stochprofML: Stochastic Profiling Using Maximum Likelihood Estimation in R
Amrhein L, Fuchs C (2021)
BMC Bioinformatics 22: 123.
Zeitschriftenaufsatz
| Veröffentlicht | Englisch
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Autor*in
Amrhein, Lisa;
Fuchs, ChristianeUniBi
Abstract / Bemerkung
Background
Tissues are often heterogeneous in their single-cell molecular expression, and this can govern the regulation of cell fate. For the understanding of development and disease, it is important to quantify heterogeneity in a given tissue.
Results
We present the R package stochprofML which uses the maximum likelihood principle to parameterize heterogeneity from the cumulative expression of small random pools of cells. We evaluate the algorithm’s performance in simulation studies and present further application opportunities.
Conclusion
Stochastic profiling outweighs the necessary demixing of mixed samples with a saving in experimental cost and effort and less measurement error. It offers possibilities for parameterizing heterogeneity, estimating underlying pool compositions and detecting differences between cell populations between samples.
Erscheinungsjahr
2021
Zeitschriftentitel
BMC Bioinformatics
Band
22
Art.-Nr.
123
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Open-Access-Publikationskosten wurden durch die Universität Bielefeld gefördert.
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https://pub.uni-bielefeld.de/record/2944735
Zitieren
Amrhein L, Fuchs C. stochprofML: Stochastic Profiling Using Maximum Likelihood Estimation in R. BMC Bioinformatics. 2021;22: 123.
Amrhein, L., & Fuchs, C. (2021). stochprofML: Stochastic Profiling Using Maximum Likelihood Estimation in R. BMC Bioinformatics, 22, 123. https://doi.org/10.1186/s12859-021-03970-7
Amrhein, Lisa, and Fuchs, Christiane. 2021. “stochprofML: Stochastic Profiling Using Maximum Likelihood Estimation in R”. BMC Bioinformatics 22: 123.
Amrhein, L., and Fuchs, C. (2021). stochprofML: Stochastic Profiling Using Maximum Likelihood Estimation in R. BMC Bioinformatics 22:123.
Amrhein, L., & Fuchs, C., 2021. stochprofML: Stochastic Profiling Using Maximum Likelihood Estimation in R. BMC Bioinformatics, 22: 123.
L. Amrhein and C. Fuchs, “stochprofML: Stochastic Profiling Using Maximum Likelihood Estimation in R”, BMC Bioinformatics, vol. 22, 2021, : 123.
Amrhein, L., Fuchs, C.: stochprofML: Stochastic Profiling Using Maximum Likelihood Estimation in R. BMC Bioinformatics. 22, : 123 (2021).
Amrhein, Lisa, and Fuchs, Christiane. “stochprofML: Stochastic Profiling Using Maximum Likelihood Estimation in R”. BMC Bioinformatics 22 (2021): 123.
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