Moving iSEE to Viz category?

I'm not an author on iSEE, but now that there's a separate category for interactive visualization, that seems like the appropriate place for one of the most powerful SummarizedExperiment visualization tools out there!

Author: innesbre

README.md

@@ -55,7 +55,6 @@ List of software packages (and the people developing these methods) for single-c
 - [IA-SVA](https://github.com/UcarLab/iasva) - [R] - Iteratively Adjusted Surrogate Variable Analysis (IA-SVA) is a statistical framework to uncover hidden sources of variation even when these sources are correlated with the biological variable of interest. IA-SVA provides a flexible methodology to i) identify a hidden factor for unwanted heterogeneity while adjusting for all known factors; ii) test the significance of the putative hidden factor for explaining the variation in the data; and iii), if significant, use the estimated factor as an additional known factor in the next iteration to uncover further hidden factors.
 - [ICGS](https://github.com/nsalomonis/altanalyze) - [Python] - Iterative Clustering and Guide-gene Selection (Olsson et al. Nature 2016). Identify discrete, transitional and mixed-lineage states from diverse single-cell transcriptomics platforms. Integrated FASTQ pseudoalignment /quantification (Kallisto), differential expression, cell-type prediction and optional cell cycle exclusion analyses. Specialized methods for processing BAM and 10X Genomics spares matrix files. Associated single-cell splicing PSI methods (MultIPath-PSI). Apart of the AltAnalyze toolkit along with accompanying visualization methods (e.g., heatmap, t-SNE, SashimiPlots, network graphs). Easy-to-use graphical user and commandline interfaces.
 - [inferCNV](https://github.com/broadinstitute/inferCNV) - [R] - Part of the TrinityCTAT (Trinity Cancer Transcriptome Analysis Toolkit).  Provides tools for copy-number inference from single-cell RNA-seq data.
-- [iSEE](https://bioconductor.org/packages/iSEE/) - [R] - iSEE, interactive SummarizedExperiment Explorer. The iSEE package aims to provide an interactive user interface for exploring data in objects derived from the SummarizedExperiment class. Particular focus will be given to single-cell data in the SingleCellExperiment derived class. The interface is implemented with RStudio's Shiny, with a multi-panel setup for ease of navigation. Features include: dynamically linked charts, support for reproducibility by recording the exact code for every output, as well as guided tours to learn step-by-step the salient features of the user interface and of the data. A demo instance of the app is available at this address: http://shiny.imbei.uni-mainz.de:3838/iSEE.
 - [knn-smoothing](https://github.com/yanailab/knn-smoothing) - [python or R or matlab] - The algorithm is based on the observation that across protocols, the technical noise exhibited by UMI-filtered scRNA-Seq data closely follows Poisson statistics. Smoothing is performed by first identifying the nearest neighbors of each cell in a step-wise fashion, based on variance-stabilized and partially smoothed expression profiles, and then aggregating their transcript counts.
 - [MAST](https://github.com/RGLab/MAST) - [R] - Model-based Analysis of Single-cell Transcriptomics (MAST) fits a two-part, generalized linear models that are specially adapted for bimodal and/or zero-inflated single cell gene expression data.
 - [MERLoT](https://github.com/soedinglab/merlot) - [R/python] - Reconstructing complex lineage trees from scRNA-seq data using MERLoT.
@@ -254,6 +253,7 @@ List of software packages (and the people developing these methods) for single-c
 - [Ginkgo](http://qb.cshl.edu/ginkgo) - [R, C] - Ginkgo is a web application for single-cell copy-number variation analysis and visualization.
 - [Granatum](http://garmiregroup.org/granatum/app) - Granatum 🍇 is a graphical single-cell RNA-seq (scRNA-seq) analysis pipeline for genomics scientists. [Published in December 2017](https://doi.org/10.1186/s13073-017-0492-3).
 - [iS-CellR](https://github.com/immcore/iS-CellR) - iS-CellR (Interactive platform for Single-cell RNAseq) is a web-based Shiny app that integrates the Seurat package with Shiny's reactive programming framework to provide comprhensive analysis and interactive visualization of single-cell RNAseq data. [Paper](https://doi.org/10.1093/bioinformatics/bty517)
+- [iSEE](https://bioconductor.org/packages/iSEE/) - [R] - iSEE, interactive SummarizedExperiment Explorer. The iSEE package aims to provide an interactive user interface for exploring data in objects derived from the SummarizedExperiment class. Particular focus will be given to single-cell data in the SingleCellExperiment derived class. The interface is implemented with RStudio's Shiny, with a multi-panel setup for ease of navigation. Features include: dynamically linked charts, support for reproducibility by recording the exact code for every output, as well as guided tours to learn step-by-step the salient features of the user interface and of the data. A demo instance of the app is available at this address: http://shiny.imbei.uni-mainz.de:3838/iSEE.
 - [NASQAR](http://nasqar.abudhabi.nyu.edu/) - Nucleic Acid SeQuence Analysis Resource, a web-based platform that provides an intuitive interface for popular tools (like DESeq2, Seurat, and others) to perform standard downstream analysis workflows for RNAseq data. The portal hosts a number of R Shiny apps.
 - [PIVOT](https://github.com/qinzhu/PIVOT) - Platform for Interactive analysis and Visualization Of Transcriptomics data. [ref](https://doi.org/10.1186/s12859-017-1994-0)
 - [SeuratWizard](https://github.com/nasqar/SeuratWizard/) - a web-based (wizard style) interactive R Shiny application to perform guided single-cell RNA-seq data analysis and clustering. [demo](http://nasqar.abudhabi.nyu.edu/SeuratWizard)