SEQUIN is an R/Shiny framework for rapid and reproducible analysis of RNA-seq data.

[1]  Carlos A. Tristan,et al.  Robotic high-throughput biomanufacturing and functional differentiation of human pluripotent stem cells , 2021, Stem cell reports.

[2]  B. Habermann,et al.  RNfuzzyApp: an R shiny RNA-seq data analysis app for visualisation, differential expression analysis, time-series clustering and enrichment analysis , 2021, F1000Research.

[3]  P. Kharchenko The triumphs and limitations of computational methods for scRNA-seq , 2021, Nature Methods.

[4]  Hsiao-Fang Sunny Sun,et al.  Gene expression analysis of combined RNA-seq experiments using a receiver operating characteristic calibrated procedure , 2021, Comput. Biol. Chem..

[5]  L. Elo,et al.  Computational strategies for single-cell multi-omics integration , 2021, Computational and structural biotechnology journal.

[6]  Vincent Rouilly,et al.  SCHNAPPs - Single Cell sHiNy APPlication(s) , 2020, bioRxiv.

[7]  Giovanni Parmigiani,et al.  ComBat-seq: batch effect adjustment for RNA-seq count data , 2020, bioRxiv.

[8]  Ryan Gosselin,et al.  Current RNA-seq methodology reporting limits reproducibility , 2019, Briefings Bioinform..

[9]  R. Ghildyal,et al.  Transcriptomic changes during TGF-β-mediated differentiation of airway fibroblasts to myofibroblasts , 2019, Scientific Reports.

[10]  Carlos A. Tristan,et al.  A Versatile Polypharmacology Platform Promotes Cytoprotection and Viability of Human Pluripotent and Differentiated Cells , 2019, bioRxiv.

[11]  Friedrich Leisch,et al.  Simple K-Medoids Partitioning Algorithm for Mixed Variable Data , 2019, Algorithms.

[12]  K. Kadota,et al.  TCC-GUI: a Shiny-based application for differential expression analysis of RNA-Seq count data , 2019, BMC Research Notes.

[13]  Klaus H. Kaestner,et al.  Comparative analysis of commercially available single-cell RNA sequencing platforms for their performance in complex human tissues , 2019, bioRxiv.

[14]  Leo Anthony Celi,et al.  The reproducibility crisis in the age of digital medicine , 2019, npj Digital Medicine.

[15]  Gary D Bader,et al.  scClustViz – Single-cell RNAseq cluster assessment and visualization , 2018, F1000Research.

[16]  Qin Ma,et al.  IRIS-EDA: An integrated RNA-Seq interpretation system for gene expression data analysis , 2019, PLoS Comput. Biol..

[17]  Luke Zappia,et al.  Clustering trees: a visualization for evaluating clusterings at multiple resolutions , 2018, bioRxiv.

[18]  Kathleen M Jagodnik,et al.  Massive mining of publicly available RNA-seq data from human and mouse , 2017, Nature Communications.

[19]  Andrew D. Rouillard,et al.  Enrichr: a comprehensive gene set enrichment analysis web server 2016 update , 2016, Nucleic Acids Res..

[20]  Charles H. Yoon,et al.  Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq , 2016, Science.

[21]  Erik Schultes,et al.  The FAIR Guiding Principles for scientific data management and stewardship , 2016, Scientific Data.

[22]  D. Melton,et al.  An improved ScoreCard to assess the differentiation potential of human pluripotent stem cells , 2015, Nature Biotechnology.

[23]  A. Regev,et al.  Spatial reconstruction of single-cell gene expression , 2015, Nature Biotechnology.

[24]  Matthew E. Ritchie,et al.  limma powers differential expression analyses for RNA-sequencing and microarray studies , 2015, Nucleic acids research.

[25]  W. Huber,et al.  Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 , 2014, Genome Biology.

[26]  S. Dudoit,et al.  Normalization of RNA-seq data using factor analysis of control genes or samples , 2014, Nature Biotechnology.

[27]  M. D. de Miguel,et al.  Pluripotent Stem Cells: Origin, Maintenance and Induction , 2010, Stem Cell Reviews and Reports.

[28]  Davis J. McCarthy,et al.  edgeR: a Bioconductor package for differential expression analysis of digital gene expression data , 2009, Bioinform..

[29]  S. Horvath,et al.  WGCNA: an R package for weighted correlation network analysis , 2008, BMC Bioinformatics.

[30]  J. Loring,et al.  Assessment of human pluripotent stem cells with PluriTest , 2014 .