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novoWorx

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A Next Generation Sequencing Data Management and Analytics Platform

 

“Moving your research from analysis to data interpretation”

 

As NGS continues to be one of the most popular tools in molecular biology, NGS data analysis is at the heart of making sense of your big data. Running complex bioinformatics algorithm might take away a big chunk of your time causing unnecessary delays in research progress. Here’s the good news, we have a smart solution for you.

 

Introducing novoWorx, a Next Generation Sequencing data management and analytics platform. A comprehensive multi proprietary platform from Novocraft Technologies to accelerate your research by simplifying analysis using sophisticated, fully automated solutions powered by the latest technologies. The platform uses the best practice in running millions of reads to provide clear insights from your NGS data to drive your research further.

NGS Data Management and Analytics in a Single Platform

novoWorx is a comprehensive Genome Data Management and Analytics Platform to meet the growing need for working with large sequencing datasets. novoWorx is a combination of unique proprietary software and open source modules to decipher your big data into meaningful results. This product is accessed via a web browser and requires no coding for wet lab scientists to process NGS sequencing data in a user-friendly environment.

Why novoWorx?

 

  • The only commercially available tool to offer embedded novoAlign and novoSort programs for high-throughput bioinformatics analysis.
  • A modular system for delivering full genomics pipelines.
  • Process large datasets consisting of multiple samples without programming knowledge.
  • Generates all the outputs in standard formats required for downstream/tertiary analysis by other systems.
  • Reproducible data allows accountability and continuity of processes.

Who should use novoWorx?

 

  • Academic labs
  • Small to midsize biotech companies
  • Discovery and Translational groups in Pharmaceutical companies
  • Core research labs in universities and hospitals

Single module analysis available

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FASTQ Validator

 

A module to validate single- or paired-end FASTQ file format from NGS platform.

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BAM
Validator

 

A module for BAM file format validation from NGS platform.

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Quality Check

 

A module for quality checks (presence of an adapter sequence, the base quality, fragment length distribution, etc.) on FASTQ file.

slide4

CutAdapt

 

A module for adapters or contaminants data trimming of short reads from Illumina platform.

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Trimmomatic

 

A module for adapters or contaminants data trimming of short reads from Illumina platform.

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Clone Filter

 

A module to remove PCR clone or high duplicates reads from the FASTQ reads.

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Indexing

 

A module for indexing FASTA reference genome.

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Alignment

 

A module for mapping reads to the reference genome using novoAlign.

Multiple pipelines in one platform

novoWorx has a wide range of pipelines to assist you in your research.

Metagenomics

Metagenomics Screening & Classification Pipeline

 

This pipeline performs profiling analysis of bacteria, virus and protozoa in gut/environment samples. The pair-end reads are merged into single read and the adapter and bad quality reads are removed. Then, the proportion of organisms present in the sample is classified and the comparative analysis is performed.

Metagenomics Differential Abundance Pipeline

 

This pipeline performs differential abundance analysis of bacteria, virus and protozoa in gut or environment samples. The reads are mapped to reference and are sorted using novoAlign and novoSort respectively. Next, the sorted BAM file is subjected to quantifying the abundance of each feature. The differential abundance analysis is then performed to analyze the differential expression.

Shotgun Metagenomics Squeezemeta Pipeline

 

This pipeline is a full automatic pipeline that performs taxonomic and functional analysis of metagenomics. In brief, this analysis provides information such as the organisms that are present and the metabolic processes that are involved in the community. The reads are assembled and annotated before they are subjected to a number of analysis such as homology searching, HMM search, taxonomic assignment, functional assignment, contig assignment, differential abundance analysis and the prediction of metabolic pathways.

Genomics

Single Nucleotide Variants (SNVs) Analysis Pipeline

 

This pipeline identifies the mutations or variants in the NGS dataset. The detection of genetic variants such as Single Nucleotide Variants (SNVs), insertions and deletions (INDELs), and structural variants (SVs) is one of the major objectives for the usage of variant calling. Only WGS, WES, and human amplicon dataset are applicable for this pipeline.

Reference Guided Assembly Pipeline

 

This pipeline performs the assembly of reference-based reads. The reads will be mapped to the reference selected by user using novoAlign and novoSort, and thus generating a sorted BAM file. Next, the sorted BAM file is used to mask the zero coverage region to N bases and then is subjected to novoLRPolish to generate consensus reads assembly in FASTA file. Then, the assembly annotation will be conducted.

Transcriptomics

RNA Analysis Pipeline

 

This pipeline performs known differential gene expression analysis on RNA samples. The reads are mapped to reference using novoAlign are sorted using novoSort. The sorted BAM file will be used to count the reads that are mapped to each gene. This step requires an annotation file in GTF format. Then, the differential gene expression analysis and data quality assessment are performed by sample clustering. At the same time, the differential expression of replicates analysis is also conducted where it counts the reads of expression abundance and identifies the replicates with different factors.

miRNA Analysis Pipeline

 

This pipeline performs novel and known differential gene expression analysis on micro-RNA samples. The reads are mapped to reference using novoAlign are sorted using novoSort. The sorted BAM file will be used to predict the novel miRNA and count the reads that are mapped to each gene. This step requires an annotation file in GFF3 format. Then, the differential gene expression analysis and data quality assessment are performed by sample clustering. At the same time, the differential expression of replicates analysis is also conducted where it counts the reads of expression abundance and identifies the replicates with different factors.

