Single-cell RNA-seq analysis pipeline

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Pipeline goal:

Perform single-cell RNA-seq analysis from FastQ files to cerebro file for 10XGenomics technology data.

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Available Steps:

Individual Analysis

• Alignments (Alignment_countTable_GE, Alignment_countTable_ADT, Alignment_annotations_TCR_BCR),
• QC of Droplets and filetring (Droplets_QC_GE, Filtering_GE),
• Normalization and dimension Reduction (Norm_DimRed_Eval_GE),
• Clustering, Identification of Marker Genes and Annotation of clusters (Clust_Markers_Annot_GE),
• Integration of several additional "omics" (Adding_ADT, Adding_TCR, Adding_BCR),
• Creation of a Cerebro object to help vizualisation of results (Cerebro).

Integrated Analysis of several samples

• Integration, Normalization and dimension Reduction (Int_Norm_DimRed_Eval_GE)
• Clustering, Identification of Marker Genes and Annotation of clusters (Int_Clust_Markers_Annot_GE),
• Integration of several additional "omics" (Int_Adding_ADT, Int_Adding_TCR, Int_Adding_BCR),
• Creation of a Cerebro object to help vizualisation of results (Cerebro).

Grouped Analysis (no integration) of several samples

• Merger, Normalization and dimension Reduction (Grp_Norm_DimRed_Eval_GE)
• Clustering, Identification of Marker Genes and Annotation of clusters (Grp_Clust_Markers_Annot_GE),
• Integration of several additional "omics" (Grp_Adding_ADT, Grp_Adding_TCR, Grp_Adding_BCR),
• Creation of a Cerebro object to help vizualisation of results (Cerebro).

Future Developments:

• Improve cell annotation,
• Update to CellRanger 6.0.0,
• Analysis of scATAC-seq,
• ...

See complete documentation on the wiki