Showing 5 of total 5 results (show query)
satijalab
Seurat:Tools for Single Cell Genomics
A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.2015.05.002>, Stuart T, Butler A, et al (2019) <doi:10.1016/j.cell.2019.05.031>, and Hao, Hao, et al (2020) <doi:10.1101/2020.10.12.335331> for more details.
Maintained by Paul Hoffman. Last updated 1 years ago.
human-cell-atlassingle-cell-genomicssingle-cell-rna-seqcpp
2.4k stars 16.86 score 50k scripts 73 dependentssatijalab
SeuratObject:Data Structures for Single Cell Data
Defines S4 classes for single-cell genomic data and associated information, such as dimensionality reduction embeddings, nearest-neighbor graphs, and spatially-resolved coordinates. Provides data access methods and R-native hooks to ensure the Seurat object is familiar to other R users. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.2015.05.002>, and Stuart T, Butler A, et al (2019) <doi:10.1016/j.cell.2019.05.031> for more details.
Maintained by Paul Hoffman. Last updated 2 years ago.
25 stars 11.69 score 1.2k scripts 88 dependents
samuel-marsh
scCustomize:Custom Visualizations & Functions for Streamlined Analyses of Single Cell Sequencing
Collection of functions created and/or curated to aid in the visualization and analysis of single-cell data using 'R'. 'scCustomize' aims to provide 1) Customized visualizations for aid in ease of use and to create more aesthetic and functional visuals. 2) Improve speed/reproducibility of common tasks/pieces of code in scRNA-seq analysis with a single or group of functions. For citation please use: Marsh SE (2021) "Custom Visualizations & Functions for Streamlined Analyses of Single Cell Sequencing" <doi:10.5281/zenodo.5706430> RRID:SCR_024675.
Maintained by Samuel Marsh. Last updated 3 months ago.
customizationggplot2scrna-seqseuratsingle-cellsingle-cell-genomicssingle-cell-rna-seqvisualization
246 stars 8.45 score 1.1k scripts
bioc
GeomxTools:NanoString GeoMx Tools
Tools for NanoString Technologies GeoMx Technology. Package provides functions for reading in DCC and PKC files based on an ExpressionSet derived object. Normalization and QC functions are also included.
Maintained by Maddy Griswold. Last updated 5 months ago.
geneexpressiontranscriptioncellbasedassaysdataimporttranscriptomicsproteomicsmrnamicroarrayproprietaryplatformsrnaseqsequencingexperimentaldesignnormalizationspatial
7.11 score 239 scripts 3 dependentsbioc
visiumStitched:Enable downstream analysis of Visium capture areas stitched together with Fiji
This package provides helper functions for working with multiple Visium capture areas that overlap each other. This package was developed along with the companion example use case data available from https://github.com/LieberInstitute/visiumStitched_brain. visiumStitched prepares SpaceRanger (10x Genomics) output files so you can stitch the images from groups of capture areas together with Fiji. Then visiumStitched builds a SpatialExperiment object with the stitched data and makes an artificial hexogonal grid enabling the seamless use of spatial clustering methods that rely on such grid to identify neighboring spots, such as PRECAST and BayesSpace. The SpatialExperiment objects created by visiumStitched are compatible with spatialLIBD, which can be used to build interactive websites for stitched SpatialExperiment objects. visiumStitched also enables casting SpatialExperiment objects as Seurat objects.
Maintained by Nicholas J. Eagles. Last updated 4 months ago.
softwarespatialtranscriptomicstranscriptiongeneexpressionvisualizationdataimport10xgenomicsbioconductorspatial-transcriptomicsspatialexperimentspatiallibdvisium
1 stars 5.36 score 4 scripts