Example of results of Integrated or Grouped Analysis for a school case

These results were generated on the Flamingo computing cluster of GR.

The datasets:

For this example, I need of 2 datasets (at least) of single-cell RNA-seq:

I reuse the sc5p_v2_hs_PBMC_1k_5 sample from 10XGenomics (found here: https://support.10xgenomics.com/single-cell-vdj/datasets/4.0.0/sc5p_v2_hs_PBMC_1k) used in the example of individual analysis of this wiki.
I use the sc5p_v2_hs_PBMC_10k_5 sample from 10XGenomics (found here: https://support.10xgenomics.com/single-cell-vdj/datasets/5.0.0/sc5p_v2_hs_PBMC_10k).

This 2 datasets are Human PBMC sample from Healthy Donors with:

Gene Expression,
BCR,
TCR,
ADT (named Feature Barcoding by 10XGenomics).

This sample contains average 1k and 10k cells and it was made by v2 chemistry technology.

Preparation of the analysis:

Make the individual analysis of the datasets:

I reuse the sc5p_v2_hs_PBMC_1k_5 sample used in the example of individual analysis of this wiki.
I made the individual analysis for the sc5p_v2_hs_PBMC_10k_5 sample. I will not detail this individual analysis but you can see the parameters file Params_indiv.yaml and the launcher file launcher_indiv.sh. (Notes: The .rda files and gene expression matrix, are not present in the github results because their sizes exceed the threshold of 50 mb of github.)

Make the ADT reference index:

I reuse the ADT reference index from the individual analysis of samples. (see Make the ADT reference index)

Make the Markfile (Additional files):

I reuse the Markfile from the individual analysis of samples. (see Make the Markfile)

General information

As the individual analysis and specified in the Pipeline phylosophy, single-cell data analysis cannot be done through a one-shot pipeline. So, the rest of the explanation will be a repetition of several phases:

Make the Configuration Parameter file
Launch of the analysis
Interpretation of Results (and Choice of Next Parameters)

Notes:

See Arborescence of all results for understand the arborecence.
The .rda files are snapshots of data at key points in the analysis.
The .rda files and gene expression matrix, are not present in the github results because their sizes exceed the threshold of 50 mb of github.
Here I present the integrated analysis and the grouped analysis separately, but we could have done both types of analysis with a single configuration file.