Downloads provided by UsageCounts
{"references": ["Qiu, C., Cao, J., Martin, B.K., Li, T., Welsh, I.C., Srivatsan, S., Huang, X., Calderon, D., Noble, W.S., Disteche, C.M. and Murray, S.A., 2022. Systematic reconstruction of cellular trajectories across mouse embryogenesis. Nature genetics, 54(3), pp.328-341.", "Satija, R., Farrell, J.A., Gennert, D., Schier, A.F. and Regev, A., 2015. Spatial reconstruction of single-cell gene expression data. Nature biotechnology, 33(5), pp.495-502.", "Wolf, F.A., Angerer, P. and Theis, F.J., 2018. SCANPY: large-scale single-cell gene expression data analysis. Genome biology, 19(1), pp.1-5.", "Mohammed, H., Hernando-Herraez, I., Savino, A., Scialdone, A., Macaulay, I., Mulas, C., Chandra, T., Voet, T., Dean, W., Nichols, J. and Marioni, J.C., 2017. Single-cell landscape of transcriptional heterogeneity and cell fate decisions during mouse early gastrulation. Cell reports, 20(5), pp.1215-1228.", "Cheng, S., Pei, Y., He, L., Peng, G., Reinius, B., Tam, P.P., Jing, N. and Deng, Q., 2019. Single-cell RNA-seq reveals cellular heterogeneity of pluripotency transition and X chromosome dynamics during early mouse development. Cell reports, 26(10), pp.2593-2607.", "Pijuan-Sala, B., Griffiths, J.A., Guibentif, C., Hiscock, T.W., Jawaid, W., Calero-Nieto, F.J., Mulas, C., Ibarra-Soria, X., Tyser, R.C., Ho, D.L.L. and Reik, W., 2019. A single-cell molecular map of mouse gastrulation and early organogenesis. Nature, 566(7745), pp.490-495.", "Cao, J., Spielmann, M., Qiu, X., Huang, X., Ibrahim, D.M., Hill, A.J., Zhang, F., Mundlos, S., Christiansen, L., Steemers, F.J. and Trapnell, C., 2019. The single-cell transcriptional landscape of mammalian organogenesis. Nature, 566(7745), pp.496-502."]}
Combined and converted scRNA data from http://tome.gs.washington.edu/ (Qui et al. 2022), see a detailed description of the study here: https://www.nature.com/articles/s41588-022-01018-x Data were downloaded from http://tome.gs.washington.edu/ as R rds files, combined into a single Seurat object and converted into loom and AnnData (h5ad) files to be able to analyse with e.g. python scanpy package. If you use this data, please cite Mohammed et al. 2017, Cheng et al. 2019, Pijuan-Sala et al. 2019, Cao et al. 2019 and Qui et al. 2022.
RData, AnnData, Mus musculus, scanpy, scRNA, loom
RData, AnnData, Mus musculus, scanpy, scRNA, loom
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 14 | |
| downloads | 2 |

Views provided by UsageCounts
Downloads provided by UsageCounts