ClustAssess - Tools for Assessing Clustering
A set of tools for evaluating clustering robustness using proportion of ambiguously clustered pairs (Senbabaoglu et al. (2014) <doi:10.1038/srep06207>), as well as similarity across methods and method stability using element-centric clustering comparison (Gates et al. (2019) <doi:10.1038/s41598-019-44892-y>). Additionally, this package enables stability-based parameter assessment for graph-based clustering pipelines typical in single-cell data analysis.
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softwaresinglecellrnaseqatacseqnormalizationpreprocessingdimensionreductionvisualizationqualitycontrolclusteringclassificationannotationgeneexpressiondifferentialexpressionbioinformaticsgenomicsmachine-learningparameter-optimizationrobustnesssingle-cellunsupervised-learningcpp
5.24 score 32 stars 54 scripts 687 downloadsnoisyr - Noise Quantification in High Throughput Sequencing Output
Quantifies and removes technical noise from high-throughput sequencing data. Two approaches are used, one based on the count matrix, and one using the alignment BAM files directly. Contains several options for every step of the process, as well as tools to quality check and assess the stability of output.
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4.70 score 10 stars 10 scripts 217 downloads