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mirgff3_shiny's Introduction

mirtop

Project Status: Active – The project has reached a stable, usable state and is being actively developed. biorxiv

Command line tool to annotate with a standard naming miRNAs e isomiRs.

This tool adapt the miRNA GFF3 format agreed on here: https://github.com/miRTop/mirGFF3

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Ask question, ideas Contributors to code

Cite

http://mirtop.github.io

Contributing

Everybody is welcome to contribute, fork the devel branch and start working!

If you are interesting in miRNA or small RNA analysis, you can jump into the incubator issue pages to propose/ask or say hi:

https://github.com/miRTop/incubator/issues

About

Join the team: https://orgmanager.miguelpiedrafita.com/join/15463928

Read more: http://mirtop.github.io

Installation

Bioconda

conda install mirtop -c bioconda

PIP

pip install mirtop

develop version

Thes best solution is to install conda to get an independent enviroment.

wget http://repo.continuum.io/miniconda/Miniconda-latest-Linux-x86_64.sh

bash Miniconda-latest-Linux-x86_64.sh -b -p ~/mirtop_env

export PATH=$PATH:~/mirtop_env

conda install -c bioconda pysam pybedtools pandas biopython samtools

git clone http://github.com/miRTop/mirtop

cd mirtop

python setup.py develop

Quick start

Read complete commands at: https://mirtop.readthedocs.org

git clone mirtop
cd mirtop/data
mirtop gff --sps hsa --hairpin examples/annotate/hairpin.fa --gtf examples/annotate/hsa.gff3 -o test_out sim_isomir.bam

Output

The mirtop gff generates the GFF3 adapted format to capture miRNA variations. The output is explained here.

Contributors

Citizens

Here we cite any person who has contribute somehow to the project different than through code development and/or bioinformatic concepts.

Gianvito Urgese, Jan Oppelt(CEITEC Masaryk University, Brno, Czech Republic), Thomas Desvignes, Bastian, Kieran O'Neill (BC Cancer), Charles Reid (University of California Davis), Radhika Khetani (Harvard Chan School of Public Health), Shannan Ho Sui (Harvard Chan School of Public Health), Simonas Juzenas(CAU), Rafael Alis (Catholic University of Valencia), Aida Arcas (Instituto de Neurociencias (CSIC-UMH)), Yufei Lin (Harvard University), Victor Barrera(Harvard Chan School of Public Health), Marc Halushka (Johns Hopkins University)

mirgff3_shiny's People

Contributors

adriancbondia avatar lpantano avatar

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mirgff3_shiny's Issues

change choices values

selectInput("datadrop","metadata", choices = colnames(metadata)),

esta linea tiene que ser selectInput("datadrop","metadata", choices = ""), sino da error si tu environment esta vacio.

noise should be by default TRUE and some lines should change

if (input$noise) {

if (input$noise) {
      #Normalizamos los datos.
      dds<- DESeqDataSetFromMatrix(counts, metadata, design = ~1)
      vst<-varianceStabilizingTransformation(dds)
      #Creamos el Assay "vst" dentro del objeto SummarizedExperiment
      assays(se)[[1]] = assay(vst)
      #no mostrar nada
      # Mostramos la información en el Assay "vst"
      # head(assays(se)[["vst"]])
      }
})

remove from here degPLot

This should be in a separate place and maybe other button can activate it. It will need the isomiR ID and a button to activate that. It could be another tab, or the same tab and plot the PCA or the degPLot depending on the button used.

degPlot(dds,genes = rownames(dds)[1:12], xs = "group",log2 = FALSE)

Rowdata y gráficos

mirgff3_shiny/server.R

Lines 125 to 132 in 4c50f00

output$graph <- renderPlot({
#Creamos la variable que almacenará las filas seleccionadas.
filas5 <-input$tabla4_rows_selected
#Creamos metadata a partir de la variable se
metadata = colData(se)
#Desarrollamos los gráficos de las filas seleccionadas.
degPlot(se,genes = rownames(se)[filas5], xs = colnames(metadata),log2 = FALSE)
})

No se si había que hacer rowData una tabla interactiva. Funciona mostrando las gráfica pero no se si es posible que no muestre error en la ventana de gráficos antes de seleccionar las lineas.

correct use of degPCA

degPCA(assays(se)[[1]], metadata = colData(se), condition = columname, data = FALSE)

Progression indicator

Hola Lorena,

He añadido este contador para indicar que el programa está en activo. A ver que te parece

withProgress(message = 'Calculating',
detail = 'Hold your horses...', value = 0, {
for (i in 1:15) {
incProgress(1/15)
sum(runif(10000000,0,1))
}
})

reducir la tabla a los mas expresados

Para eliminar sequencias muy pocos expresados poner estas lineas arriba de este codigo

    keep <- rowSums(counts>0) > (ncol(counts) * 0.2)
    attributes <- attributes[keep,]
    counts <- counts[keep,]

se<-SummarizedExperiment(assays = list(raw = counts), colData = metadata, rowData = attributes)

No logro que funcione

mirgff3_shiny/server.R

Lines 71 to 80 in 4c50f00

output$pca<- renderPlot({
#Blanco y negro
degPCA(assays(dataInput())[[1]], metadata = colData(se), data = FALSE)
#observeEvent(input$upload2, {
# degPCA(assays(se)[[1]], metadata = colData(se), condition = input$datadrop, shape = input$datadrop, data = FALSE)
#})
#Diferenciado por color y forma
#metadata = colData(se)
#degPCA(assays(se)[[1]], metadata = colData(se), condition = input$datadrop, shape = input$datadrop, data = FALSE)
})

Conseguí que funcionara si dejo la variable metadata cargada en memoria por otros medios. También hace la gráfica con diferenciación de colores y demás pero no logro encotrar donde tiene que ir el "selectInput" para que se cargue el datadrop.

all the loading data has to be in isolated function

The below code needs to be in a function that run when a button is activated.

inFile1 <-input$file1

   inFile1 <-input$file1
    if(is.null(inFile1))
      return(NULL)
    #Alacenamos el archiv GFF como inFile2
    inFile2 <-input$file2
    if(is.null(inFile2))
      return(NULL)
    #Establecemos el valor de: rowdata, coldata, metadata y counts.
    colnames<- coldata_extract(inFile2$datapath)
    attributes<-atributes_extract(inFile2$datapath)
    counts<-counts_extract(inFile2$datapath, colnames)
    metadata<-coldata_extract_csv(inFile1$datapath)
    #Registramos la columna de CSV seleccionada como "seleccion"
    seleccion<-input$columna
    #Creamos el objeto SumamarizedExperiment
    se<-SummarizedExperiment(assays = list(raw = counts), colData = metadata, rowData = attributes)

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