Showing 5 of total 5 results (show query)
bioc
RcisTarget:RcisTarget Identify transcription factor binding motifs enriched on a list of genes or genomic regions
RcisTarget identifies transcription factor binding motifs (TFBS) over-represented on a gene list. In a first step, RcisTarget selects DNA motifs that are significantly over-represented in the surroundings of the transcription start site (TSS) of the genes in the gene-set. This is achieved by using a database that contains genome-wide cross-species rankings for each motif. The motifs that are then annotated to TFs and those that have a high Normalized Enrichment Score (NES) are retained. Finally, for each motif and gene-set, RcisTarget predicts the candidate target genes (i.e. genes in the gene-set that are ranked above the leading edge).
Maintained by Gert Hulselmans. Last updated 5 months ago.
generegulationmotifannotationtranscriptomicstranscriptiongenesetenrichmentgenetarget
37 stars 9.18 score 191 scripts
winvector
sigr:Succinct and Correct Statistical Summaries for Reports
Succinctly and correctly format statistical summaries of various models and tests (F-test, Chi-Sq-test, Fisher-test, T-test, and rank-significance). This package also includes empirical tests, such as Monte Carlo and bootstrap distribution estimates.
Maintained by John Mount. Last updated 2 years ago.
28 stars 7.18 score 97 scripts 1 dependentsbioc
puma:Propagating Uncertainty in Microarray Analysis(including Affymetrix tranditional 3' arrays and exon arrays and Human Transcriptome Array 2.0)
Most analyses of Affymetrix GeneChip data (including tranditional 3' arrays and exon arrays and Human Transcriptome Array 2.0) are based on point estimates of expression levels and ignore the uncertainty of such estimates. By propagating uncertainty to downstream analyses we can improve results from microarray analyses. For the first time, the puma package makes a suite of uncertainty propagation methods available to a general audience. In additon to calculte gene expression from Affymetrix 3' arrays, puma also provides methods to process exon arrays and produces gene and isoform expression for alternative splicing study. puma also offers improvements in terms of scope and speed of execution over previously available uncertainty propagation methods. Included are summarisation, differential expression detection, clustering and PCA methods, together with useful plotting functions.
Maintained by Xuejun Liu. Last updated 10 days ago.
microarrayonechannelpreprocessingdifferentialexpressionclusteringexonarraygeneexpressionmrnamicroarraychiponchipalternativesplicingdifferentialsplicingbayesiantwochanneldataimporthta2.0
4.71 score 17 scripts
andreamrau
ebdbNet:Empirical Bayes Estimation of Dynamic Bayesian Networks
Infer the adjacency matrix of a network from time course data using an empirical Bayes estimation procedure based on Dynamic Bayesian Networks.
Maintained by Andrea Rau. Last updated 2 years ago.
4 stars 4.28 score 19 scripts
michlau
logicDT:Identifying Interactions Between Binary Predictors
A statistical learning method that tries to find the best set of predictors and interactions between predictors for modeling binary or quantitative response data in a decision tree. Several search algorithms and ensembling techniques are implemented allowing for finetuning the method to the specific problem. Interactions with quantitative covariables can be properly taken into account by fitting local regression models. Moreover, a variable importance measure for assessing marginal and interaction effects is provided. Implements the procedures proposed by Lau et al. (2024, <doi:10.1007/s10994-023-06488-6>).
Maintained by Michael Lau. Last updated 6 months ago.
2 stars 2.00 score 2 scripts