scRNA MAST
Template developed with materials from https://hbctraining.github.io/main/.
This code is in this 
revision.
Overview
- Project: name_hbcXXXXX
- PI: person name
- Analyst: person in the core
- Experiment: short description
- Aim: short description
MAST analysis
Pre-processing
Subset genes observed in at least 10% of cells …
Prep for MAST comparison …
MAST run with desired contrasts …
Output results …
[Full MAST object saved]
[MAST summary results output to csv files]
[Significant MAST summary results output to csv files]
Differentially Expressed Genes Table
[Option 1: numbers displayed in digits]
[Option 2: FDR displayed in scientific notation]
Group Mean Heatmap
Volcano plot and Top DEG
This volcano plot shows the genes that are significantly up- and down-regulated as a result of the analysis comparison.
The points highlighted:
- in grey points are non-significant.
- in blue have a padj > 0.05 and a log2-fold change > 0.5.
- in plum have a padj < 0.05 and a log2-fold change < 0.5.
- in purple are genes that have fdr < 0.05 and a log2-fold change > 0.5.
The dashed lines correspond to the cutoff values of log2 foldchance and padj that we have chosen.
% of expression for Top DEGs
(Option 1: Plain) sc-expression across contrast groups: top 16 DEGs
(Option 2: Colored) sc-expression across contrast groups: top 16 DEGs
Options for dot styles for above plots
Method description
MAST is used to generate differential expressed genes among the supplied contrast groups by taking into account the number of genes activated in every cell, also other batch information (e.g. different samples in the suppliedd seurat object).
Please read more about MAST in its paper and github repository.
R session
List and version of tools used for the QC report generation.
R version 4.5.1 (2025-06-13)
Platform: x86_64-pc-linux-gnu
Running under: Ubuntu 22.04.5 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0
locale:
[1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8
[4] LC_COLLATE=C.UTF-8 LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8
[7] LC_PAPER=C.UTF-8 LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C
time zone: UTC
tzcode source: system (glibc)
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] qs_0.27.3 ggpubr_0.6.1 viridis_0.6.5
[4] viridisLite_0.4.2 pheatmap_1.0.13 EnhancedVolcano_1.26.0
[7] ggrepel_0.9.6 knitr_1.50 ggprism_1.0.6
[10] data.table_1.17.8 lubridate_1.9.4 forcats_1.0.0
[13] stringr_1.5.1 dplyr_1.1.4 purrr_1.1.0
[16] readr_2.1.5 tidyr_1.3.1 tibble_3.3.0
[19] ggplot2_3.5.2 tidyverse_2.0.0 Seurat_5.3.0
[22] SeuratObject_5.1.0 sp_2.2-0
loaded via a namespace (and not attached):
[1] RColorBrewer_1.1-3 jsonlite_2.0.0 magrittr_2.0.3
[4] ggbeeswarm_0.7.2 spatstat.utils_3.1-5 farver_2.1.2
[7] rmarkdown_2.29 vctrs_0.6.5 ROCR_1.0-11
[10] spatstat.explore_3.5-2 rstatix_0.7.2 htmltools_0.5.8.1
[13] broom_1.0.9 Formula_1.2-5 sass_0.4.10
[16] sctransform_0.4.2 parallelly_1.45.1 bslib_0.9.0
[19] KernSmooth_2.23-26 htmlwidgets_1.6.4 ica_1.0-3
[22] plyr_1.8.9 cachem_1.1.0 plotly_4.11.0
[25] zoo_1.8-14 igraph_2.1.4 mime_0.13
[28] lifecycle_1.0.4 pkgconfig_2.0.3 Matrix_1.7-3
[31] R6_2.6.1 fastmap_1.2.0 fitdistrplus_1.2-4
[34] future_1.58.0 shiny_1.11.1 digest_0.6.37
[37] patchwork_1.3.1 tensor_1.5.1 RSpectra_0.16-2
[40] irlba_2.3.5.1 crosstalk_1.2.1 labeling_0.4.3
[43] progressr_0.15.1 spatstat.sparse_3.1-0 timechange_0.3.0
[46] httr_1.4.7 polyclip_1.10-7 abind_1.4-8
[49] compiler_4.5.1 withr_3.0.2 backports_1.5.0
[52] carData_3.0-5 fastDummies_1.7.5 ggsignif_0.6.4
[55] MASS_7.3-65 tools_4.5.1 vipor_0.4.7
[58] lmtest_0.9-40 beeswarm_0.4.0 httpuv_1.6.16
[61] future.apply_1.20.0 goftest_1.2-3 glue_1.8.0
[64] nlme_3.1-168 promises_1.3.3 grid_4.5.1
[67] Rtsne_0.17 cluster_2.1.8.1 reshape2_1.4.4
[70] generics_0.1.4 gtable_0.3.6 spatstat.data_3.1-6
[73] tzdb_0.5.0 RApiSerialize_0.1.4 hms_1.1.3
[76] stringfish_0.16.0 car_3.1-3 spatstat.geom_3.5-0
[79] RcppAnnoy_0.0.22 RANN_2.6.2 pillar_1.11.0
[82] spam_2.11-1 RcppHNSW_0.6.0 later_1.4.2
[85] splines_4.5.1 lattice_0.22-7 survival_3.8-3
[88] deldir_2.0-4 tidyselect_1.2.1 miniUI_0.1.2
[91] pbapply_1.7-4 gridExtra_2.3 scattermore_1.2
[94] xfun_0.52 matrixStats_1.5.0 DT_0.33
[97] stringi_1.8.7 lazyeval_0.2.2 yaml_2.3.10
[100] evaluate_1.0.4 codetools_0.2-20 BiocManager_1.30.26
[103] cli_3.6.5 RcppParallel_5.1.10 uwot_0.2.3
[106] xtable_1.8-4 reticulate_1.43.0 jquerylib_0.1.4
[109] Rcpp_1.1.0 globals_0.18.0 spatstat.random_3.4-1
[112] png_0.1-8 spatstat.univar_3.1-4 parallel_4.5.1
[115] dotCall64_1.2 listenv_0.9.1 scales_1.4.0
[118] ggridges_0.5.6 rlang_1.1.6 cowplot_1.2.0