View source: R/subset_metaanalysis.R
| find_gene_statistics | R Documentation | 
For each gene retrieve mean, median, and standard deviation of the log2FC and the number of times it is ecountered differentially expressed in the various comparisons.
find_gene_statistics(dataset, genes = NULL, top = NULL)
dataset | 
 list of 3 lists, the first with gene IDs (called   | 
genes | 
 vector of gene names. Limit the results only to the elements of   | 
top | 
 integer. Limit the results to the top number of genes with the highest occurence in the dataset. Cannot be set together with   | 
a dataframe with 6 columns and as many rows as genes. The column names reports the gene names used in the dataset. occurences indicates the number of times a gene is found differentially expressed. median_log2FC, mean_log2FC and sd_log2FC: median, mean, and standard deviations of all the log2 fold changes in which the gene is encountered across the comparisons. pseudotscore: this statistics is calculated as mean_log2FC/(sd_log2FC/sqrt(occurences)). Genes with a high pseudo-t-score have high absolute fold change that does not vary across comparisons and are found differentially expressed in a relatively high number of comparisons.
# create a list of lists were only the first 500 most significant genes with adjusted p-value < 0.05 and fold change >1.5 or < -1.5 are included
data(list_array) #load data
list_array.05_fc1.5_max500 <- subset_metanalysis(dataset=list_array, adjpval = 0.05, abslog2FC = log2(1.5), max_n_genes = 500 )
#retrieve the statistics for the most frequent 500 DE genes
find_gene_statistics(dataset=list_array.05_fc1.5_max500, top=500)
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