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ascagenes [2010/02/28 16:08] aconesa |
ascagenes [2014/05/12 12:37] jcarbonell |
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| __Parameters__: | __Parameters__: | ||
| *//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.\\ | ||
| - | \\ | + | Example:\\ |
| - | |Name|Array|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|…| | ||
| |...|...|...|...|...|...|...|...|...|...|…| | |...|...|...|...|...|...|...|...|...|...|…| | ||
| - | *//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.\\ |
| - | \\ | + | Example:\\ |
| |Time|3|3|3|9|9|9|27|27|27|…| | |Time|3|3|3|9|9|9|27|27|27|…| | ||
| |Treatment|Ctr|TrA|TrB|Ctr|TrA|TrB|Ctr|TrA|TrB|…| | |Treatment|Ctr|TrA|TrB|Ctr|TrA|TrB|Ctr|TrA|TrB|…| | ||
| - | * //Join//: logical to indicate whether serial transcriptional changes should include time-zero non-null values (TRUE, default) or not (FALSE).\\ | + | * //Include interaction between factors//: logical to indicate whether interaction/s between factors should be analyzed (only for experimental designs with more than one factor).\\ |
| - | * //Interaction//: logical to indicate whether interactions between factors should be analyzed.\\ | + | * //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//: average" to explain more than the average variation of the principal components. A specific variation can be also indicated as 0.75 or 0.80...\\ | + | * //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...\\ |
| - | *//alpha//: significant level for gene selection.\\ | + | * //Criterion for gene selection//. Strategy for selection of genes based on SPE and leverage values. Can be either |
| - | *//R//: number of bootstrap rounds for gene selection.\\ | + | * //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]]]. |
| - | // | + | * //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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