<p>Please understand that your question is open-ended and essentially you're asking for a complete guidance through your analysis which is not feasible. I recommend to go through either the Seurat tutorials or the <a href="https://bioconductor.org/books/release/OSCA.basic/" rel="nofollow noreferrer">Bioconductor single-cell workflow</a> to learn the basics, such as typical workflows, formats of required input files etc.</p>
<p>With this knowledge you can then start finding out which sort of data are provided in GEO and start getting your analysis going. You're welcome to ask specific questions here, but please be precise and not open-ended.</p>

CC BY-SA 4.0
2023-08-07T10:25:34.903Z
2023-08-07T10:25:34.903Z
ATpoint
<p>I'm completely new to scRNA-seq analysis (and to most of Bioinformatics as well) so I apologize if this was asked a million times before.</p>
<p>I am trying to get the single cell expression data of lymph node and bone marrow from <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE159929" rel="nofollow noreferrer">this GEO entry</a></p>
<p>In Samples, there are multiple organs and accessing any of them gets me a CSV file compressed in gz format. The CSV file appears to contain the barcodes and the counts, but I do not know where to go from there. I need to annotate each cell type and I am not sure how. Seurat tutorials indicate that I have to have a few other file types which do not seem to be available in this repository. Does this mean I cannot use it, or is there a way to get this data to count/cell type just using what's available? I imagine that I don't need to perform any alignment since the rows already contain gene names.</p>
<p>Any and all guidance would be very much appreciated. Thank you so much in advance.</p>

CC BY-SA 4.0
2023-08-07T08:59:18.193Z
Welcome to the site @AhmadAl-Shaibi. My advice is to read the Seurat tutorial, attempt the calculation on your test data set and then report back with specific errors.
M__
CC BY-SA 4.0
2023-08-07T17:21:57.827Z
Please do consider revising the question. Just to mention there are close requests for this question.
M__
<rna-seq><scrnaseq><single-cell>
Using CSV files continaing scRNA-seq count data from GEO
# Using CSV files continaing scRNA-seq count data from GEO

(Asked by: username_0 on 2023-08-07)

I'm completely new to scRNA-seq analysis (and to most of Bioinformatics as well) so I apologize if this was asked a million times before.

I am trying to get the single cell expression data of lymph node and bone marrow from [this GEO entry](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE159929)

In Samples, there are multiple organs and accessing any of them gets me a CSV file compressed in gz format. The CSV file appears to contain the barcodes and the counts, but I do not know where to go from there. I need to annotate each cell type and I am not sure how. Seurat tutorials indicate that I have to have a few other file types which do not seem to be available in this repository. Does this mean I cannot use it, or is there a way to get this data to count/cell type just using what's available? I imagine that I don't need to perform any alignment since the rows already contain gene names.

Any and all guidance would be very much appreciated. Thank you so much in advance.

**Tags:** rna-seq, scrnaseq, single-cell
> **Comments:**
> **username_1**: Welcome to the site @AhmadAl-Shaibi. My advice is to read the Seurat tutorial, attempt the calculation on your test data set and then report back with specific errors.  
> **username_1**: Please do consider revising the question. Just to mention there are close requests for this question.  

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## 1 answers

### Answer by username_2 on 2023-08-07. Score: 1

Please understand that your question is open-ended and essentially you're asking for a complete guidance through your analysis which is not feasible. I recommend to go through either the Seurat tutorials or the [Bioconductor single-cell workflow](https://bioconductor.org/books/release/OSCA.basic/) to learn the basics, such as typical workflows, formats of required input files etc.

With this knowledge you can then start finding out which sort of data are provided in GEO and start getting your analysis going. You're welcome to ask specific questions here, but please be precise and not open-ended.


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