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Allowed File types are fastq, fasta, genbank, gff, xlsx and text (txt,config,ini) and can be in gzip format.
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Empowering the Development of Genomics Expertise

EDGE COVID-19 is a tailored bioinformatics platform based on the more flexible and fully open-source EDGE Bioinformatics software (Li et al. 2017). This mini-version consists of a user-friendly GUI that drives standardized workflows for genome reference-based 'assembly' and preliminary analysis of Illumina or Nanopore data for SARS-CoV-2 genome sequencing projects. The result is a final SARS-CoV-2 genome ready for submission to GISAID and/or GenBank.

The default workflow in EDGE COVID-19 includes:
  1. data quality control (QC) and filtering,
  2. alignment of reads to the original (first available) reference genome (NC_045512.2, we removed the PolyA tail from the 3' end (33 nt)),
  3. creation of a consensus genome sequence based on the read alignments, and
  4. a Single Nucleotide Polymorphism and Variant analyses, with some detail such as location and resulting coding differences if any.

The EDGE COVID-19 platform can accommodate Illumina or ONT data, including ONT data from the SARS-CoV-2 ARTIC network sequencing protocols. Users can input/upload Illumina or Nanopore sequencing FASTQ files (and/or download from NCBI SRA). For Illumina data, default analyses include only read QC, read mapping to the reference, and SNP/variant analysis. For ONT data, the data must be demultiplexed prior to uploading; the samples will be processed individually. The SNP/variant calling is not on by default for ONT. However, other functions (e.g. de novo assembly for whole genome data) are also available for both sequencing platforms. While command line execution is possible (see here and here), the GUI provides an easy data submission and results viewing platform, with the graphical and tabular views of variant/SNP data and a genome browser to view read coverage and location of SNPs or variants, as well as the reference annotations.

This light-weight version is a Docker container, able to run on any local hardware infrastructure or in the cloud. We have tested this Docker container on laptops and cloud, using several Illumina (e.g. SRR11177792) and ONT (e.g. SRR11300652) datasets.

Note: For EDGE Bioinformatics users who would also like to use the phylogeny or read- and assembly-based taxonomy classification tools to identify all organisms that may be present within complex samples, we recommend using the original EDGE Bioinformatics platform which harbors several tools and associated (large) databases that enable such a search. In initial tests of taxonomy classification of SARS-CoV-2 samples (with no SARS-CoV-2 genomes in any of the databases), we recover SARS coronavirus and Bat Coronavirus as the nearest neighbor.

Features of EDGE

Implementation

Download & Updates

EDGE COVID-19 Docker image: location and instructions.
The Source code: LANL-Bioinformatics GitHub site.

Tutorial & Help

Publication

Chien-Chi Lo, Migun Shakya, Ryan Connor, Karen Davenport, Mark Flynn, Adán Myers y Gutiérrez, Bin Hu, Po-E Li, Elais Player Jackson, Yan Xu, Patrick S G Chain, EDGE COVID-19: A Web Platform to generate submission-ready genomes from SARS-CoV-2 sequencing efforts, Bioinformatics, 2022;, btac176, https://doi.org/10.1093/bioinformatics/btac176

This research was supported by LANL (20200732ER), by DTRA (CB10152 and CB10623) and by the DOE Office of Science (KP160101), through the National Virtual Biotechnology Laboratory, a consortium of DOE national laboratories focused on response to COVID-19, with funding provided by the Coronavirus CARES Act.

Input Your Sample

EDGE requires sequence data files in FASTQ format. EDGE accepts both paired-end and single-end sequence data files. User Guide

The Qiime2 pipeline requires sequence data files in FASTQ format and a mapping file. The sequence file is either paired-end or single-end sequences.Or directory with demultiplexed fastq files. Please see the documentation for more information.

The DETEQT is a pipeline for diagnostic targeted sequencing adjudication. Please see the documentation for more information.

The PiReT is a pipeline for Reference based Transcriptomics analysis. Please see the documentation for more information.

Input Raw Reads

Amplicon Type
Input Source
Platform

(Internet required) Input SRA accessions (comma separate for > 1 input) support studies (SRP*/ERP*/DRP*), experiments (SRX*/ERX*/DRX*), samples (SRS*/ERS*/DRS*), runs (SRR*/ERR*/DRR*), or submissions (SRA*/ERA*/DRA*). ex: SRR11241255

file
Reads Type

Sequencing Reads:

file
file Delete

and/or

file Delete
Dir
file Delete
file
| additional options |
Add Paired-end Input Add Single-end Input Add Mapping File Field
file

Your customized parameters can be used again. You can utilize the file selector above to upload a standard config file generated by EDGE bioinformatics.

Batch Project Submission

Run EDGE with Multiple projects using a tools set configuration. Click Download [Sample File] to see the example.

file

Input Metadata

Virus detail


Sample information


Choose Processes / Analyses

EDGE provides many modules to do various analyses. You can choose to run or skip a specific process. Parameters/options are provided for most of the analyses. You can click here to turn all on, expand all sections or close all sections.

