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ascagenes [2010/02/28 17:18] aconesa |
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 serial transcriptional changes should include time-zero non-null values (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 a 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]]]. | ||
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| - | **References** \\ | + | |
| - | Nueda, M.J.; Conesa, A.; Westerhuis, J.A.; Hoefsloot, H.C.J.; Smilde, A.K.; Talón, M. and Ferrer, A. (2007) Discovering gene expression patterns in Time Course Microarray Experiments by ANOVA-SCA. Bioinformatics, 23 (14), 1792-1800. | + | |
