Enter the query into the form above. You can look for specific version of a package by using @ symbol like this: gcc@10.
API method:
GET /api/packages?search=hello&page=1&limit=20
where search is your query, page is a page number and limit is a number of items on a single page. Pagination information (such as a number of pages and etc) is returned
in response headers.
If you'd like to join our channel webring send a patch to ~whereiseveryone/toys@lists.sr.ht adding your channel as an entry in channels.scm.
Platform Design Info for Affymetrix AraGene-1_1-st.
Platform Design Info for Affymetrix RabGene-1_0-st.
PWMEnrich pre-compiled background objects for M.musculus (mouse) and MotifDb M. musculus motifs.
Platform Design Info for The Manufacturer's Name HT_HG-U133A.
Platform Design Info for The Manufacturer's Name E_coli_2.
Package for the position related analysis of quantitative functional genomics data.
Store UCSC phyloP mm39 conservation scores AnnotationHub Resource Metadata. Provide provenance and citation information for UCSC phyloP mm39 conservation score AnnotationHub resources. Illustrate in a vignette how to access those resources.
Platform Design Info for The Manufacturer's Name NuGO_Mm1a520177.
PAA imports single color (protein) microarray data that has been saved in gpr file format - esp. ProtoArray data. After preprocessing (background correction, batch filtering, normalization) univariate feature preselection is performed (e.g., using the "minimum M statistic" approach - hereinafter referred to as "mMs"). Subsequently, a multivariate feature selection is conducted to discover biomarker candidates. Therefore, either a frequency-based backwards elimination aproach or ensemble feature selection can be used. PAA provides a complete toolbox of analysis tools including several different plots for results examination and evaluation.
Platform Design Info for The Manufacturer's Name HT_MG-430A.
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 Porcine\_probe\_tab.
Platform Design Info for NimbleGen feinberg_mm8_me_hx1.
Platform Design Info for Affymetrix RaGene-1_1-st-v1.
Platform Design Info for Affymetrix Atdschip_tiling.
Platform Design Info for The Manufacturer's Name wheat.
Platform Design Info for The Manufacturer's Name RG_U34C.
This package provides a package containing an environment representing the Plasmodium_Anopheles.cdf file.
Platform Design Info for NimbleGen 081229_hg18_promoter_medip_hx1.
This package provides visualization of the results from the multiple (i.e. pairwise) comparison tests such as pairwise.t.test, pairwise.prop.test or pairwise.wilcox.test. The groups being compared are visualized as nodes in Hasse diagram. Such approach enables very clear and vivid depiction of which group is significantly greater than which others, especially if comparing a large number of groups.
Platform Design Info for Affymetrix SoyGene-1_1-st.
Phenotypes comparison based on a pathway consensus approach. Assess the relationship between candidate genes and a set of phenotypes based on additional genes related to the candidate (e.g. Pathways or network neighbors).
PaIRKAT is model framework for assessing statistical relationships between networks of metabolites (pathways) and an outcome of interest (phenotype). PaIRKAT queries the KEGG database to determine interactions between metabolites from which network connectivity is constructed. This model framework improves testing power on high dimensional data by including graph topography in the kernel machine regression setting. Studies on high dimensional data can struggle to include the complex relationships between variables. The semi-parametric kernel machine regression model is a powerful tool for capturing these types of relationships. They provide a framework for testing for relationships between outcomes of interest and high dimensional data such as metabolomic, genomic, or proteomic pathways. PaIRKAT uses known biological connections between high dimensional variables by representing them as edges of ‘graphs’ or ‘networks.’ It is common for nodes (e.g. metabolites) to be disconnected from all others within the graph, which leads to meaningful decreases in testing power whether or not the graph information is included. We include a graph regularization or ‘smoothing’ approach for managing this issue.
Most human genes have multiple promoters that control the expression of different isoforms. The use of these alternative promoters enables the regulation of isoform expression pre-transcriptionally. Alternative promoters have been found to be important in a wide number of cell types and diseases. proActiv is an R package that enables the analysis of promoters from RNA-seq data. proActiv uses aligned reads as input, and generates counts and normalized promoter activity estimates for each annotated promoter. In particular, proActiv accepts junction files from TopHat2 or STAR or BAM files as inputs. These estimates can then be used to identify which promoter is active, which promoter is inactive, and which promoters change their activity across conditions. proActiv also allows visualization of promoter activity across conditions.
Platform Design Info for The Manufacturer's Name Hu6800.