible; if "rdoc" within quotation marks is provided, columns 'Rotations', 'FreezeBase', 'Timeimmobile', 'Baseline', 'Activity', 'Choices' and 'Meanspeed' are multiplied by -1; if "emptcf4" within quotation marks is provided, columns 'Center', 'Choices' and 'Meanspeed' are multiplied by -1; you may alternatively provide a vector containing characters within quotation marks (e.g. by using c("Nocturnal", "inhibition75")) with all columns you wants to have multiplied by -1; only applied if 'return.matrix' is TRUE and only useful if 'absoluteval' is FALSE; default: FALSE
`absoluteval`	boolean that specifies if only absolute values of z-scored matrix should be given; only applied and useful if 'return.matrix' is TRUE; default: FALSE
`return.matrix, mean`	boolean that specifies if matrix should only contain the mean of each group for each experiment; grouping follows specification of groups to be analyzed as defined by 'analysis'; only useful if 'return.matrix' is TRUE; default: FALSE

prepared and joined dataframe of all animals and corresponding NTB experiments or customized z-scored matrix

Paul Volkmann

getexpdata(directory = paste0(system.file("extdata", package = "ntbgraphics", mustWork = T),"/"))

getexpdata(directory = paste0(system.file("extdata", package = "ntbgraphics", mustWork = T),"/"), 
                   analysis = "2arm_sd", 
                   ordercolumns = "manual", 
                   ordercolumns_manual = c("Meanspeed", "SerialLearn", "Center"), 
                   exclude.animals = c("900200000070142"), 
                   orderlevelcond = "2rev", 
                   acceptable.nas = 3, 
                   return.matrix = TRUE, 
                   naomit = TRUE, 
                   directional = "emptcf4")