Here is the all package i used to perform performance testing, each package could be install following given steps.
| Name | Language | Identification of pA sites | PolyA_USE | Invidual cell matrix | Version | website |
|---|---|---|---|---|---|---|
| MAAPER | R | Modeling based on known PASs | No | No | 1.1.1 | https://github.com/Vivianstats/MAAPER |
| scAPA | Shell, R | Homer and mclust::Mclust (R package) | No | Yes | 0.1.0 | https://github.com/ElkonLab/scAPA |
| scAPAtrap | R | derfinder::regionMatrix (R package) | Yes; correct pA site | Yes | 0.1.0 | https://github.com/BMILAB/scAPAtrap |
| SCAPTURE | Shell | Homer | No | Yes | 1 | https://github.com/YangLab/SCAPTURE |
| scDaPars | python | DaPars2 | No | No | 0.1.0 | https://github.com/YiPeng-Gao/scDaPars |
| Sierra | R | fit a Guassian with NLS or MLE | No | Yes | 0.99.27 | https://github.com/VCCRI/Sierra |
| SCAPE | python | Modeling based on insert size | Yes | Yes | 1.0.0 | https://github.com/LuChenLab/SCAPE |
| polyApipe | python | Soft clipped reads with poly(A) | Yes | Yes | 0.1.0 | https://github.com/MonashBioinformaticsPlatform/polyApipe |
Requirement
- Install all packages were listed above.
- R (4.0.3)
- python (3.7.3)
- snakemake (6.6.1)
Run
snakemake -s simu_run.pyZhou et al. SCAPE: A mixture model revealing single-cell polyadenylation diversity and cellular dynamic during cell differentiation and reprogramming. Nucleic Acids Research. 2022, gkac167, https://doi.org/10.1093/nar/gkac167