ipdworkshop/DESCRIPTION at devel · salernos/ipdworkshop · GitHub

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
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
Package: ipdworkshop
Title: Inference with Predicted Data Using the ipd Package
Version: 1.0.0
Authors@R:
    c(person(
      given  = "Stephen",
      family = "Salerno",
      role   = c("aut", "cre"),
      email  = "ssalerno@fredhutch.org",
      comment = c(ORCID = "0000-0003-2763-0494")
    ),
    person(
      given  = "Sean",
      family = "Davis",
      role   = "ctb",
      email  = "seandavi@gmail.com",
      comment = c(ORCID = "0000-0002-8991-6458")
    ))
Description: |
    A workshop demonstrating how to perform downstream statistical inference
    when the outcome has been partially imputed via a machine learning model.
    The central R package is the ipd package (Inference with Predicted Data).
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
Depends:
    R (>= 4.0),
    ipd,
    BiocStyle,
    Biobase
Imports:
    knitr,
    rmarkdown,
    tidyverse,
    patchwork,
    nhanesA,
    ranger,
    mgcv,
    pROC,
    ALL,
    golubEsets,
    AnnotationDbi,
    hgu95av2.db,
    hu6800.db,
    BiocGenerics,
    DALEX,
    broom,
    GGally,
    MLInterfaces,
    here,
    janitor,
    keggorthology,
    neuralnet,
    partykit,
    randomForest,
    scales
Suggests:
    DT,
    dplyr
URL: https://salernos.github.io/ipdworkshop/
BugReports: https://github.com/salernos/ipdworkshop/issues/new/choose
VignetteBuilder: knitr
DockerImage: ghcr.io/salernos/ipdworkshop:latest