homepage: http://github.com/GregorySchwartz/too-many-cells#readme
changelog-type: ''
hash: 696072c48165a94d598d9cbe99fd7c3caffbb2e2465ba30bbb782addf766e733
test-bench-deps: {}
maintainer: gsch@pennmedicine.upenn.edu
synopsis: Cluster single cells and analyze cell clade relationships.
changelog: ''
basic-deps:
  streaming: -any
  diagrams-lib: -any
  birch-beer: -any
  bytestring: -any
  optparse-generic: -any
  SVGFonts: -any
  too-many-cells: -any
  diagrams-graphviz: -any
  split: -any
  base: ! '>=4.7 && <5'
  palette: -any
  find-clumpiness: -any
  streaming-cassava: -any
  managed: -any
  diagrams-cairo: -any
  text: -any
  modularity: -any
  streaming-with: -any
  text-show: -any
  filepath: -any
  streaming-utils: -any
  hierarchical-clustering: -any
  graphviz: -any
  spectral-clustering: -any
  containers: -any
  plots: -any
  lens: -any
  cassava: -any
  matrix-market-attoparsec: -any
  hierarchical-spectral-clustering: -any
  fgl: -any
  mtl: -any
  foldl: -any
  sparse-linear-algebra: -any
  statistics: -any
  terminal-progress-bar: -any
  vector-algorithms: -any
  colour: -any
  transformers: -any
  diversity: -any
  parallel: -any
  deepseq: -any
  scientific: -any
  hmatrix: -any
  diagrams: -any
  streaming-bytestring: -any
  inline-r: -any
  aeson: -any
  safe: -any
  differential: -any
  vector: -any
  mltool: -any
  directory: -any
all-versions:
- 0.1.0.0
author: Gregory W. Schwartz
latest: 0.1.0.0
description-type: haddock
description: Different methods to cluster and analyze single cell data with diversity
  indices and differential expression.
license-name: GPL-3.0-only

Update from Hackage at 2019-01-10T18:17:37Z
Update from Hackage at 2019-01-10T18:17:37Z
