scImpute Updates
Wei Vivian Li
2018-08-15
Updates
2018/08/15:
- Version 0.0.9 is released!
- More robust implementation of dimension reduction.
- Faster calculation of cell similarity.
2018/06/27:
- Version 0.0.8 is released!
- Faster implementation of dimension reduction.
2018/06/08:
- Version 0.0.7 is released!
- New option for application on TPM values.
2018/03/16:
- Version 0.0.6 is released!
- The scImpute method is published at Nature Communications.
- scImpute now supports input and output in the format of R objects (.rds).
2018/01/12:
- Version 0.0.5 is released!
- It is now possible to apply scImpute on just one cell population by setting
Kcluster = 1
.
2017/10/27:
- Version 0.0.4 is released!
- scImpute now supports multi-code parallelism.
2017/10/22:
- Version 0.0.3 is released!
- Estimation of dropout probabilities is more accurate.
- Imputation step is more robust.
scimpute()
incorporates a new parameter Kcluster
to specify the number of cell subpopulations.
scImpute
is now able to detect outlier cells.
2017/07/01:
- Version 0.0.2 is released!
- This version speeds up the first step in
scImpute
and program now completes in a few seconds when applied to a dataset with 10,000 genes and 100 cells (using single core).