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2018-Developmental-single-cell-RNA-sequencing

Scripts used for analysis of data in manuscript at Nature Communications. "Lineage Dynamics of Pancreatic Development at Single-Cell Resolution." Byrnes L. & Wong D. et al. https://www.nature.com/articles/s41467-018-06176-3. Nat Commun. 2018 Sep 25;9(1):3922. doi: 10.1038/s41467-018-06176-3.

Scripts description

seurat_v1.R - initialize seurat object from 10X Genomics cellranger outputs. Includes filtering, normalization, regression, variable gene identification, PCA analysis, clustering, tSNE visualization. Used for v1 datasets.

merge_seurat.R - merge two or more seurat objects into one seurat object. Perform linear regression to remove batch effects from separate objects. Used for v1 datasets.

subcluster_seurat_v1.R - Subcluster clusters of interest from Seurat object and reanalyze. Used for v1 dataset.

seurat_v2.R - initialize seurat object from 10X Genomics cellranger outputs. Includes filtering, normalization, regression, variable gene identification, and PCA analysis. Used for v2 datasets.

clustering_markers_v2.R - clustering and tSNE visualization for v2 datasets.

subcluster_seurat_v2.R - Subcluster cluster of interest from Seurat object and reanalyze. Used for v2 dataset.

seurat_object_analysis_v1_and_v2.R - downstream analysis and plotting functions for seurat object created by seurat_v1.R or seurat_v2.R.

merge_clusters.R - merge clusters that do not meet gene threshold. Used for both v1 and v2 datasets.

prepare_for_monocle_v1.R - subcluster cells of interest and perform linear regression, but not scaling in order to input normalized, regressed values into monocle with monocle_seurat_input_v1.R

monocle_seurat_input_v1.R - monocle script using seurat batch corrected values as input for v1 merged timecourse datasets.

monocle_lineage_trace.R - monocle script using nUMI as input for v2 lineage traced dataset.

monocle_object_analysis.R - downstream analysis for monocle object - BEAM and plotting.

CCA_merging_v2.R - script for merging v2 endocrine datasets with canonical correlation analysis and determining the number of CCs to include in downstream analysis.

CCA_alignment_v2.R - script for downstream alignment, clustering, tSNE visualization, and differential gene expression analysis.

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Scripts for analyzing data from manuscript under revisions

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