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Script archive: Organoid single-cell genomic atlas uncovers human-specific features of brain development

Reusable scripts and functions archive for the paper "Organoid single-cell genomic atlas uncovers human-specific features of brain development" (https://www.nature.com/articles/s41586-019-1654-9). The preprint version is also available in biorxiv "Single-cell genomic atlas of great ape cerebral organoids uncovers human-specific features of brain development"

File description:

  • extdata: the BrainSpan RNA-seq data
  • scATAC_analysis: the scripts for preprocessing and analyzing the scATAC-seq data
    • scATAC_1_processing_singlecells.sh: the BASH commands to process the scATAC-seq data, including mapping, peak calling, liftover between species, etc.
    • scATAC_2_merge_singleCells.sh: the BASH commands to merge scATAC-seq of all cells, and do peak calling based on the merged data
    • scATAC_3_merge_species.sh: the BASH commands to create a single count matrix for scATAC-seq data from species mapped to different genomes
    • scATAC_analysis.R: script to analyze scATAC-seq data in R
  • calculateRSS.r: functions related to RSS (Reference Similarity Spectrum) calculation, including:
    • retrieveABARef: retrieve the BrainSpan reference. It requires the extdata folder to be available
    • calculateRSS: calculate RSS matrix given the input expression and reference expression matrices
    • plotFeature: the plot function (based on R-base) used in the paper for feature plots
  • differential_detection_rate.r: functions related to differential detection rate analysis, including:
    • sample_cells_ctrl_hetero: subsample cells/nuclei by controlling subtype heterogeneity and cell number differences among groups to compare
    • differential_detection_rate_test: the GLM-based ANCOVA with binomial noise to do differential detection rate test
  • differential_expression.r: functions related to differential expression analysis, including:
    • sampling_ctrl_lines_pt: get cells indices by random sampling with line number restricted and cell distribution along pseudotime controlled
    • DE_ftest_pt: function to do DE along the aligned pseudotime trajectory
  • pt_alignment.r: functions related to pseudotime alignment, including:
    • align_diff: dynamic-time-warping-based alignment
    • get_truncate_points: determine start/end of reference trajectory for truncated pseudotime alignment
    • align_pt_traj: the wrapper function to align given expression matrix and pseudotimes of cells in reference trajectory and query trajectories
    • trunc_align_pt_traj: the wrapper function for truncated alignment given expression matrix, alternative representation matrix and pseudotimes of cells in reference and query trajectories
  • preprocess_spring_given_rss.py: the Python script to generate pseudocells and prepare the input folder for SPRING

Related data

  • The raw data reported in this work can be found in ArrayExpress:
    • E-MTAB-7552: single-cell RNA-seq data based on 10x Genomics
    • E-MTAB-8234: single-cell RNA-seq data based on Fluidigm C1/Smart-seq2
    • E-MTAB-8089: single-cell ATAC-seq of human organoids
    • E-MTAB-8043: single-cell ATAC-seq of chimpanzee organoids
    • E-MTAB-8083: single-cell ATAC-seq of bonobo organoids
    • E-MTAB-8087: single-cell ATAC-seq of macaque organoids
    • E-MTAB-8228: the bulk ATAC-seq data
    • E-MTAB-8230: snRNA-seq data of the adult brain samples
    • E-MTAB-8231: bulk RNA-seq data of the adult brain samples
  • The processed scRNA-seq data is available in Mendeley Data: https://data.mendeley.com/datasets/z4jyxnx3vp/2
  • The data is available for exploration in scApeX. If there is any issue accessing the app, please try the mirror.
  • The data is also browsable in NeMO

Related publication

The 10x Genomics based scRNA-seq data of human cerebral organoids in this work was reprocessed with CSS (Cluster Similarity Spectrum, https://github.com/quadbiolab/simspec) in He et al. 2020 Genome Biol, which is also available in biorxiv.

Contact

If you have any question related to the data and the analysis, please contact Dr. Zhisong He (zhisong.he(at)bsse.ethz.ch), Prof. Barbara Treutlein (barbara.treutlein(at)bsse.ethz.ch), Prof. J. Gray Camp (grayson.camp(at)iob.ch)