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 aDESeq2::DESeqDataSet(). 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): gene581 gene426 ... gene115 gene280
#> 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
#> gene581 1 9 6 18 13 3 651 393 1936
#> gene426 10 21 0 27 38 36 5112 795 2181
#> gene853 27 36 19 116 200 60 6906 3141 4588
#> gene171 6 35 49 16 58 31 10801 6918 10332
#> gene904 13 14 13 45 19 8 6564 4084 1688
#> gene498 33 25 25 10 32 20 8275 6536 8335
#> gene251 5 7 4 8 1 11 5941 3281 1098
#> gene901 1 7 2 2 2 1 1946 1029 2166
#> gene330 23 56 11 9 7 4 6884 17151 5819
#> gene179 11 18 17 4 5 1 5566 3776 3417
#> gene695 69 113 212 66 99 108 0 1 0
#> gene731 100 87 109 65 195 157 0 2 0
#> gene283 90 81 88 102 134 217 0 1 2
#> gene208 131 130 154 108 76 155 0 0 1
#> gene497 68 59 94 226 213 142 1 1 0
#> gene374 73 85 156 86 127 67 2 0 0
#> gene245 48 77 78 376 554 275 2 1 2
#> gene709 49 48 29 85 63 202 2 1 0
#> gene115 63 49 72 57 12 23 0 2 0
#> gene280 35 17 59 68 84 69 0 1 1
#> sample10 sample11 sample12
#> gene581 852 1349 1960
#> gene426 2947 2934 5641
#> gene853 21473 43639 26752
#> gene171 11320 11922 5176
#> gene904 5193 10201 10899
#> gene498 8388 8675 14914
#> gene251 3145 2443 1077
#> gene901 1991 643 419
#> gene330 4038 7566 2040
#> gene179 3222 2816 2721
#> gene695 0 1 1
#> gene731 1 2 0
#> gene283 0 0 5
#> gene208 2 1 6
#> gene497 8 0 4
#> gene374 1 1 6
#> gene245 8 6 2
#> gene709 3 1 0
#> gene115 0 0 0
#> gene280 1 1 0