-
Notifications
You must be signed in to change notification settings - Fork 0
/
DESCRIPTION
38 lines (38 loc) · 1.25 KB
/
DESCRIPTION
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
Package: recall
Title: Calibrated clustering with artificial variables to avoid over-clustering in single-cell RNA-sequencing
Version: 0.0.0
Authors@R:
person("Alan", "DenAdel", , "alan_denadel@brown.edu", role = c("aut", "cre"),
comment = c(ORCID = "0000-0002-7985-6789"))
Description: recall (Calibrated Clustering with Artificial Variables) is a method for protecting
against over-clustering by controlling for the impact of double-dipping. The approach
can be applied to any clustering algorithm (implemented are the Louvain and Leiden algorithms with
plans forK-means, and hierarchical clustering algorithms). The method provides state-of-the-art
clustering performance and can rapidly analyze large-scale scRNA-seq studies and is
compatible with the Seurat library.
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
Imports:
Matrix,
Seurat (>= 5.0.1),
SingleCellExperiment,
scDesign3,
SummarizedExperiment,
MASS,
fitdistrplus,
lamW,
knockoff,
future,
stats,
cli,
stringr,
countsplit
License: MIT + file LICENSE
Suggests:
knitr,
markdown
Remotes:
scDesign3=github::SONGDONGYUAN1994/scDesign3
VignetteBuilder: knitr
URL: https://lcrawlab.github.io/recall/