scholarly journals CancerInSilico: An R/Bioconductor package for combining mathematical and statistical modeling to simulate time course bulk and single cell gene expression data in cancer

2019 ◽  
Vol 14 (4) ◽  
pp. e1006935 ◽  
Author(s):  
Thomas D. Sherman ◽  
Luciane T. Kagohara ◽  
Raymon Cao ◽  
Raymond Cheng ◽  
Matthew Satriano ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Statistical Modeling ◽  
Gene Expression Data ◽  
Time Course ◽  
Expression Data ◽  
Bioconductor Package ◽  
Cell Gene Expression ◽  
Cell Gene

scholarly journals Putative cell type discovery from single-cell gene expression data

2020 ◽  
Vol 17 (6) ◽  
pp. 621-628 ◽  
Author(s):  
Zhichao Miao ◽  
Pablo Moreno ◽  
Ni Huang ◽  
Irene Papatheodorou ◽  
Alvis Brazma ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Gene Expression Data ◽  
Expression Data ◽  
Cell Type ◽  
Cell Gene Expression ◽  
Cell Gene

scholarly journals Robust Lineage Reconstruction from High-Dimensional Single-Cell Data

2016 ◽  
Author(s):  
Gregory Giecold ◽  
Eugenio Marco ◽  
Lorenzo Trippa ◽  
Guo-Cheng Yuan
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Gene Expression Data ◽  
Quantitative Estimate ◽  
Cell Lineage ◽  
Computational Method ◽  
Expression Data ◽  
Cell Gene Expression ◽  
Cell Data ◽  
Cell Gene

Single-cell gene expression data provide invaluable resources for systematic characterization of cellular hierarchy in multi-cellular organisms. However, cell lineage reconstruction is still often associated with significant uncertainty due to technological constraints. Such uncertainties have not been taken into account in current methods. We present ECLAIR, a novel computational method for the statistical inference of cell lineage relationships from single-cell gene expression data. ECLAIR uses an ensemble approach to improve the robustness of lineage predictions, and provides a quantitative estimate of the uncertainty of lineage branchings. We show that the application of ECLAIR to published datasets successfully reconstructs known lineage relationships and significantly improves the robustness of predictions. In conclusion, ECLAIR is a powerful bioinformatics tool for single-cell data analysis. It can be used for robust lineage reconstruction with quantitative estimate of prediction accuracy.

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