scISR
Single-Cell Imputation using Subspace Regression
Provides an imputation pipeline for single-cell RNA sequencing data. The 'scISR' method uses a hypothesis-testing technique to identify zero-valued entries that are most likely affected by dropout events and estimates the dropout values using a subspace regression model (Tran et.al. (2022) doi:10.1038/s41598-022-06500-4).
- Version0.1.1
- R versionunknown
- LicenseLGPL-2
- LicenseLGPL-2.1
- LicenseLGPL-3
- Needs compilation?No
- scISR citation info
- Last release06/30/2022
Documentation
Team
Duc Tran
Hung Nguyen
Show author detailsRolesAuthorBang Tran
Show author detailsRolesAuthorTin Nguyen
Show author detailsRolesfnd
Insights
Last 30 days
This package has been downloaded 106 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 4 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 1,460 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Apr 24, 2024 with 18 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports6 packages
- Suggests3 packages