Extract genes with highest loadings
hi_loadings(
pcaobj,
whichpc = 1,
topN = 10,
exprTable = NULL,
annotation = NULL,
title = "Top/bottom loadings"
)Arguments
- pcaobj
A
prcompobject- whichpc
An integer number, corresponding to the principal component of interest
- topN
Integer, number of genes with top and bottom loadings
- exprTable
A
matrixobject, e.g. the counts of aDESeqDataSet(). If not NULL, returns the counts matrix for the selected genes- annotation
A
data.frameobject, with row.names as gene identifiers (e.g. ENSEMBL ids) and a column,gene_name, containing e.g. HGNC-based gene symbols- title
The title of the plot
Value
A ggplot2 object, or a matrix, if exprTable is not null
Examples
dds <- makeExampleDESeqDataSet_multifac(betaSD = 3, betaSD_tissue = 1)
rlt <- DESeq2::rlogTransformation(dds)
pcaobj <- prcomp(t(SummarizedExperiment::assay(rlt)))
hi_loadings(pcaobj, topN = 20)
hi_loadings(pcaobj, topN = 10, exprTable = dds)
#> class: DESeqDataSet
#> dim: 20 12
#> metadata(1): version
#> assays(1): counts
#> rownames(20): gene300 gene88 ... gene961 gene444
#> rowData names(4): trueIntercept trueBeta_condition trueBeta_tissue
#> trueDisp
#> colnames(12): sample1 sample2 ... sample11 sample12
#> colData names(2): condition tissue
hi_loadings(pcaobj, topN = 10, exprTable = counts(dds))
#> sample1 sample2 sample3 sample4 sample5 sample6 sample7 sample8 sample9
#> gene300 16 6 10 2 0 1 1351 526 1211
#> gene88 30 77 24 46 8 37 8591 6193 11330
#> gene427 45 64 42 76 60 124 4956 3260 2321
#> gene415 109 129 49 51 125 130 19543 18247 13509
#> gene305 1 5 0 0 0 0 1732 321 19
#> gene838 27 5 10 7 7 7 2112 4368 3959
#> gene239 9 6 3 1 1 0 903 3410 74
#> gene758 49 13 39 30 38 58 8797 12405 3412
#> gene917 15 21 33 32 14 5 12829 27023 14151
#> gene766 3 6 16 8 10 4 3819 3015 3545
#> gene496 347 297 299 398 258 374 0 3 2
#> gene4 90 53 27 102 152 72 0 0 0
#> gene558 233 71 211 170 126 90 3 1 0
#> gene361 42 29 31 88 61 196 0 0 0
#> gene795 172 162 79 186 146 60 1 5 0
#> gene124 105 39 57 143 81 182 0 3 0
#> gene54 39 82 63 39 27 67 1 0 0
#> gene204 47 62 116 81 125 84 1 1 1
#> gene961 71 91 89 79 129 93 0 2 1
#> gene444 13 35 56 80 62 15 0 0 0
#> sample10 sample11 sample12
#> gene300 441 227 449
#> gene88 2797 542 3383
#> gene427 19699 18154 24313
#> gene415 4508 11323 10913
#> gene305 81 219 14
#> gene838 430 1477 1446
#> gene239 158 346 3642
#> gene758 17233 16278 10338
#> gene917 6588 1753 730
#> gene766 1388 3942 2556
#> gene496 4 5 2
#> gene4 1 0 0
#> gene558 1 2 1
#> gene361 0 1 0
#> gene795 1 2 1
#> gene124 1 1 1
#> gene54 0 0 0
#> gene204 0 1 2
#> gene961 2 1 2
#> gene444 1 0 1