Package: HIPPO 1.19.0

Tae Kim

HIPPO: Heterogeneity-Induced Pre-Processing tOol

For scRNA-seq data, it selects features and clusters the cells simultaneously for single-cell UMI data. It has a novel feature selection method using the zero inflation instead of gene variance, and computationally faster than other existing methods since it only relies on PCA+Kmeans rather than graph-clustering or consensus clustering.

Authors:Tae Kim [aut, cre], Mengjie Chen [aut]

HIPPO_1.19.0.tar.gz
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HIPPO.pdf |HIPPO.html
HIPPO/json (API)
NEWS

# Install 'HIPPO' in R:
install.packages('HIPPO', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/tk382/hippo/issues

Datasets:
  • ensg_hgnc - A reference data frame that matches ENSG IDs to HGNC symbols
  • toydata - A sample single cell sequencing data subsetted from Zheng2017

On BioConductor:HIPPO-1.19.0(bioc 3.21)HIPPO-1.18.0(bioc 3.20)

sequencingsinglecellgeneexpressiondifferentialexpressionclustering

6.16 score 18 stars 4 scripts 186 downloads 8 mentions 18 exports 74 dependencies

Last updated 4 months agofrom:3720af6268. Checks:1 OK, 6 NOTE, 1 WARNING. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 16 2025
R-4.5-winNOTEFeb 16 2025
R-4.5-macWARNINGFeb 16 2025
R-4.5-linuxNOTEFeb 16 2025
R-4.4-winNOTEFeb 16 2025
R-4.4-macNOTEFeb 16 2025
R-4.3-winNOTEFeb 16 2025
R-4.3-macNOTEFeb 16 2025

Exports:%>%get_data_from_sceget_hippoget_hippo_diffexphippohippo_diagnostic_plothippo_diffexphippo_dimension_reductionhippo_feature_heatmaphippo_pca_plothippo_tsne_plothippo_umap_plotnb_prob_zeropois_prob_zeropreprocess_heterogeneouspreprocess_homogeneouszero_proportion_plotzinb_prob_zero

Dependencies:abindaskpassBiobaseBiocGenericsclicolorspacecrayoncurlDelayedArraydplyrfansifarvergenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2ggrepelgluegridExtragtableherehttrIRangesirlbaisobandjsonlitelabelinglatticelifecyclemagrittrMASSMatrixMatrixGenericsmatrixStatsmgcvmimemunsellnlmeopensslpillarpkgconfigplyrpngR6rappdirsRColorBrewerRcppRcppEigenRcppTOMLreshape2reticulaterlangrprojrootRSpectraRtsneS4ArraysS4VectorsscalesSingleCellExperimentSparseArraystringistringrSummarizedExperimentsystibbletidyselectUCSC.utilsumaputf8vctrsviridisLitewithrXVector

Feature Selection and Hierarchical Clustering of cells in Zhengmix4eq

Rendered fromexample.Rmdusingknitr::rmarkdownon Feb 16 2025.

Last update: 2020-03-26
Started: 2019-12-30