### Overview

This portal hosts a number of web-based Bioinformatics analysis and visualization apps.

Users can either run apps Online or download/run on a local machine

### GitHub

https://github.com/nasqar/nasqar

### Abstract

As high-throughput sequencing applications continue to evolve, the rapid growth in quantity and variety of sequence-based data calls for the development of new software libraries and tools for data analysis and visualization. Often, effective use of these tools requires computational skills beyond those of the average researcher.

To lower this computational barrier, we have created a dynamic web-based platform, NASQAR. It provides an intuitive interface that allows users to easily and efficiently explore their data in an interactive way using popular tools for a variety of applications, including Transcriptome Data Preprocessing, RNAseq Analysis (including Single-cell RNAseq), Metagenomics, and Gene Enrichment

### Data Privacy

Although data uploaded for analysis on the online instance of NASQAR (at http://nasqar.abudhabi.nyu.edu/) is by default discarded after a users session ends, this does not guarantee total data privacy. In cases where data privacy is a concern (e.g. patient or pilot data), it is recommended that NASQAR is deployed on a local intranet for private users, or on a personal computer. A Docker image of NASQAR is publicly available through DockerHub and can be used to deploy the application seamlessly on any system with Docker installed, whether a local computer, a public internet server, or a private server (e.g. research institutions intranet).

### Run NASQAR on local computer/server (Docker)

Prerequisite: Docker (version >= 17.03.0-ce)

To run NASQAR locally on port 80, use the following docker command:

docker run -p 80:80 aymanm/nasqarall:nasqar

To run NASQAR locally on a different port (e.g. port 8083), use:

docker run -p 8083:80 aymanm/nasqarall:nasqar

Access via web-browser on http://localhost/ or http://localhost:8083/ depending on port number used.

### Apps

#### Pre-Processing

Gene Count Merger

Gene Count Merger

Launch

Merge FPKMs

mergeFPKMs

Launch

#### Bulk RNA

DESeq2 Shiny

DESeq2 Shiny

Launch

STARTApp

STARTapp

Launch

#### Other

Shaman (Metagenomics)

Shaman

Launch

DEApp (RNASeq)

DEApp

Launch

#### Single-Cell RNA

SeuratV3 Wizard

SeuratV3 Wizard

Launch

Seurat Wizard

Seurat Wizard

Launch

#### Enrichment

clusterProfiler(GSEA)

clusterProfiler(GSEA)

Launch

clusterProfiler(ORA)

clusterProfiler(ORA)

Launch

#### Epidemiology Covid-19

Tracking Covid-19

Tracking Covid-19

Launch

Coronavirus Dashboard

Coronavirus Dashboard

Launch

### Citation

Lastly, if you use any of the apps on our portal as part of a publication, please remember to add the appropriate NASQAR citation, as follows:

NASQAR: A web-based platform for High-throughput sequencing data analysis and visualization

Ayman Yousif, Nizar Drou, Jillian Rowe, Mohammed Khalfan, Kristin C. Gunsalus

bioRxiv 709980; doi: https://doi.org/10.1101/709980

Also make sure to add appropriate citation for the open source apps we are hosting which are always clearly displayed on the individual app pages or GitHub

## Data Pre-processing Tools

#### Gene Count Merger

- Merge individual raw gene counts files into one csv file

- Convert gene ids to gene names & Remove duplicate genes

- Add pseudo counts

- URLs: Github Page

Gene Count Merger

#### Merge FPKMs

- Merge individual FPKM files into one csv file.

- Convert gene ids to gene names & Remove duplicate genes

- Convert FPKMs to TPMS

- Add pseudo counts

Merge FPKMs

#### Create Samples MetaTable

- Create meta table for samples/factors/conditions

- Convenient to use with RNAseq/DEApp (below)

Create MetaTable

## RNAseq Tools

### Single Cell

#### Seurat Wizard

- R Shiny interface for Seurat single-cell analysis library developed and maintained by NYUAD CGSB Bioinformatics Core

- Seurat is an R toolkit for single cell genomics, developed and maintained by the Satija Lab at NYGC.

- URLs: Github Page

Seurat Wizard

#### SeuratV3 Wizard

- R Shiny interface for Seurat (version 3.0-alpha) single-cell analysis library developed and maintained by NYUAD CGSB Bioinformatics Core

- Seurat is an R toolkit for single cell genomics, developed and maintained by the Satija Lab at NYGC.

- URLs: Github Page

SeuratV3 Wizard

### Bulk RNA

#### DESeq2 Shiny

- An interactive web application for differential expression analysis based on DESeq2

- DESeq2: an R package for Differential gene expression analysis based on the negative binomial distribution.

- URLs: Github Page

DESeq2 Shiny

#### START App: RNAseq

- The START App: R Shiny Transcriptome Analysis Resource Tool

- A web-based RNAseq analysis and visualization resource using edgeR and limma-voom

- URLs: Github Page

STARTapp: RNA Seq
STARTapp: RNA Seq (without DESeq2)

#### DEApp

- DEApp: an interactive web application of differential expression analysis

- This app uses edgeR, limma-voom, and DESeq2

- URLs: Github Page

DEApp

## Gene Enrichment Tools

#### ClusterProfShinyGSEA (Gene Set Enrichment Analysis)

- A web-based application to perform Gene Set Enrichment Analysis (GSEA) using clusterProfiler and shiny R libraries

- This is based on clusterProfiler R package

- URLs: Github Page

ClusterProfShinyGSEA

#### ClusterProfShinyORA (Over-Representation Analysis)

- A web-based application to perform Over-Representation Analysis (ORA) using clusterProfiler and shiny R libraries

- This is based on clusterProfiler R package

- URLs: Github Page

ClusterProfShinyORA

## Metagenomics Tools

#### Shaman

- SHAMAN is a SHiny application for Metagenomic ANalysis including the normalization, the differential analysis and mutiple visualization

- Main packages: VSEARCH, DESeq2

- URLs: Github Page

Shaman

## Epidemiology Covid-19

#### Covid-19 Tracker

- This app provides up-to-date visualizations of data tracking the global spread of Coronavirus Disease 2019 (COVID-19) and easy access to the World Health Organization's daily situation reports on it

- Author: Jay Ulfelder

- URLs: Github Page

Covid-19 Tracker

#### Coronavirus Dashboard

- Coronavirus dashboard provides an overview of the 2019 Novel Coronavirus COVID-19 (2019-nCoV) epidemic.

- Author: Rami Krispin

- URLs: Github Page

Coronavirus Dashboard