Depending on the pipeline used to generate the single-cell object,
there may be inherent mismatches in the barcodes in the single-cell
object and the output of combineBCR()
or
combineTCR()
.
Seurat-modified barcodes: By default, Seurat will append _X to the suffix of the barcodes.
original: ACGTACGTACGTACGT-1
seurat-modified: ACGTACGTACGTACGT-1_1
scRepertoire-modified barcodes:
scRepertoire
uses the samples and/or ID parameters in
combineTCR()
or combineBCR()
to add a prefix
to the barcodes.
original: ACGTACGTACGTACGT-1
scRepertoire-modified: Sample1_ACGTACGTACGTACGT-1
The easiest way to make these compatible is to rename the cell
barcodes in the Seurat object using RenameCells()
from the
SeuratObject
package
# Assuming 'seuratObj' is your Seurat object
cell.barcodes <- rownames(seuratObj[[]])
# removing the _1 at the end of the barcodes (adjust regex if your suffix differs)
cell.barcodes <- stringr::str_split(cell.barcodes, "_", simplify = TRUE)[,1]
# adding the prefix of the orig.ident to the barcodes, assuming that is the sample IDs
cell.barcodes <- paste0(seuratObj$orig.ident, "_", cell.barcodes)
seuratObj <- RenameCells(seuratObj, new.names = cell.barcodes)
For all visualizations in scRepertoire
, you have two
primary ways to adjust the color scheme.
Methods for Color Adjustment
palette
parameter within scRepertoire
functions to the desired color scheme. This approach uses the built-in
palettes of grDevices
, and you can access the list of
available color schemes using hcl.pals()
.scRepertoire
plot (which is a ggplot object) by adding a
ggplot2
layer with a new color scheme using
scale_fill_manual()
or similar functions.# Internal Palette Selection
clonalQuant(combined.TCR,
cloneCall="strict",
chain = "both",
scale = TRUE,
palette = "Zissou 1")
# Using gg System
clonalQuant(combined.TCR,
cloneCall="strict",
chain = "both",
scale = TRUE) +
scale_fill_manual(values = hcl.colors(8,"geyser"))
Since scRepertoire
functions return ggplot
objects, modifying the general appearance or theme of the plot is
straightforward, similar to adjusting color palettes—by adding a
ggplot2
theme layer.
# Original clonalQuant plot
clonalQuant(combined.TCR,
cloneCall="strict",
chain = "both",
scale = TRUE)
# Modifying the theme of the clonalQuant plot
clonalQuant(combined.TCR,
cloneCall="strict",
chain = "both",
scale = TRUE) +
theme_classic()
The order of grouping/group.by variables in scRepertoire
plots (whether along an axis or in color legends) can be precisely
controlled using the order.by parameter.
Key Parameter for Plot Order
order.by
: A character vector defining the desired order
of elements for the group.by
variable. It’s crucial that
the strings in this vector exactly match the group.by
strings. Alternatively, setting order.by = "alphanumeric"
will automatically sort groups alphanumerically.clonalQuant(combined.TCR,
cloneCall="strict",
chain = "both",
scale = TRUE,
order.by = c("P17B","P18B","P19B","P20B","P17L","P18L","P19L","P20L"))
Within each of the general analysis functions in
scRepertoire
, there’s an option to export the underlying
data frame used to create the visualization.
Key Parameter for Data Export
exportTable
: Set this parameter to TRUE
to
return the data frame used to generate the graph instead of the visual
output.clonalQuant_output <- clonalQuant(combined.TCR,
cloneCall="strict",
scale = TRUE,
exportTable = TRUE)
clonalQuant_output
## contigs values total scaled
## 1 745 P17B 2805 26.55971
## 2 2117 P17L 2893 73.17663
## 3 1254 P18B 1328 94.42771
## 4 1202 P18L 1278 94.05321
## 5 5544 P19B 6942 79.86171
## 6 1619 P19L 2747 58.93702
## 7 6087 P20B 8991 67.70103
## 8 192 P20L 201 95.52239
When using scRepertoire
in your research, please cite
the appropriate version of the package.
Citation Details
Your feedback is valuable for improving scRepertoire! If you encounter a bug or have a suggestion for a new feature, please report it.
Submit a GitHub issue - if possible please include a reproducible example. Alternatively, an example with the internal scRep_example and contig_list would be extremely helpful.