Description Usage Arguments Value See Also Examples
This function would base on Fold-Change information from the output of negative_cor, differExp_discrete and show heatmaps to users. Note that if miRNA-gene interactions (row) from input are larger than 100, the lable in plot would be unclear.
1 | heat_vis(cor_data, mrna_d, mirna_21)
|
cor_data |
matrix format generated from negative_cor. |
mrna_d |
differential expressed data in data.frame format, with sample name in columns and gene symbol in rows, which is generated by differExp_discrete or differExp_continuous. |
mirna_21 |
differential expressed data in data.frame format, with sample name in columns and miRNAl in rows, which is generated by differExp_discrete or differExp_continuous, miRNA should be miRBase 21 version now. |
heatmap plots of miRNA and gene.
heatmap.2
for plot.
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 | ## Use the internal dataset
data("mirna", package = "anamiR", envir = environment())
data("pheno.mirna", package = "anamiR", envir = environment())
data("mrna", package = "anamiR", envir = environment())
data("pheno.mrna", package = "anamiR", envir = environment())
## SummarizedExperiment class
require(SummarizedExperiment)
mirna_se <- SummarizedExperiment(
assays = SimpleList(counts=mirna),
colData = pheno.mirna)
## SummarizedExperiment class
require(SummarizedExperiment)
mrna_se <- SummarizedExperiment(
assays = SimpleList(counts=mrna),
colData = pheno.mrna)
## Finding differential miRNA from miRNA expression data with t.test
mirna_d <- differExp_discrete(
se = mirna_se,
class = "ER",
method = "t.test"
)
## Finding differential mRNA from mRNA expression data with t.test
mrna_d <- differExp_discrete(
se = mrna_se,
class = "ER",
method = "t.test"
)
## Convert annotation to miRBse 21
mirna_21 <- miR_converter(data = mirna_d, original_version = 17)
## Correlation
cor <- negative_cor(mrna_data = mrna_d, mirna_data = mirna_21)
## Draw heatmap
heat_vis(cor, mrna_d, mirna_21)
|
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