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Scripts used to analyse the single-cell data as presented in the manuscript

Run /1_mkfastq/mkfastq_cellplex_main.sh to generate fastq files from Illumina sequencer output using bcl2fastq2 v2.20.

Run /2_cellranger/multi_cellplex_main.sh to generate gene expression count matrices from sequencing fastq files using cellranger 7.0.0.

Run /3_count_to_seuratv4/count_to_seurat_main.sh to generate a seurat v4 object from count matrix.

Run /4_sc_p_sample/sc_p_sample_main.sh to perform a standard analysis of the data, individually. This wrapper calls a Nextflow script sc_p_sample.nf, which includes multiple steps including importing the data, QC, filtering, clustering, dimensionality reduction, and DE gene analysis. This is run in the conda environment scVelocity.yml.

Run /5_sc_multi_sample/sc_multi_sample_main.sh to integrate individual seurat objects using harmony. This wrapper calls a Nextflow script sc_multi_sample.nf, which combines the data, performs dimensionality reduction, clustering and DE gene analysis. This is run in the conda environment scVelocity.yml.

Seurat object meta columns Annotation, Sample Type, and Sample were added using Seurat v4 and standard R packages. Annotation was determined based on and in accordance with marker genes from publicly available sources.

Run /6_make_plots/make_plots_sbatch.sh to generate figures presented in the manuscript.

[1] Absolute paths are used at certain instances, which will need to be adapted, as needed.
[2] Anaconda was used to set up the necessary environments.

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We developed a human Bone-on-a-Chip (BOAC) model that integrates autologous primary immune and bone cells on native human bone substrates within a xeno-free, perfused environment. scRNA-seq profiling was performed on a human ex vivo bone tissue biopsy (reference) and two in vitro Bone-on-a-Chip samples on day 42 of cultivation.

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