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pcamasigpro [2010/03/10 14:12]
mjnueda
pcamasigpro [2014/05/12 12:42] (current)
jcarbonell
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 __Parameters for //​PCA-maSigFun gene selection//​__:​ __Parameters for //​PCA-maSigFun gene selection//​__:​
    ​*//​Data//:​ txt file with expression data, genes in rows, arrays in columns. The file must contain an additional row with arrays names and a column with gene names.\\    ​*//​Data//:​ txt file with expression data, genes in rows, arrays in columns. The file must contain an additional row with arrays names and a column with gene names.\\
 +\\
 +|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|…|
 +|gene2|0.5|0.3|0.4|0.3|0.4|0.1|0.1|0.4|0.5|…|
 +|...|...|...|...|...|...|...|...|...|...|…|
 +\\
    ​*//​Covariates//:​ txt file with experimental design information,​ containing as many columns as arrays and as many rows as experimental factor. Each cell contains the value of the array in the experimental factor. E.g:    ​*//​Covariates//:​ txt file with experimental design information,​ containing as many columns as arrays and as many rows as experimental factor. Each cell contains the value of the array in the experimental factor. E.g:
 \\ \\
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    ​*//​Alpha//:​ significant level for gene selection.\\    ​*//​Alpha//:​ significant level for gene selection.\\
    ​*//​R-Squared cut-off//: required level of the goodness of fit of the regression model. This parameter is between 0 and 1. Higher values indicate well fitted models. We recommend values between [0.4,0.8]. \\    ​*//​R-Squared cut-off//: required level of the goodness of fit of the regression model. This parameter is between 0 and 1. Higher values indicate well fitted models. We recommend values between [0.4,0.8]. \\
-   ​*//​Cut-off ​(0-1)//: Variability level to select Principal Components in each category.+   ​*//​Cut-off//:​ Variability level to select Principal Components in each category.
    ​*//​Selection factor//: ​ criterion to select components can be:    ​*//​Selection factor//: ​ criterion to select components can be:
-      * Proportion of acumulated variability. +      * Proportion of acumulated variability. Posible cut-off values are in (0,1)
-      * Proportion of variability of that PC.+      * Proportion of variability of each PC. Posible cut-off values are in (0,1). 
 +      * Average: components are selected that explain more than "​cut-off"​ times the average component variability. The recommended "​cut-off"​ values are in [1,1.5].
    \\    \\
 __Parameters for //​PCA-maSigFun visualization//​__\\ __Parameters for //​PCA-maSigFun visualization//​__\\
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 by applying several procedures: by applying several procedures:
    ​*//​Resampling//:​ where a null Leverage distribution is created by permuting columns of expression data and genes are selected at the "​alpha"​ percentile of the null distribution.    ​*//​Resampling//:​ where a null Leverage distribution is created by permuting columns of expression data and genes are selected at the "​alpha"​ percentile of the null distribution.
-   ​*//​minAS//:​ where a density function is calculated on the data and genes are selected on a local minimum basis. +   ​*//​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 the gene loadings, and genes are selected at the "​alpha"​ percentile of the gamma distribution. ​+   ​*//​Gamma//:​ where a gamma distribution is adjusted to the distributions of the gene loadings, and genes are selected at the "​alpha"​ percentile of the gamma distribution ​[[references |[7]]]
    ​*//​Custom//:​ where the user can decide the threshold.    ​*//​Custom//:​ where the user can decide the threshold.
 \\ \\
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pcamasigpro.1268226722.txt.gz · Last modified: 2010/03/10 14:12 by mjnueda
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