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ascagenes [2010/03/09 13:06]
mjnueda
ascagenes [2014/05/12 12:37] (current)
jcarbonell
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 Example:\\ Example:\\
 |Name|Array1|Array2|Array3|Array4|Array5|Array6|Array7|Array8|Array9|…| |Name|Array1|Array2|Array3|Array4|Array5|Array6|Array7|Array8|Array9|…|
-|gene1|0.5|0.2|0.7|1.3|1.4|1.0|2.1|2.4|2.6|….+|gene1|0.5|0.2|0.7|1.3|1.4|1.0|2.1|2.4|2.6|…|
 |gene2|0.5|0.3|0.4|0.3|0.4|0.1|0.1|0.4|0.5|…| |gene2|0.5|0.3|0.4|0.3|0.4|0.1|0.1|0.4|0.5|…|
 |...|...|...|...|...|...|...|...|...|...|…| |...|...|...|...|...|...|...|...|...|...|…|
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 |Treatment|Ctr|TrA|TrB|Ctr|TrA|TrB|Ctr|TrA|TrB|…| |Treatment|Ctr|TrA|TrB|Ctr|TrA|TrB|Ctr|TrA|TrB|…|
  
-   * //Include interaction between factors//: logical to indicate whether ​interactions ​between factors should be analyzed (only for experimental designs with more than one factor).\\+   * //Include interaction between factors//: logical to indicate whether ​interaction/​s ​between factors should be analyzed (only for experimental designs with more than one factor).\\
    * //Join interaction with second factor//: logical to indicate whether interaction/​s must be analysed jointly with the second/​third factor (TRUE, default) or not (FALSE).\\    * //Join interaction with second factor//: logical to indicate whether interaction/​s must be analysed jointly with the second/​third factor (TRUE, default) or not (FALSE).\\
    * //​Variability threshold for component selection//:​ Criterion for selection of principal components. With "​average",​ components are selected that explain more than the average component variability,​ calculated as total data variability divided by the rank of the matrix associated to the factor. Also a fixed value for percentage of explained variability can be indicated such as 0.2, 0.4, 0.5, 0.7, 0.8...\\    * //​Variability threshold for component selection//:​ Criterion for selection of principal components. With "​average",​ components are selected that explain more than the average component variability,​ calculated as total data variability divided by the rank of the matrix associated to the factor. Also a fixed value for percentage of explained variability can be indicated such as 0.2, 0.4, 0.5, 0.7, 0.8...\\
-   * //Criterion for gene selection//​. Strategy for selection of genes based on SPE and leverage values. Can be either ​"Resampling", ​where null SPE/Leverage ​distributions are created by permuting columns and genes are selected at the "​alpha"​ percentile of the null distributions;​ "​Gamma",​ where a gamma distribution is adjusted ​to the distributions of SPE and leverage values, and genes are selected at the "​alpha"​ percentile of the gamma distribution. ​"minAS", ​where a density function is calculated on the data and genes are selected on a local minimum basis +   * //Criterion for gene selection//​. Strategy for selection of genes based on SPE and leverage values. Can be either ​ 
-       *//alpha//: significant level for gene selection (only for Resampling ​and Gamma).\\ +       * //Resampling//: where null Leverage ​distribution is created by permuting columns ​of expression data and genes are selected at the "​alpha"​ percentile of the null distribution ​and SPE cutoff ​is computed by using an approximation ​to a weighted chi-squared ​distribution ​[[references|[2]]]. 
-       *//R//: number of bootstrap rounds for gene selection (only for Resampling)\\+       * //minAS//: where a density function is calculated on the data and genes are selected on a local minimum basis [[references|[7]]]. 
 +       * //Gamma//: where a gamma distribution is adjusted to the distributions of SPE and leverage values, and genes are selected at the "​alpha"​ percentile of the gamma distribution [[references|[7]]].  
 +        
 +   
 \\ \\
  
ascagenes.1268136407.txt.gz · Last modified: 2010/03/09 13:06 by mjnueda
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