Hi Everyone, 

I am a newbie in processing scRNA-Seq data and I am trying to understand a Seurat Object. 
Here's a single cell dataset deposited on NCBI GEO: GSE158130

```
str(obj)

Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
  ..@ i       : int [1:2110714] 25 26 28 30 32 112 113 114 124 127 ...
  ..@ p       : int [1:1177] 0 2014 4094 6011 8780 11407 14821 17657 19653 20675 ...
  ..@ Dim     : int [1:2] 27044 1176
  ..@ Dimnames:List of 2
  .. ..$ : chr [1:27044] "1/2-SBSRNA4" "5S_rRNA" "5_8S_rRNA" "7M1-2;OR2F1" ...
  .. ..$ : chr [1:1176] "WSJ0005001" "WSJ0005002" "WSJ0005003" "WSJ0005004" ...
  ..@ x       : num [1:2110714] 1 1 2 1 1 1 1 1 1 1 ...
  ..@ factors : list()
```

What I understand from this object:
- @Dim provides the dimensionality of this dataset is 27,044 (genes) x 1176 (cells)
- @Dimnames slot provides names for genes and cells.

I have the following questions:
 1. What data does slot @i, @p and @x show?
 2. Could we determine if QC, normalization and dimensionality reduction methods have been applied to the data by looking at the object?
 3. This dataset also provides 2 additional files - `GSE158130_cellID_barcode_map.txt` and `GSE158130_SK-N-SH_counts.txt`. I am not sure how to use these files and what should be my next steps.


Any help is appreciated here.

Thanks.



This isn't a Seurat object, but rather a sparse matrix from the `Matrix` library. `@x` are all of the non-zero counts. `@i` are the index positions column-wise of non-zero values. `@p` is a cumulative sum of the number of non-zero values in each column.

`GSE158130_SK-N-SH_counts.txt` is the same matrix but in csv format. `GSE158130_cellID_barcode_map.txt` has some metadata about each cell, such as the assigned cell-id, corresponding cell barcode, patient ID, etc.

From this data alone you can't tell how the data was processed. You'll need to look at the methods from the paper.