| reduceReplicates {dMod} | R Documentation |
Reduce replicated measurements to mean and standard deviation
Description
Obtain the mean and standard deviation from replicates per condition.
Usage
reduceReplicates(file, select = "condition", datatrans = NULL)
Arguments
file |
Data file of csv. See Format for details. |
select |
Names of the columns in the data file used to define conditions, see Details. |
datatrans |
Character vector describing a function to transform data. Use x to refere to data. |
Format
The following columns are mandatory for the data file.
- name
Name of the observed species.
- time
Measurement time point.
- value
Measurement value.
- condition
The condition under which the observation was made.
In addition to these columns, any number of columns can follow to allow a fine grained definition of conditions. The values of all columns named in select are then merged to get the set of conditions.
Details
Experiments are usually repeated multiple times possibly under different conditions leading to replicted measurements. The column "Condition" in the data allows to group the data by their condition. However, sometimes, a more fine grained grouping is desirable. In this case, any number of additional columns can be append to the data. These columns are referred to as "condition identifier". Which of the condition identifiers are used to do the grouping is user defined by anouncing the to select. The mandatory column "Condition" is always used. The total set of different conditions is thus defined by all combinations of values occuring in the selected condition identifiers. The replicates of each condition are then reduced to mean and variance.New conditions names are derived by merging all conditions which were used in mean and std.
Value
A data frame of the following variables
- time
Measurement time point.
- name
Name of the observed species.
- value
Mean of replicates.
- sigma
Standard error of the mean, NA for single measurements.
- n
The number of replicates reduced.
- condition
The condition for which the value and sigma were calculated. If more than one column were used to define the condition, this variable holds the effecive condition which is the combination of all applied single conditions.
Author(s)
Wolfgang Mader, Wolfgang.Mader@fdm.uni-freiburg.de