About miRShiny

miRShiny is an R Shiny-based interactive pipeline for the processing and visualization of microRNA sequencing data.

Tabs/Features

• Data Upload
• Data Pre-Process
• Quality Control
• Differential Analysis
• Genomic Visualization
• Individual Feature Visualization
• Data Download
• Accuracy Evaluation
• Statistical Power Analysis

Input Data Format

Data input requires two files: Expression Data and a Conditions File.

Expression Data: A counts matrix or similar numerical matrix, with rows corresponding to features, and columns corresponding to samples.

Requirements:

1. Uploaded in tab-seperated, comma-seperated, or similar text format
2. Formatted as a matrix with dimensions [i,j], with multiple rows i and columns j
3. One row and column of sample and feature name annotation, with NO repeated names

Conditions File: A columnar text file including sample conditions and other sample annotations.

Requirements:

1. Uploaded in tab-seperated, comma-seperated, or similar text format
2. Number of sample information rows (discounting header) in each column is equal to j, the number of columns/samples in the expression data
3. Includes at minimum one complete column titled condition to identify the state of each sample
4. Exactly one header row

Optional columns: Additional column information is accepted in the Conditions File for various purposes.

• group: for subsetting the uploaded data set
• batch: for considering results between batches and correcting batch error
• normalizer: for a custom scaling vector in normalization

Screenshots

Developed With

• R
  • R Core Team (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/
• Bioconductor
  • Orchestrating high-throughput genomic analysis with Bioconductor. W. Huber, V.J. Carey, R. Gentleman,..., M. Morgan Nature Methods, 2015:12, 115. https://www.bioconductor.org/
• shiny
  • Winston Chang, Joe Cheng, JJ Allaire, Yihui Xie and Jonathan McPherson (2017). shiny: Web Application Framework for R. R package version 1.0.3. https://CRAN.R-project.org/package=shiny
• Limma
  • Ritchie, M.E., Phipson, B., Wu, D., Hu, Y., Law, C.W., Shi, W., and Smyth, G.K. (2015). limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Research 43(7), e47.
• edgeR
  • McCarthy DJ, Chen Y and Smyth GK (2012). Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Research 40, 4288-4297
• DESeq2
  • Love, M.I., Huber, W., Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 Genome Biology 15(12):550 (2014)
• ggplot2
  • H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2009.
• sva
  • Leek JT, Johnson WE, Parker HS, Fertig EJ, Jaffe AE, Storey JD, Zhang Y and Torres LC (2017). sva: Surrogate Variable Analysis. R package version 3.24.4.
• NMF
  • Renaud Gaujoux, Cathal Seoighe (2010). A flexible R package for nonnegative matrix factorization. BMC Bioinformatics 2010, 11:367.
• reader
  • Nicholas Cooper (2017). reader: Suite of Functions to Flexibly Read Data from Files. R package version 1.0.6. https://CRAN.R-project.org/package=reader
• viridis
  • Simon Garnier (2017). viridis: Default Color Maps from 'matplotlib'. R package version 0.4.0. https://CRAN.R-project.org/package=viridis
• RnaSeqSampleSize
  • Zhao S, Li C, Guo Y, Sheng Q and Shyr Y (2017). RnaSeqSampleSize: RnaSeqSampleSize. R package version 1.10.0. http://bioconductor.org/packages/release/bioc/html/RnaSeqSampleSize.html
• circlize
  • Gu, Z. (2014) circlize implements and enhances circular visualization in R. Bioinformatics. 10.1093/bioinformatics/btu393
• ComplexHeatmap
  • Gu, Z. (2016) Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. https://bioconductor.org/packages/release/bioc/html/ComplexHeatmap.html
• openxlsx
  • Alexander Walker (2017). openxlsx: Read, Write and Edit XLSX Files. R package version 4.0.17. https://CRAN.R-project.org/package=openxlsx
• heatmaply
  • Tal Galili, Alan O'Callaghan, Jonathan Sidi, Carson Sievert; heatmaply: an R package for creating interactive cluster heatmaps for online publishing, Bioinformatics, , btx657. https://doi.org/10.1093/bioinformatics/btx657