View source: R/assemble.byDataset.R
assemble.byDataset | R Documentation |
Assemble individual figures for a single dataset analyzed and plotted by SJD
assemble.byDataset(
SJDScorePlotter.obj,
dataset_name,
SJD_algorithm,
group = NA
)
SJDScorePlotter.obj |
A list outputted by the SJDScorePlotter function |
dataset_name |
dataset/study analyzed by SJD |
SJD_algorithm |
SJD_algorithm name of SJD algorithm, i.e. concatICA |
group |
group name of the weights group from the SJD_algorithm output, i.e 'Shared.All.13' |
a list of images filtered by dataset
library(ggplot2)
data(NeuroGenesis4.afterWrap)
data(NeuroGenesis4.info)
SampleMetaNamesTable = data.frame(
row.names = names(NeuroGenesis4.afterWrap),
Type = c('Yaxis','Yaxis','2Dscatter','2Dscatter'),
XaxisColumn = c("X","DAYx","tSNE_1","tsne1:ch1"),
YaxisColumn = c("PJDscores","PJDscores","tSNE_2","tsne2:ch1"),
COLaxisColumn = c("color","colorBYlabelsX","PJDscores","PJDscores"),
PCHColumn = c("","","","")
)
grp = list(
Shared.All.4 = c(1 : 4),
Shared.bulk.2 = c(1, 2),
Shared.sc.2 = c(3, 4),
Hs.Meisnr.1 = c(1),
Hs.AZ.1 = c(2),
Gesch.1 = c(3),
Telley.1 = c(4)
)
dims = c(2, 2, 2, 2, 2, 2, 2)
lbb = "NeuroGenesis4.p2"
twoStageLCA.out = twoStageLCA(dataset = NeuroGenesis4.afterWrap, group = grp, comp_num = dims)
SJDScorePlotter.obj = SJDScorePlotter(
SJDalg = "twoStageLCA",
scores = twoStageLCA.out$score_list,
lbb = lbb,
info = NeuroGenesis4.info,
SampleMetaNamesTable = SampleMetaNamesTable
)
assemble.byDataset.obj = assemble.byDataset(
SJDScorePlotter.obj = SJDScorePlotter.obj,
dataset_name = "Meissner.inVitro.bulk.Hs",
SJD_algorithm = "twoStageLCA",
group = NA)
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