Transcriptional comparison between Gli1- and Ascl1- targeted neuronal stem cells (NSCs) isolated from the adult mouse hippocampus.
Tasks (01, 02, etc) subfolders contain both source code in R (Rmd files) and the rendered HTML reports.
data, processed data / annotations.01_jaeger_descriptive, scater's QC; Seurat's integration, dimensionality reduction and clustering.02_mapping, STAR + featurecounts + velocyto workflow to retrieve count matrices and velocyto's loom files.03_diff_expression, differential expression analysis (Seurat-based).04_velocyto,velocyto.R-based run.05_prediction, Machine Learning approach to predict Gli vs Ascl cells
Mapping and other computer intensive tasks were run on a multicore 64-bits linux machine. Data analysis was carried out in R v3.6.1. A shortlist of the package versions include:
cutadapt v1.16
sickle v1.33
STAR v2.6.0c
subread v1.6.2 (featurecounts)
velocyto.py v0.17.17
caret v6.0.84
R packages
package * version date lib source
biomaRt * 2.40.0 2019-05-02 [1] Bioconductor
edgeR 3.26.5 2019-06-21 [1] Bioconductor
ggplot2 * 3.2.0 2019-06-16 [1] CRAN (R 3.6.0)
igraph 1.2.4.1 2019-04-22 [1] CRAN (R 3.6.0)
irlba 2.3.3 2019-02-05 [1] CRAN (R 3.6.0)
limma 3.40.2 2019-05-17 [1] Bioconductor
Rtsne 0.15 2018-11-10 [1] CRAN (R 3.6.0)
scater * 1.12.2 2019-05-24 [1] Bioconductor
scran * 1.12.1 2019-05-27 [1] Bioconductor
sctransform 0.2.0 2019-04-12 [1] CRAN (R 3.6.0)
Seurat * 3.0.0 2019-04-15 [1] CRAN (R 3.6.0)
SingleCellExperiment * 1.6.0 2019-05-02 [1] Bioconductor
tsne 0.1-3 2016-07-15 [1] CRAN (R 3.6.0)
purrr 0.3.2 2019-03-15 [1] CRAN (R 3.6.1)
dplyr 0.8.3 2019-07-04 [1] cran (R 3.6.1)
- GSE138941 includes raw data and count tables.
- add link to the paper
- document