Description Usage Arguments Details Value Note Author(s) References See Also
This function generates two .csv
files which descibe how samples are allocated
samples into different conditions and paired on arrays.
1 2 3 | experimentDesignTable( array.allocation, condition.allocation,
nEnvFactors, nLevels, Level, fileName,envFactorNames,
directory )
|
array.allocation |
matrix with nArray rows and nRIL columns. Elements of 1/0 indicate this RIL is/not selected for this array. |
condition.allocation |
matrix with nCondition rows and nRIL columns. Elements of 1/0 indicate this RIL is/not selected for this condition. |
nEnvFactors |
number of environmental factors, an integer bewteen 1 and 3.
When |
nLevels |
number of levels for each factor, a vector with each
component being integer. The length of it should equal
|
Level |
a list which specifies the levels for each factor in the
experiment. There are in total |
fileName |
the final optimal design table(s) in |
envFactorNames |
a vector with names for all environmental factor(s). For example, for the
experiment with two environmental factors of temperature and drug treatment:
|
directory |
It tells where the resulting optimal design tables are to be stored.
If |
Based on nEnvFactors
and nLevels
, nConditions
is calculated.
Two tables report the results: table "pair design" which is only used for
two-channel experiments and describes how samples are paired together on the
slide (e.g. microarray chip), and table "envi-ronment design" which is used
when there are more environments evolved in the experiment. With these two
tables, the experimenters can set up the environmental treatment and
follow-up profiling measurement.
Examples:
1. conditionDesign.csv
Temperature | Cell Type | Selected Samples | |||||
condition1 | 15 | A | RIL28 | RIL81 | RIL18 | RIL61 | |
condition2 | 24 | A | RIL72 | RIL40 | RIL83 | RIL44 | RIL10 |
condition3 | 29 | A | RIL22 | RIL89 | RIL3 | RIL30 | RIL58 |
condition4 | 15 | B | RIL70 | RIL47 | RIL4 | RIL59 | |
condition5 | 24 | B | RIL93 | RIL97 | RIL49 | RIL14 | |
2. arrayDesign.csv
Channel 1 | Channel 2 | |
array1 | RIL28 | RIL92 |
array2 | RIL70 | RIL47 |
array3 | RIL22 | RIL89 |
array4 | RIL45 | RIL15 |
array5 | RIL52 | RIL41 |
The optimal design results are described in two tables. One is called "array design" which is only used for two-channel experiments. It describes how samples are paired together on the slide (e.g. microarray chip). The other table is called "condition design" which is used when there is more than one environmental factor involved in the experiment. Each cell in condition design table represents a combination of different levels of environmental factors and the selected sample names (e.g. RIL names) for this condition are shown. Based on these two tables, the experimenters can set up the environmental treatment and follow-up profiling measurement.
Yang Li <yang.li@rug.nl>, Gonzalo Vera <gonzalo.vera.rodriguez@gmail.com>
Rainer Breitling <r.breitling@rug.nl>, Ritsert Jansen <r.c.jansen@rug.nl>
Y. Li, R. Breitling and R.C. Jansen. Generalizing genetical
genomics: the added value from environmental perturbation, Trends Genet
(2008) 24:518-524.
Y. Li, M. Swertz, G. Vera, J. Fu, R. Breitling, and R.C. Jansen. designGG:
An R-package and Web tool for the optimal design of genetical genomics
experiments. BMC Bioinformatics 10:188(2009)
http://gbic.biol.rug.nl/designGG
designGG
, exampleArrayDesignTable
, exampleConditionDesignTable
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