PCA / MDS / tSNE visualisation (mainly overlap / gene usage)
# S3 method for immunr_mds vis(.data, .by = NA, .meta = NA, .point = T, .text = T, .ellipse = T, .point.size = 2, .text.size = 4, ...)
.data | Output from analysis functions such as geneUsageAnalysis or immunr_pca, immunr_mds or immunr_tsne. |
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.by | Pass NA if you want to plot samples without grouping. You can pass a character vector with one or several column names from ".meta" to group your data before plotting. In this case you should provide ".meta". You can pass a character vector that exactly matches the number of samples in your data, each value should correspond to a sample's property. It will be used to group data based on the values provided. Note that in this case you should pass NA to ".meta". |
.meta | A metadata object. An R dataframe with sample names and their properties, such as age, serostatus or hla. |
.point | Logical. If TRUE then plot points corresponding to objects. |
.text | Logical. If TRUE then plot sample names. |
.ellipse | Logical. If TRUE then plot ellipses around clusters of grouped samples. |
.point.size | Numeric. A size of points to plot. |
.text.size | Numeric. A size of sample names' labels. |
... | Not used here. |
Other visualisation methods:
- PCA - vis.immunr_pca
- MDS - vis.immunr_mds
- tSNE - vis.immunr_tsne