Quality Trim and Filter
Stitch Paired-End Reads
Host Removal
Run Quality Trim and Filter
Quality Offset
Primer Trim Method
file
file
Trim polyA
Run Stitch PE Reads
Use joined PE reads only
Human Host Removal
file

Assembly
Annotation
Binning
Bypass Assembly And Use Pre-assembled Contigs
file
Assembler

Unicycler is an assembly pipeline for bacterial genomes. It can assemble Illumina-only read sets where it functions as a SPAdes-optimise. For the best possible assemblies, give it both Illumina reads and long reads, and it will conduct a hybrid assembly.

Bridging mode
file

LRASM is designed for long noise reads such as reads from Nanopore and it assemble fastq/fasta formatted reads using miniasm/wtdbg2/flye and use racon to perform consensus.

Algorithm
Error Correction
Preset

IDBA_UD performs well on isolates as well as metagenomes but it may not work well on very large genomes.

SPAdes performs well on isolates as well as single cell data but it may not work on larger genomes, and it takes more computational resource. PacBio CLR and Oxford Nanopore reads are used for gap closure and repeat resolution.

file
file

MEGAHIT is an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph which achieves low memory assembly.

Validation Aligner
| additional options |
Extract Unmapped/Unassembled Reads
Annotation

EDGE will use RATT to transfer the annotation from the reference genome, NC_045512.2.

Annotation Tool
Specify Kingdom
KEGG Pathway View
file

Secondary Metabolite Analysis Parameters

Taxon
Known ClusterBlast
Sub ClusterBlast
smCoG analysis
Active Site Finder
ClusterBlast
Whole-genome PFAM analysis
Detect TTA codons
Cluster-border prediction based on transcription factor binding sites (CASSIS)
| additional options |
file
Binning
Marker Gene Sets
file
CheckM

Preselected NCBI RefSeq Reference Genome
file Add
Read Aligner
Variant Call
Consensus Fasta
Lineage Assignment Mode
Lineage Abundance Prediction
| additional options |

Consensus Generation Options

Disable BAQ
Remove PCR Duplicates
Homopolymer Filter
StrandBias Filter
Extract Mapped Reads
Extract Unmapped Reads
Ploidy

  1. Read-based Taxonomy Classification

    2. EDGE will use all reads by default. You can change the behavior to use reads that are unmapped to the reference if Reference-based Analysis is on.

    Always Use All Reads
    Classification Tools
    | additional options |
    Add
  2. Contig-based Taxonomy Classification
    3. Contigs Classification

EDGE supports 5 pre-computed databases for SNP phylogeny analysis and two tree builders. FastTree is faster and RAxML is slower but more accurate.

Tree Build Method

or

Select/Add Genomes or SRA Reads: The same species or at least within the same genus are recommended.

file Add
Bootstrap

  1. Read-based Gene Family Analysis

    2. EDGE will use ShortBRED to search the reads for Antibiotic Resistance genes from ARDB and Resfams and for Virulence genes from VFDB.

    Reads Gene Family Analysis
  2. Contig-based (CDS) Gene Family Analysis

    3. EDGE will use ShortBRED to search the CDSs on the contigs for Virulence genes from VFDB.

    EDGE will use RGI (Resistance Gene Identifier) to search the CDSs on the contigs for Antibiotic Resistance genes from CARD.

    CDS Gene Family Analysis
| additional options |

a. Primer Validation
b. Primer Design
Run Primer Validation

Given a primer file, EDGE will run validation of the primer pair to the reference and/or assembled contigs, as available.

file
Maximum Mismatch
Run Primer Design

EDGE will design primers based on the assembled contigs.

Parameters

  1. Barcode Options
    2. file
  2. Reads Quality Control and Feature Table Construction
    3. Quality Offset
    Quality Control Method
  3. Sampling
    4. Auto-Adjust Sampling Depth

Parameters

Platform
Mode
| additional options |

The following parameters will affect how the Quality Calcuation derived. The four weight parameters should sum up to 1. Mouse over the label to see the notes.

Parameters

  1. Required arguments
    2. Kingdom
    file
    file
    file
    file
  2. Optional arguments
    3. Strandedness
    file

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Upload files

Max file size is 1gb and total user space up to 1gb. Allowed File types are fastq, fasta, genbank, gff, xlsx and text (txt,bed,config,ini) and can be in gzip format. Files will be kept for 7 days.

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Alternative uploading methods

Web uploader is designed to upload small files. When the sizes of uploading files are >1000MB, please use one of following options:
  • Directly copy files to user's MyUploads directory from the host OS (mounted EDGE_input directory while docker run):
      - The path is:
      /path/to/EDGE_input//MyUploads/
      - For example:
      cp /path/to/your_seq.fastq /path/to/EDGE_input//MyUploads/































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Questions? Please contact us at edge-covid19@lanl.gov.