Showing 5 of total 5 results (show query)
bioc
Biobase:Biobase: Base functions for Bioconductor
Functions that are needed by many other packages or which replace R functions.
Maintained by Bioconductor Package Maintainer. Last updated 5 months ago.
infrastructurebioconductor-packagecore-package
9 stars 16.46 score 6.6k scripts 1.8k dependentsbioc
MSnbase:Base Functions and Classes for Mass Spectrometry and Proteomics
MSnbase provides infrastructure for manipulation, processing and visualisation of mass spectrometry and proteomics data, ranging from raw to quantitative and annotated data.
Maintained by Laurent Gatto. Last updated 18 days ago.
immunooncologyinfrastructureproteomicsmassspectrometryqualitycontroldataimportbioconductorbioinformaticsmass-spectrometryproteomics-datavisualisationcpp
131 stars 12.76 score 772 scripts 36 dependentsbioc
Cardinal:A mass spectrometry imaging toolbox for statistical analysis
Implements statistical & computational tools for analyzing mass spectrometry imaging datasets, including methods for efficient pre-processing, spatial segmentation, and classification.
Maintained by Kylie Ariel Bemis. Last updated 3 months ago.
softwareinfrastructureproteomicslipidomicsmassspectrometryimagingmassspectrometryimmunooncologynormalizationclusteringclassificationregression
48 stars 10.32 score 200 scriptsbioc
amplican:Automated analysis of CRISPR experiments
`amplican` performs alignment of the amplicon reads, normalizes gathered data, calculates multiple statistics (e.g. cut rates, frameshifts) and presents results in form of aggregated reports. Data and statistics can be broken down by experiments, barcodes, user defined groups, guides and amplicons allowing for quick identification of potential problems.
Maintained by Eivind Valen. Last updated 5 months ago.
immunooncologytechnologyalignmentqpcrcrisprcpp
10 stars 7.54 score 41 scriptsbioc
MultimodalExperiment:Integrative Bulk and Single-Cell Experiment Container
MultimodalExperiment is an S4 class that integrates bulk and single-cell experiment data; it is optimally storage-efficient, and its methods are exceptionally fast. It effortlessly represents multimodal data of any nature and features normalized experiment, subject, sample, and cell annotations, which are related to underlying biological experiments through maps. Its coordination methods are opt-in and employ database-like join operations internally to deliver fast and flexible management of multimodal data.
Maintained by Lucas Schiffer. Last updated 5 months ago.
datarepresentationinfrastructuresinglecell
4.00 score 3 scripts