How to analyze public Single cell RNAseq datasets in Seurat?

[Biobarani22]

I'm trying to look through a published dataset to check for gene expression for my own project. I am having trouble finding materials to learn how to analyze single-cell RNA sequencing data on Seurat R from the GEO NCBI database. Since multiple samples such as barcodes.tsv.gz,genes.tsv.gz and matrix.mtx.gz files are there in this dataset. How to give input to seurat and analyze those multiple samples? The example data format is given below for your kind reference. Your help is much appreciated. Thanks in advance!

GEO_Accession number of this Dataset

GSE128423, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE128423 

datasets looks like this

GSM3674224_std1.barcodes.tsv.gz		GSM3674231_ctrl_16May.matrix.mtx.gz	GSM3674239_b1.genes.tsv.gz
GSM3674224_std1.genes.tsv.gz		GSM3674232_ctrl_26May.barcodes.tsv.gz	GSM3674239_b1.matrix.mtx.gz
GSM3674224_std1.matrix.mtx.gz		GSM3674232_ctrl_26May.genes.tsv.gz	GSM3674240_b2.barcodes.tsv.gz
GSM3674225_std2.barcodes.tsv.gz		GSM3674232_ctrl_26May.matrix.mtx.gz	GSM3674240_b2.genes.tsv.gz
GSM3674225_std2.genes.tsv.gz		GSM3674233_ctrl_7Jun.barcodes.tsv.gz	GSM3674240_b2.matrix.mtx.gz
GSM3674225_std2.matrix.mtx.gz		GSM3674233_ctrl_7Jun.genes.tsv.gz	GSM3674241_b3.barcodes.tsv.gz
GSM3674226_std3.barcodes.tsv.gz		GSM3674233_ctrl_7Jun.matrix.mtx.gz	GSM3674241_b3.genes.tsv.gz
GSM3674226_std3.genes.tsv.gz		GSM3674234_ctrl_8May.barcodes.tsv.gz	GSM3674241_b3.matrix.mtx.gz
GSM3674226_std3.matrix.mtx.gz		GSM3674234_ctrl_8May.genes.tsv.gz	GSM3674242_b4.barcodes.tsv.gz

[bassanio]

Follow this Vignette https://satijalab.org/seurat/articles/pbmc3k_tutorial.html

[samuel-marsh]

Hi,

Not member of dev team but hopefully can be helpful. If I understand correctly you are wondering how to import those files as Read10X expects 10X formatted files without any such file prefixes and not the actual analysis itself as @bassanio directed?

If so then one solution just using current package version is to rename those files but will need to create and move them to their own directories first (but be careful).

Alternatively, you can see a few solutions currently being discussed in #4101 to allow for easier reading in of files from GEO or other repos.

Best,
Sam

[Biobarani22]

@bassanio ,

Thank you very much. I will check it out.

[Biobarani22]

@samuel-marsh,

Thank you very much. I understand and split into separate files. worked. But another issue is while scaling it shows memory exhausted. If you have a solution, please help. Thanks once again.

Sample code is here:

data_S <- ScaleData(data_S)
Centering and scaling data matrix
Error: vector memory exhausted (limit reached?)

[samuel-marsh]

Hi,

So that issue means that the dataset/memory that R needs exceeds what is available on your computer/server/cloud. The only solution there is to select smaller portion of the data to do the analysis on or move the analysis to platform that has more memory available.

Best,
Sam

[Biobarani22]

@samuel-marsh,

Ok.understand. Thanks a lot for your valuable suggestions.