Collection of supplementary materials for the paper "Clonal analysis of murine development reveals novel positional programs directing lineage progression" (Q5162)
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Dataset published at Zenodo repository.
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Collection of supplementary materials for the paper "Clonal analysis of murine development reveals novel positional programs directing lineage progression" |
Dataset published at Zenodo repository. |
Statements
This is the collection of supplementary materials for the paper Clonal analysis of murine development reveals novel positional programs directing lineage progression (Erickson et al.). All AnnData containers have normalized expressions stored inadata.X and raw counts stored in adata.layers["counts"]. In clone2vec AnnData objects fractions of the clone within the fate ([0; 1]) are stored in adata.X, and cell counts are stored in adata.layers["counts"]. This repository contains: Plasmids.zip the archive with plasmids maps and additional sequences / CRISPR gRNAs descriptions that were used to build chimeric references, AnnDatas_control_trunk.zip the archive with AnnData objects for control mice (trunk samples) with all cells or with major domains of cells (neurons, mesenchyme, neural crest-derived, and others) + clonal embedding for all cells, AnnDatas_control_head.zip the archive with AnnData objects for control mice (head samples) with all cells or with major domains of cells (neurons, mesenchyme, and others) + clonal embedding for all cells, AnnDatas_perturbed_trunk.zip the archive with AnnData objects for control and perturbed mice (trunk samples) with all cells or with major domains of cells (neurons, mesenchyme, neural crest-derived, and others) + clonal embeddings for NC-derived cells and all cells, AnnDatas_perturbed_head.zip the archive with AnnData objects for control and perturbed mice (head samples) with all cells or with major domains of cells (neurons, mesenchyme, and others) + clonal embedding for all cells. The code for the analysis is available on GitHub. Please, feel free to contact us if you need additional data: sergey.isaev[at]meduniwien.ac.at.
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