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This repository is home of R package uncoverappLib launching a unCOVERApp, a web application for clinical assessment and annotation of coverage gaps in target genes. Read more about unCOVERApp on biorxiv

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Prerequisites

This app requires following dependencies:

  • R >= 4.0.0

  • java installed

  • annotation files (sorted.bed.gz and sorted.bed.gz.tbi) that can be downloaded on Zenodo with getAnnotationFiles() function of uncoverappLib.

Installation

To install this package, start R and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
#BiocManager::install("uncoverappLib")     

The development version can be installed directly from Github:

install.packages("devtools")
devtools::install_github("Manuelaio/uncoverappLib")

Major informations about unCOVERApp R dependences are here .

Build Status

Introduction

The rapid spread of NGS-technology has been coupled since its beginning with development of bioinformatic tools for data analysis and interpretation. However, despite increasing accuracy of available approaches, the need to assess sequencing quality of the analysis targets at the base-pair resolution poses growing challenges especially in the clinical settings.
In diagnostics indeed, meticulous investigation of every single target base is often required to exclude that pathogenic events across the gene of interest may be missed due to uneven sequence coverage.

unCOVERApp is an interactive web-application for graphical inspection of sequence coverage within gene regions.

unCOVERApp highlights low coverage genomic positions, according to the coverage threshold specified by the user, providing dbNSFP-based annotations for clinical assessment of low coverage regions. It implements basic statistical tools such as binomial probability calculation that genomic positions are adequately covered, and maximum credible allele frequency.

Download_annotation_files

To associate low-coverage sites with functional and clinical annotations, unCOVERApp uses dbNSFP version 4.0 stored in two file:

  • sorted.bed.gz: a genomically-sorted, TABIX-indexed, BGZipped BED file containing selected columns from dbNSFP version v4.0.

  • sorted.bed.gz.tbi: TABIX-indexed file.

Those files are stored on Zenodo at following link for downloading. sorted.bed.gz encloses prediction scores (MutationAssessor, SIFT, CADD, M-CAP, Polyphen2-HVAR), allele frequencies observed in gnomAD data, dbsnp accession number, HGVS notations and clinical annotation information from ClinVar and OMIM. Loading sorted.bed.gz allows the annotation of each low coverage genomic position user-defined. . Run following commands to correctly create a unique cache for uncoverappLib using BiocFileCache package.

library(uncoverappLib)
getAnnotationFiles()

Input

As input file unCOVERApp takes:

  • a text file, with .txt extension, containing HGNC official gene name one per row

  • a text file, with .list extension, containing absolute paths to BAM files (one per row). In the output file, the first written bam file correspond to sample 1 and so forth.

For more details on working with unCOVERApp see Vignette.

Usage

Load library and set up R environment with annotation file as following. The way to launch unCOVERApp is run.uncoverapp(where="window") function.

library(uncoverappLib)
run.uncoverapp(where="window")

User can define where uncoverapp will be launched wiht where option:

  • browser option will open uncoverapp in your default browser
  • viewer option will open uncoverapp in RStudio viewer
  • window option will open uncoverapp in RStudio RStudio

For more details on working with uncoverapp see Vignette or Documentation.pdf on Github.

About

This is a read-only mirror of the git repos at https://bioconductor.org

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