bioMate-AI/biomate-bioconductor-kb

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

This package provides a collection of functions designed for analyzing deconvolution of the bulk sample(s) using an atlas of reference omic signature profiles and a user-selected model. Users are given the option to create or extend a reference atlas and,also simulate the desired size of the bulk signature profile of…

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

Uses DESeq2 to estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution.

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

Intuitive framework for identifying spatially variable genes (SVGs) via edgeR, a popular method for performing differential expression analyses. Based on pre-annotated spatial clusters as summarized spatial information, DESpace models gene expression using a negative binomial (NB), via edgeR, with spatial clusters as…

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

Perform a complete gene expression meta-analysis workflow including data preparation, annotation harmonization, log transformation, heterogeneity testing, optional imputation, meta-analysis, and heatmap visualization.

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

Dino normalizes single-cell, mRNA sequencing data to correct for technical variation, particularly sequencing depth, prior to downstream analysis. The approach produces a matrix of corrected expression for which the dependency between sequencing depth and the full distribution of normalized expression; many existing…

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

The filtering uses intelligent methods to generate output 10X matrices as would be otherwise generated by CellRanger. The ranking option serves to illustrate the number of detected barcodes in the sample.

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

This package provides a workflow for the use of EaSIeR tool, developed to assess patients' likelihood to respond to ICB therapies providing just the patients' RNA-seq data as input. We integrate RNA-seq data with different types of prior knowledge to extract quantitative descriptors of the tumor microenvironment from…

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

Estimates differential gene expression for short read sequence count using methods appropriate for count data. If you have paired data you may also want to consider Tophat/Cufflinks. Input must be raw count data for each sequence arranged i.

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

Volcano plots represent a useful way to visualise the results of differential expression analyses. Here, we present a highly-configurable function that produces publication-ready volcano plots. EnhancedVolcano will attempt to fit as many po.

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

The epistack package main objective is the visualizations of stacks of genomic tracks (such as, but not restricted to, ChIP-seq, ATAC-seq, DNA methyation or genomic conservation data) centered at genomic regions of interest. epistack needs three different inputs: 1) a genomic score objects, such as ChIP-seq coverage…

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

The creation of effective visualizations is a fundamental component of data analysis. In biomedical research, new challenges are emerging to visualize multi-dimensional data in a 2D space, but current data visualization tools have limited capabilities. To address this problem, we leverage Gestalt principles to improve…

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

A tabular file with gene symbols in the first column, and a ranked statistic (e.g. t-statistic or log fold-change) in the second column.

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

This package implements functions to find influential TF and target based on different input type. It have five module: Multi-peak multi-gene annotaion(mmPeakAnno module), Calculate regulation potential(calcRP module), Find influential Target based on ChIP-Seq and RNA-Seq data(Find influential Target module), Find…

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

This package implements a metabolic network analysis pipeline to identify an active metabolic module based on high throughput data. The pipeline takes as input transcriptional and/or metabolic data and finds a metabolic subnetwork (module) most regulated between the two conditions of interest. The package further…

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

This package contain functions to run genomic instability analysis (GIA) from scRNA-Seq data. GIA estimates the association between gene expression and genomic location of the coding genes. It uses the aREA algorithm to quantify the enrichment of sets of contiguous genes (loci-blocks) on the gene expression profiles…

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

Connect new gene expression profile with the relevant information from the existing databases, such as previous publications, MeSH terms, and gene sets.

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

This tool fetches microarray data directly from GEO database, based on the GEOQuery R package. Given a GSE accession ID, it returns an Rdata object containing the data and a text file (.cond file) summarizing the conditions of the experimen.

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

Gene Expression Omnibus(GEO) and The Cancer Genome Atlas (TCGA) provide us with a wealth of data, such as RNA-seq, DNA Methylation, SNP and Copy number variation data. It's easy to download data from TCGA using the gdc tool, but processing these data into a format suitable for bioinformatics analysis requires more…

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

Fit linear models to overdispersed count data. The package can estimate the overdispersion and fit repeated models for matrix input. It is designed to handle large input datasets as they typically occur in single cell RNA-seq experiments.

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

Deconvolute bulk RNA-seq data using multiple reference profiles and benchmark the results against ground truth cell type proportions.

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

This package provides classes and methods to support Gene Set Enrichment Analysis (GSEA).

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

Gene Set Variation Analysis (GSVA) is a non-parametric, unsupervised method for estimating variation of gene set enrichment through the samples of a expression data set. GSVA performs a change in coordinate systems, transforming the data fr.

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

An implementation, which takes input data and makes it available for proper batch effect removal by ComBat or Limma. The implementation appropriately handles missing values by dissecting the input matrix into smaller matrices with sufficient data to feed the ComBat or limma algorithm. The adjusted data is returned to…

bioMate-AI/biomate-bioconductor-kb

Skill Claude Code

Tools for parsing Illumina's microarray output files, including IDAT.