how to assign row names and colnames to a sparse matrix

Question

[bioinformatics]

Hi,

I'm performing single cell rna sequencing differential expression analyses in R using the public dataset which can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM4952363. It has 3 data files: barcodes, features, and matrix.

These are the commands I have done so far: library(Matrix) mat <- Matrix::readMM("GSM4952363_OS_1_matrix.mtx") features <- read.delim("GSM4952363_OS_1_features.tsv") barcodes <- read.delim("GSM4952363_OS_1_barcodes.tsv")

I am in the process of adding colnames (barcodes) and rownames (features) to the sparse matrix (mat) which contains the expression data, however it gives an error message.

rownames(mat) <- features

Error in dimnamesGets(x, value) : invalid dimnames given for “dgTMatrix” object

Does anyone know why I have received this error message? Please help thankyou

Answer 1

[ATpoint]

library(Matrix)

mat <- Matrix::readMM("~/Downloads/GSM4952363_OS_1_matrix.mtx.gz")
features <- read.delim("~/Downloads/GSM4952363_OS_1_features.tsv.gz",
                       header=FALSE)
barcodes <- read.delim("~/Downloads/GSM4952363_OS_1_barcodes.tsv.gz",
                       header=FALSE)

colnames(mat) <- barcodes[,1]
rownames(mat) <- features[,1]

Mind the header=FALSE because these files have no header, otherwise the first row is used as header and that then makes the files one entry short of the dimensions of mat. Also note that features has two columns, one with Ensembl gene ID and the other with gene names. Up to you what to choose.

[bioinformatics]

Ok, thankyou so much for your help.

[bioinformatics]

Do you know how I might construct my single cell experiment from this stage?

[ATpoint]

Type ?SingleCellExperiment and learn single-cell analysis via https://bioconductor.org/books/release/OSCA/

[bioinformatics]

Ok thanks, could you help me understand this first step. I've started with chapter 10 before chapter 4 for preprocessing.

Chapter 10 can be found here - http://bioconductor.org/books/3.14/OSCA.multisample/chimeric-mouse-embryo-10x-genomics.html#chimeric-mouse-embryo-10x-genomics

10.2 Data loading library(MouseGastrulationData) sce.chimera <- WTChimeraData(samples=5:10) sce.chimera

I'm confused as to what (samples=5:10) means and also what WTChimeraData is (ie. expression data or gene names etc) and since I have already loaded my data and merged the 3 files into 1 do I need to do this step?

[ATpoint]

I am not going to walk you through that book, sorry. Try and error, that is how I learned it.

[bioinformatics]

Is this a good workflow to follow? https://rpubs.com/mathetal/DEGs