Agilent "Mouse Genome, Whole" annotation data (chip mgug4122a) assembled using data from public repositories.

This package provides tools for meta-analysis in the presence of hierarchical (and/or sampling) dependence, including with gene expression studies.

This package provides a comprehensive tool for converting and retrieving the miRNA Name, Accession, Sequence, Version, History and Family information in different miRBase versions. It can process a huge number of miRNAs in a short time without other depends.

MODA can be used to estimate and construct condition-specific gene co-expression networks, and identify differentially expressed subnetworks as conserved or condition specific modules which are potentially associated with relevant biological processes.

This package was automatically created by package AnnotationForge version 1.11.21. The probe sequence data was obtained from http://www.affymetrix.com. The file name was MoGene-1\_0-st-v1\_probe\_tab.

MsImpute is a package for imputation of peptide intensity in proteomics experiments. It additionally contains tools for MAR/MNAR diagnosis and assessment of distortions to the probability distribution of the data post imputation. The missing values are imputed by low-rank approximation of the underlying data matrix if they are MAR (method = "v2"), by Barycenter approach if missingness is MNAR ("v2-mnar"), or by Peptide Identity Propagation (PIP).

Store minor allele frequency data from NHLBI TOPMed for the human genome version hg19.

This package produces metagene plots to compare coverages of sequencing experiments at selected groups of genomic regions. It can be used for such analyses as assessing the binding of DNA-interacting proteins at promoter regions or surveying antisense transcription over the length of a gene. The metagene2 package can manage all aspects of the analysis, from normalization of coverages to plot facetting according to experimental metadata. Bootstraping analysis is used to provide confidence intervals of per-sample mean coverages.

Two-stage measurement error model for correlation estimation with smaller bias than the usual sample correlation.

Agilent annotation data (chip mgug4120a) assembled using data from public repositories.

This package provides functions for preprocessing, automated gating and meta-analysis of cytometry data. It also provides functions that facilitate the collection of cytometry data from the ImmPort database.

Pathway analysis based on p-values associated to genes from a genes expression analysis of interest. Utility functions enable to extract pathways from the Gene Ontology Biological Process (GOBP), Molecular Function (GOMF) and Cellular Component (GOCC), Kyoto Encyclopedia of Genes of Genomes (KEGG) and Reactome databases. Methodology, and helper functions to display the results as a table, barplot of pathway significance, Gene Ontology graph and pathway significance are available.

gene target tabale of miRNA for human/mouse used for MiRaGE package.

This package was created by frmaTools version 1.19.3 and hgu133ahsentrezgcdf version 19.0.0.

Experimental data for use with the MutSeqR vignette and examples. This dataset is taken from LeBlanc et al., 2022. 24 MutaMouse animals were exposed to one of three doses of benzo[a]pyrene or a vehicle control for 28 days by oral gavage. 28 days after the end of the exposure, bone marrow of the femurs was harvested from euthanized animals. DNA extraction was conducted via DNeasy Blood and Tissue kit. DNA samples were sequenced using TwinStrand's Duplex Sequencing on the Mouse Mutagenesis Panel at > 10,000 depth. The Mouse Mutagenesis Panel comprises 20 2.4kb genomic targets with one located on each mouse autosome (two on chromosome 1). Pre-processing of sequence reads was redone since publication using an updated version of TwinStrand's Mutagenesis App (v. 3.20.1) which produced tabular mutation data files for each sample. Data contained herein are only those required for running MutSeqR examples and vignette.

An integrated pipeline to predict the potential synthetic lethality partners (SLPs) of tumour mutations, based on gene expression, mutation profiling and cell line genetic screens data. It has builtd-in support for data from cBioPortal. The primary SLPs correlating with muations in WT and compensating for the loss of function of mutations are predicted by random forest based methods (GENIE3) and Rank Products, respectively. Genetic screens are employed to identfy consensus SLPs leads to reduced cell viability when perturbed.

Perform step by step methylation analysis of Next Generation Sequencing data.

Store minor allele frequency data from the Genome Aggregation Database (gnomAD exomes release 2.1) for the human genome version hs37d5.

Raw amplification data from a large microRNA mixture / dilution study. These data are used by the miRcomp package to assess the performance of methods that estimate expression from the amplification curves.

This package provides tools for augmenting signaling pathways to perform pathway analysis of microRNA and mRNA expression levels.

Translating mature miRNA names to different miRBase versions, sequence retrieval, checking names for validity and detecting miRBase version of a given set of names (data from http://www.mirbase.org/).

This package allows to estimate chronological and gestational DNA methylation (DNAm) age as well as biological age using different methylation clocks. Chronological DNAm age (in years) : Horvath's clock, Hannum's clock, BNN, Horvath's skin+blood clock, PedBE clock and Wu's clock. Gestational DNAm age : Knight's clock, Bohlin's clock, Mayne's clock and Lee's clocks. Biological DNAm clocks : Levine's clock and Telomere Length's clock.

DNA methylation is generally considered to be associated with transcriptional silencing. However, comprehensive, genome-wide investigation of this relationship requires the evaluation of potentially millions of correlation values between the methylation of individual genomic loci and expression of associated transcripts in a relatively large numbers of samples. Methodical makes this process quick and easy while keeping a low memory footprint. It also provides a novel method for identifying regions where a number of methylation sites are consistently strongly associated with transcriptional expression. In addition, Methodical enables housing DNA methylation data from diverse sources (e.g. WGBS, RRBS and methylation arrays) with a common framework, lifting over DNA methylation data between different genome builds and creating base-resolution plots of the association between DNA methylation and transcriptional activity at transcriptional start sites.

Classification of pediatric tumors into biologically defined subtypes is challenging and multifaceted approaches are needed. For this aim, we developed a diagnostic classifier based on DNA methylation profiles. We offer MethPed as an easy-to-use toolbox that allows researchers and clinical diagnosticians to test single samples as well as large cohorts for subclass prediction of pediatric brain tumors. The current version of MethPed can classify the following tumor diagnoses/subgroups: Diffuse Intrinsic Pontine Glioma (DIPG), Ependymoma, Embryonal tumors with multilayered rosettes (ETMR), Glioblastoma (GBM), Medulloblastoma (MB) - Group 3 (MB_Gr3), Group 4 (MB_Gr3), Group WNT (MB_WNT), Group SHH (MB_SHH) and Pilocytic Astrocytoma (PiloAstro).