diceR - Diverse Cluster Ensemble in R
Performs cluster analysis using an ensemble clustering framework, Chiu & Talhouk (2018) <doi:10.1186/s12859-017-1996-y>. Results from a diverse set of algorithms are pooled together using methods such as majority voting, K-Modes, LinkCluE, and CSPA. There are options to compare cluster assignments across algorithms using internal and external indices, visualizations such as heatmaps, and significance testing for the existence of clusters.
Last updated 10 months ago
8.00 score 34 stars 3 packages 54 scripts 662 downloadsnanostringr - Performs Quality Control, Data Normalization, and Batch Effect Correction for 'NanoString nCounter' Data
Provides quality control (QC), normalization, and batch effect correction operations for 'NanoString nCounter' data, Talhouk et al. (2016) <doi:10.1371/journal.pone.0153844>. Various metrics are used to determine which samples passed or failed QC. Gene expression should first be normalized to housekeeping genes, before a reference-based approach is used to adjust for batch effects. Raw NanoString data can be imported in the form of Reporter Code Count (RCC) files.
Last updated 5 months ago
4.48 score 5 stars 12 scripts 727 downloads