In NMikolajewicz/scMiko: scRNAseq analysis functions. Developed using Seurat framework.

all_times <- list()  # store the time for each chunk
knitr::knit_hooks$set(time_it = local({
  now <- NULL
  function(before, options) {
    if (before) {
      now <<- Sys.time()
    } else {
      res <- difftime(Sys.time(), now, units = "secs")
      all_times[[options$label]] <<- res
    }
  }
}))

knitr::opts_chunk$set(
  tidy = TRUE,
  tidy.opts = list(width.cutoff = 95),
  message = FALSE,
  warning = FALSE,
  time_it = TRUE
)

# load package
library(scMiko)
library(DT)

Cell-type markers

Marker-based cell-type annotation requires a reference databse comprised of cell-type annotated gene sets. To generate a cell-type marker reference catalog, we derived cell-type markers from public diverse scRNAseq atlases and using the Wilcoxon DE method to identify differentially-expressed genes across author-curated cell types. All markers satisfying logFC > 0.5, AUROC > 0.95 and FDR < 1% were included. If less than 15 markers were identified per a cell-type using these criteria, the top N markers (ranked by logFC) that satisfied FDR < 1% were taken to ensure the minimum 15 markers per cell-type requirement was satisfied.

Cell-type marker catalog

Table of cell-type markers

# load markers (loaded as data.frame)
cell_catalog <- geneSets[["Cell_Catalog"]]

# list representation as follows:
cell_catalog.list <- wideDF2namedList(cell_catalog)

# show table
flex.asDT(cell_catalog, page_length = 10,  scrollX = TRUE)

Represented cell-types

Here is a cell-type look up table to check cell-type representation in our catalog.

# show cell-types
flex.asDT(data.frame(cell_types = names(cell_catalog.list)), page_length = 10)

Single cell atlases

Here are the annotated atlases that were used to derive our marker catalog:

Cao 2019 | Murine Organogenesis

Cao, J., Spielmann, M., Qiu, X., Huang, X., Ibrahim, D. M., Hill, A. J., . . . Steemers, F. J. (2019). The single-cell transcriptional landscape of mammalian organogenesis. Nature, 566(7745), 496-502. link

# knitr::include_graphics("assets/atlas_cao2019.png")
knitr::include_graphics("../vignettes/assets/atlas_cao2019.png")

Cao 2020 | Human Fetus

Cao, J., O’Day, D. R., Pliner, H. A., Kingsley, P. D., Deng, M., Daza, R. M., . . . Zhang, F. (2020). A human cell atlas of fetal gene expression. Science, 370(6518). link

knitr::include_graphics("../vignettes/assets/atlas_cao2020.png")

La Manno 2021 | Developing Murine Brain

La Manno, G., Siletti, K., Furlan, A., Gyllborg, D., Vinsland, E., Mossi Albiach, A., . . . Dratva, L. M. (2021). Molecular architecture of the developing mouse brain. Nature, 596(7870), 92-96. link

knitr::include_graphics("../vignettes/assets/atlas_mannos2021.png")

Pijuan-Sala 2019 | Murine Gastrulation

Pijuan-Sala, B., Griffiths, J. A., Guibentif, C., Hiscock, T. W., Jawaid, W., Calero-Nieto, F. J., . . . Ho, D. L. L. (2019). A single-cell molecular map of mouse gastrulation and early organogenesis. Nature, 566(7745), 490-495. link

knitr::include_graphics("../vignettes/assets/atlas_ps2019.png")

Tabula Muris | Murine Cell-Type Atlas

Consortium, T. M. (2018). Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris. Nature, 562(7727), 367-372. link

knitr::include_graphics("../vignettes/assets/atlas_tm.png")

Tabula Sapiens | Human Cell-Type Atlas

Quake, S. R., & Consortium, T. S. (2021). The Tabula Sapiens: a single cell transcriptomic atlas of multiple organs from individual human donors. Biorxiv. link

knitr::include_graphics("../vignettes/assets/atlas_ts.png")

Tyser 2021 | Human Gastrulation

Tyser, R. C., Mahammadov, E., Nakanoh, S., Vallier, L., Scialdone, A., & Srinivas, S. (2021). Single-cell transcriptomic characterization of a gastrulating human embryo. Nature, 1-5. link

knitr::include_graphics("../vignettes/assets/atlas_tyser2021.png")

Zeisel 2018 | Adolescent Murine Brain

Zeisel, A., Hochgerner, H., Lönnerberg, P., Johnsson, A., Memic, F., Van Der Zwan, J., . . . La Manno, G. (2018). Molecular architecture of the mouse nervous system. Cell, 174(4), 999-1014. e1022. link

knitr::include_graphics("../vignettes/assets/atlas_zeisel2018.png")

\

Other cell-type databases

There are other cell-type marker databases available, including PanglaoDB, CellMarkers and MSigDB

We have consolidated the cell-type markers from PanglaoDB and CellMarkers, and they can be accessed as follows:

PanglaoDB

# load markers
murine_markers <- geneSets[["Panglao_Mm"]]
human_markers <- geneSets[["Panglao_Hs"]]

flex.asDT(human_markers, page_length = 10,  scrollX = TRUE)

CellMarkers

# load markers
cell_markers <- geneSets[["CellMarker_Hs_Zhang2019"]]

flex.asDT(cell_markers, page_length = 10,  scrollX = TRUE)

Session Info

sessionInfo()

NMikolajewicz/scMiko documentation built on June 28, 2023, 1:41 p.m.