Performance evaluation of BARtab Holze et al., 2023
<p>Comparison of synthetic barcode extraction and quantification pipelines BARtab.</p> <p>tool-comp-results.tar.gz:</p> <p>Comparison of BARtab, pycashier and TimeMachine/Rewind on population-level data. </p> <p>Input data: https://figshare.com/articles/dataset/FateMap_Paper_datasets_3_Goyal_et_al_2021_Biorxiv_/22806494</p> <p> </p> <p>tools-comp-sc-results.tar.gz:</p> <p>Comparison of BARtab and FateMap/Rewind on single-cell level data.</p> <p>Input data: fastq files from https://figshare.com/articles/dataset/FateMap_Paper_datasets_2_Goyal_et_al_2021_Biorxiv_/22802888?file=40535864 and barcode.tsv.gz files from GEO GSM7434409, GSM7434410, GSM7434411, GSM7434412.</p> <p> </p> <p>Code for both analyses: https://github.com/DaneVass/bartools_manuscript_code/tree/main/tools-comparison</p>
ShareScore
36/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 4