dansmith01
commented
10 months ago You can remove taxa names from the plot by setting layers="pe" (or any other layers spec without "t" - see https://cmmr.github.io/rbiom/reference/bdiv_ord_plot.html ).
To color points by a metadata variable, use the color.by parameter. See https://cmmr.github.io/rbiom/articles/aes.html for examples there.
On Mon, Jan 15, 2024 at 10:16 AM shwetha141 @.***> wrote:
Good morning, I was trying to create a Umap for beta diversity using rbiom and have a few questions. I am looking at distances between duplicate samples and noticed that bdiv_ord_plot outputs umap with labels such as Bacteroides (two others), is there a way to switch off this feature? The labels cover the points I want to see and having them off can help me make my point clearly. Secondly, is there a way to color the points differently, the package does suggest that I use the same parameters for ggplot but I was not able to do it. Below is an example of what I produced using the function, however, what I would like is the non-duplicated/ unique samples to be grey and the other duplicated samples to be filled. Secondly, I want the labels for the three bacteria to be turned off. Any suggestions?
Duplicated_unweighted_unrar.png (view on web) https://github.com/cmmr/rbiom/assets/19316250/1b49a7be-0e29-4a73-b686-f148c29dca44
R version 4.3.1 (2023-06-16 ucrt) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 11 x64 (build 22621)
Matrix products: default
locale: [1] LC_COLLATE=English_United States.utf8 LC_CTYPE=English_United States.utf8 [3] LC_MONETARY=English_United States.utf8 LC_NUMERIC=C [5] LC_TIME=English_United States.utf8
time zone: America/Chicago tzcode source: internal
attached base packages: [1] parallel grid stats4 stats graphics grDevices utils datasets methods base
other attached packages: [1] circlize_0.4.15 VennDiagram_1.7.3 futile.logger_1.4.3 [4] proustr_0.4.0 tm_0.7-11 NLP_0.2-1 [7] ggVennDiagram_1.4.13 miaViz_1.8.0 ggraph_2.1.0 [10] ggsignif_0.6.4 scater_1.30.1 scuttle_1.12.0 [13] mia_1.11.1 MultiAssayExperiment_1.28.0 TreeSummarizedExperiment_2.10.0 [16] Biostrings_2.70.1 XVector_0.42.0 SingleCellExperiment_1.24.0 [19] data.table_1.14.10 RColorBrewer_1.1-3 heatmaply_1.5.0 [22] Hmisc_5.1-1 DT_0.31 knitr_1.45 [25] tsne_0.1-3.1 GGally_2.2.0 reshape2_1.4.4 [28] robustHD_0.8.0 robustbase_0.99-1 perry_0.3.1 [31] corrplot_0.92 gplots_3.1.3 rstatix_0.7.2 [34] ComplexHeatmap_2.16.0 DESeq2_1.40.2 SummarizedExperiment_1.32.0 [37] Biobase_2.62.0 MatrixGenerics_1.14.0 matrixStats_1.1.0 [40] GenomicRanges_1.54.1 GenomeInfoDb_1.38.1 IRanges_2.36.0 [43] S4Vectors_0.40.2 BiocGenerics_0.48.1 ANCOMBC_2.2.2 [46] phyloseq_1.46.0 glue_1.6.2 viridis_0.6.4 [49] viridisLite_0.4.2 plotly_4.10.3 ggpubr_0.6.0 [52] gridExtra_2.3 hrbrthemes_0.8.0 rbiom_2.0.0.9110 [55] BiocManager_1.30.22 vegan_2.6-4 lattice_0.21-8 [58] permute_0.9-7 lubridate_1.9.3 forcats_1.0.0 [61] stringr_1.5.1 dplyr_1.1.4 purrr_1.0.2 [64] readr_2.1.4 tidyr_1.3.0 tibble_3.2.1 [67] ggplot2_3.4.4
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shwetha141
Good morning, I was trying to create a Umap for beta diversity using rbiom and have a few questions. I am looking at distances between duplicate samples and noticed that bdiv_ord_plot outputs umap with labels such as Bacteroides (two others), is there a way to switch off this feature? The labels cover the points I want to see and having them off can help me make my point clearly. Secondly, is there a way to color the points differently, the package does suggest that I use the same parameters for ggplot but I was not able to do it. Any suggestions?
R version 4.3.1 (2023-06-16 ucrt) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 11 x64 (build 22621)
Matrix products: default
locale: [1] LC_COLLATE=English_United States.utf8 LC_CTYPE=English_United States.utf8
[3] LC_MONETARY=English_United States.utf8 LC_NUMERIC=C
[5] LC_TIME=English_United States.utf8
time zone: America/Chicago tzcode source: internal
attached base packages: [1] parallel grid stats4 stats graphics grDevices utils datasets methods base
other attached packages: [1] circlize_0.4.15 VennDiagram_1.7.3 futile.logger_1.4.3
[4] proustr_0.4.0 tm_0.7-11 NLP_0.2-1
[7] ggVennDiagram_1.4.13 miaViz_1.8.0 ggraph_2.1.0
[10] ggsignif_0.6.4 scater_1.30.1 scuttle_1.12.0
[13] mia_1.11.1 MultiAssayExperiment_1.28.0 TreeSummarizedExperiment_2.10.0 [16] Biostrings_2.70.1 XVector_0.42.0 SingleCellExperiment_1.24.0
[19] data.table_1.14.10 RColorBrewer_1.1-3 heatmaply_1.5.0
[22] Hmisc_5.1-1 DT_0.31 knitr_1.45
[25] tsne_0.1-3.1 GGally_2.2.0 reshape2_1.4.4
[28] robustHD_0.8.0 robustbase_0.99-1 perry_0.3.1
[31] corrplot_0.92 gplots_3.1.3 rstatix_0.7.2
[34] ComplexHeatmap_2.16.0 DESeq2_1.40.2 SummarizedExperiment_1.32.0
[37] Biobase_2.62.0 MatrixGenerics_1.14.0 matrixStats_1.1.0
[40] GenomicRanges_1.54.1 GenomeInfoDb_1.38.1 IRanges_2.36.0
[43] S4Vectors_0.40.2 BiocGenerics_0.48.1 ANCOMBC_2.2.2
[46] phyloseq_1.46.0 glue_1.6.2 viridis_0.6.4
[49] viridisLite_0.4.2 plotly_4.10.3 ggpubr_0.6.0
[52] gridExtra_2.3 hrbrthemes_0.8.0 rbiom_2.0.0.9110
[55] BiocManager_1.30.22 vegan_2.6-4 lattice_0.21-8
[58] permute_0.9-7 lubridate_1.9.3 forcats_1.0.0
[61] stringr_1.5.1 dplyr_1.1.4 purrr_1.0.2
[64] readr_2.1.4 tidyr_1.3.0 tibble_3.2.1
[67] ggplot2_3.4.4