External resources
<ul> <li>ex_databases: demo database `ex_databases`, which includes three sublists: `LigRec.DB`, `RecTF.DB`, and `TFTG.DB`. Each sublist consists of three columns: `source`, `target`, and `score`. In the aforementioned sublists, the `source` column represents signalling molecules such as ligands, receptors, and transcription factors, while the `target` column represents signalling molecules such as receptors, transcription factors, and target genes. The `score` column in `LigRec.DB` and `TFTG.DB` indicates the frequency of interactions occurring in the collected database, while the `score` column in `RecTF.DB` represents the predicted probabilities of interactions occurring in the collected database.</li> <li>ex_inputs: The demo data is derived from the breast cancer dataset of 10X Visiumd, which can be found at [here](https://support.10xgenomics.com/spatial-gene-expression/datasets/1.1.0/V1_Breast_Cancer_Block_A_Section_1). We analyzed this spatial transcriptomic data using Seurat (Version 4.0.2) and performed deconvolution using the RCTD method. The demo data `ex_inputs`, which includes: <p> `exprMat`: Normalized expression matrix.<br> `annoMat`: Cell type annotation matrix.<br> `locaMat`: Spatial location information matrix.<br> `ligs_of_inter`: Potential ligand lists for different cell types.<br> `recs_of_inter`: Potential receptor lists for different cell types.<br> `tgs_of_inter`: Potential target gene lists for different cell types.</p> </li> <li>unprocessed_ex_inputs: The demo data is derived from the breast cancer dataset of 10X Visiumd, which can be found at [here](https://support.10xgenomics.com/spatial-gene-expression/datasets/1.1.0/V1_Breast_Cancer_Block_A_Section_1). We analyzed this spatial transcriptomic data using Seurat (Version 4.0.2) and performed deconvolution using the RCTD method. The demo data `unprocessed_ex_inputs`, which includes: `exprMat`: Normalized expression matrix.</li> </ul> <p> `exprMat`: Unnormalized expression matrix.<br> `annoMat`: Cell type annotation matrix.<br> `locaMat`: Spatial location information matrix.</p>
ShareScore
40/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 8
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0
ScienceDex for faculty
Your academic CV and NIH biosketch
Make your CV in your school's format and your NIH biosketch from it, then download both as Word files.