Wiki » History » Revision 2
Revision 1 (Katie Lennard, 07/13/2018 11:33 AM) → Revision 2/3 (Katie Lennard, 07/13/2018 01:41 PM)
# Wiki
# Project resources
This project will involve single cell RNAseq, which may have additional preprocessing/analysis requirements not currently implemented in our RNAseq pipeline at https://github.com/uct-cbio/RNAseq-pipeline. One major challenge in single cell RNA seq stems from the fact that only a small subset of genes, maybe 1000-2000 are detected (zero-inflated, noisy data). Another challenge is to get cells to cluster by type instead of by other sources of variation such as stage in the cell cycle. See https://www.10xgenomics.com/10x-university/single-cell/ for a screencast introduction.
Potentially useful resources specific to RNAseq data include:
* List of tools specifically for single cell RNAseq analysis: http://www.scrna-tools.org/
* Possible options for downstream analyses for this list include
> * Monocle (R/Bioconductor) https://bioconductor.org/packages/release/bioc/html/monocle.html
> * Seurat (R) https://satijalab.org/seurat/
> * Cellranger (mentioned by Walter who sent this support request) - GUI-based? Takes .fastq files as input https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/map/cr-counter
* RNAtor: Android app. for planning RNAseq experiments e.g. 'How many reads do I need to detect at least 1.5 fold change in transcript expression'? - https://www.biorxiv.org/content/biorxiv/early/2016/12/19/095315.full.pdf
# Project resources
This project will involve single cell RNAseq, which may have additional preprocessing/analysis requirements not currently implemented in our RNAseq pipeline at https://github.com/uct-cbio/RNAseq-pipeline. One major challenge in single cell RNA seq stems from the fact that only a small subset of genes, maybe 1000-2000 are detected (zero-inflated, noisy data). Another challenge is to get cells to cluster by type instead of by other sources of variation such as stage in the cell cycle. See https://www.10xgenomics.com/10x-university/single-cell/ for a screencast introduction.
Potentially useful resources specific to RNAseq data include:
* List of tools specifically for single cell RNAseq analysis: http://www.scrna-tools.org/
* Possible options for downstream analyses for this list include
> * Monocle (R/Bioconductor) https://bioconductor.org/packages/release/bioc/html/monocle.html
> * Seurat (R) https://satijalab.org/seurat/
> * Cellranger (mentioned by Walter who sent this support request) - GUI-based? Takes .fastq files as input https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/map/cr-counter
* RNAtor: Android app. for planning RNAseq experiments e.g. 'How many reads do I need to detect at least 1.5 fold change in transcript expression'? - https://www.biorxiv.org/content/biorxiv/early/2016/12/19/095315.full.pdf