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single cell sequencing understanding the structure of a data

Hello guys,

I am trying to understand the structure of single cell data

df<- new("Seurat", assays = list(RNA = new("Assay", counts = new("dgCMatrix", 
    i = c(1L, 4L, 1L, 2L, 1L), p = c(0L, 2L, 4L, 5L), Dim = c(5L, 
    3L), Dimnames = list(c("0610005C13Rik", "0610007C21Rik", 
    "0610007L01Rik", "0610007N19Rik", "0610007P08Rik"), c("10X_P4_0_AAACCTGAGATTACCC", 
    "10X_P4_0_AAACCTGAGTGCCAGA", "10X_P4_0_AAACCTGCAAATCCGT")), 
    x = c(3, 2, 1, 1, 3), factors = list()), data = new("dgCMatrix", 
    i = c(1L, 4L, 1L, 2L, 1L), p = c(0L, 2L, 4L, 5L), Dim = c(5L, 
    3L), Dimnames = list(c("0610005C13Rik", "0610007C21Rik", 
    "0610007L01Rik", "0610007N19Rik", "0610007P08Rik"), c("10X_P4_0_AAACCTGAGATTACCC", 
    "10X_P4_0_AAACCTGAGTGCCAGA", "10X_P4_0_AAACCTGCAAATCCGT")), 
    x = c(3, 2, 1, 1, 3), factors = list()), scale.data = structure(numeric(0), .Dim = c(0L, 
0L)), key = "rna_", assay.orig = NULL, var.features = character(0), 
    meta.features = structure(list(), .Names = character(0), row.names = c("0610005C13Rik", 
    "0610007C21Rik", "0610007L01Rik", "0610007N19Rik", "0610007P08Rik"
    ), class = "data.frame"), misc = list())), meta.data = structure(list(
    orig.ident = structure(c(1L, 1L, 1L), .Label = "10X", class = "factor"), 
    nCount_RNA = c(5, 2, 3), nFeature_RNA = c(2L, 2L, 1L), cell = c("10X_P4_0_AAACCTGAGATTACCC", 
    "10X_P4_0_AAACCTGAGTGCCAGA", "10X_P4_0_AAACCTGCAAATCCGT"), 
    channel = c("10X_P4_0", "10X_P4_0", "10X_P4_0"), mouse.id = c("3-M-8", 
    "3-M-8", "3-M-8"), tissue = c("Tongue", "Tongue", "Tongue"
    ), subtissue = c(NA_character_, NA_character_, NA_character_
    ), mouse.sex = c("M", "M", "M"), method = c("droplet", "droplet", 
    "droplet"), cell_ontology_class = c("basal cell of epidermis", 
    "keratinocyte", "keratinocyte"), cell_ontology_id = c("CL:0002187", 
    "CL:0000312", "CL:0000312"), free_annotation = c("proliferating", 
    "differentiated", "suprabasal differentiating")), row.names = c("10X_P4_0_AAACCTGAGATTACCC", 
"10X_P4_0_AAACCTGAGTGCCAGA", "10X_P4_0_AAACCTGCAAATCCGT"), class = "data.frame"), 
    active.assay = "RNA", active.ident = structure(c(`10X_P4_0_AAACCTGAGATTACCC` = 1L, 
    `10X_P4_0_AAACCTGAGTGCCAGA` = 1L, `10X_P4_0_AAACCTGCAAATCCGT` = 1L
    ), .Label = "10X", class = "factor"), graphs = list(), neighbors = list(), 
    reductions = list(), images = list(), project.name = "SeuratProject", 
    misc = list(), version = structure(list(c(4L, 0L, 4L)), class = c("package_version", 
    "numeric_version")), commands = list(), tools = list())

My main goal is to know how the TP53 is expressed across different cells in different organs. Any idea how to annotate this data?

r
• 1,695 views • link
updated by rpolicastro rpolicastro • written by Mo Mo

It's hard to give any specific information since you haven't provided any information about the data, but judging from the metadata the cell type might be present in the cell_ontology_class column. Read through the Seurat vignettes for more information on how to process and analyze the data.

• 0 views • link
written by rpolicastro rpolicastro

rpolicastro I have read all their vignettes, it looks so useless they have so many examples with various data structure. I am using Tabula, are you able to give me a more specific line or any specific place that I could check?

• 0 views • link
written by Mo Mo

Start off with their basic tutorial. Also consider reading Orchestrating Single Cell Analysis which uses an orthogonal workflow based off of bioconductor and scran (which I prefer). If you want to follow OSCA you can convert the Seurat object to a SingleCellExperiment with the below code.

library("SingleCellExperiment")

sce <- SingleCellExperiment(list(counts=GetAssayData(df, assay="RNA", slot="data")), colData=df[[]])
• 0 views • link
written by rpolicastro rpolicastro

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