PacBio IsoSeq Analysis Pipeline

 

This pipeline performs the isoform abundance analysis, structural and quality annotation of isoforms of PacBio Long Reads sequencing. The reads undergo preprocessing to generate a full-length transcript sequence and are then subjected to alignment and sorting using novoAlign and novoSort respectively. The transcripts also are mapped to the GMAP reference index and the isoforms that are mapped to the reference will be collapsed. Then, the isoform abundance is calculated and the isoforms will be annotated. This step requires an annotation file in GTF format.

SARS-CoV-2

SARS-CoV-2 Screening and Classification Pipeline

 

This pipeline classifies the proportion of microbes/archaes/viruses that present in the sample and do robust comparative analysis and contamination removal for metagenomics. It receives FASTQ format file as an input file. The FASTQ reads will be mapped to the pre-build database chosen by user, followed by recentrifuge to perform comparative analysis between samples.

Reference Guided Assembly Pipeline (SARS-CoV-2 as reference)

 

This pipeline performs the assembly of reference-based reads where SARS-CoV-2 will be a reference. The reads will be mapped to SARS-CoV-2 using novoAlign and novoSort, generating a sorted BAM file. The sorted BAM file will then be subjected to novoLRPolish to generate consensus reads assembly in FASTA file.

Reference Guided Assembly Pipeline (SARS-CoV-2 and GRCh38 as reference)

 

This pipeline performs the assembly of reference-based reads where SARS-CoV-2 and GRCh38 genomes will be the references. The reads are aligned and sorted to references using novoAlign and novoSort, generating a sorted BAM file. Reads that are mapped to the interest region are extracted.In the other hand, the references are filtered to extract only the viral sequences and are used to mask the zero coverage region to N bases. The extracted region BAM file and will be further subjected to generating the consensus reads using novoLRPolish.

Microbes

Reference Guided Assembly Pipeline NEW

 

This pipeline performs the assembly of reference-based reads. The reads will be mapped to E. coli using novoAlign and novoSort, and thus generating a sorted BAM file. Next, the sorted BAM file is used to mask the zero coverage region to N bases and then is subjected to novoLRPolish to generate consensus reads assembly in FASTA file. Then, the assembly annotation will be conducted.

De Novo Assembly Pipeline NEW

 

This pipeline performs reads assembly where in this analysis, references are not required. The reads undergo preprocessing which includes quality checks and removing the bad quality reads and adapter. Next, the reads are subjected to de novo assembly, producing a set of contigs. Then the reads assembly is evaluated by computing the quality metrics and is annotated.

Microbes Hybrid Assembly Analysis Pipeline

COMING SOON

Microbes Variant Calling Analysis Pipeline

COMING SOON

16s Shotgun Metagenomics Pipeline

COMING SOON

Other customized analysis pipelines available!

 

Can’t find your desired pipelines for your research project? Worry not, contact us and our team will build one for you according to your project requirements, all bundled-up into one platform.

More features to explore

Web-enabled and secure interface with access control
Drag and drop sequencing/other files into the interface
Supports multiple samples run from a single click, no coding required to loop through large sample collection sets
Integrated genome browser
Cluster-aware (SGE support) and monitor all running, pending and completed jobs
Browse all files as reactive tables and figures (javascript)
Result file downloads

System requirements

Operating system

microsoft

Microsoft Windows 8 and above

debian-logo-1024x576

Debian Linux 7.0 and above

ubuntu

Ubuntu Linux 14.04 and above

macos

Mac OS (Sierra 10.12)

Minimum requirements

Minimum Recommended
CPU Dual core 1.8GHz OctaCore 3.2Ghz
Memory 8 GB DDR2 16GB DDR3
Storage Space 5GB for installation media*

50 GB post installation **

100GB free space ***

5GB for installation media*

50 GB post installation **

100GB free space ***

Network 500Kb/s Download Speed 1Mb/s Download Speed
Virtual Machine Environment Any Virtual Machine Environment capable of importing OVA files Oracle Virtualbox V4.2 and above (Recommended) or VMware

* Only takes into account the OVA installation media
** Post installation file size

Files Size
novoWorx

(Required)

novoWorx Databases 2GB
HG19 Reference files 18GB
*** Free space on your device or on a storage device where you will store your samples and outputs. File sizes are dependent on the data you have. This is not included in the 50GB required for novoWorx installation

Browsers

novoWorx is currently tested and built for Google Chrome Build 53.0.2785.116 m. Other browsers that are supported for novoWorx are:

  1. Chromium build 37.0.2062.120-1
  2. Vivaldi build 1.4.589.11 and above
  3. Mozilla Firefox 45.3.0
  4. Safari 5.1.10

The following browsers have been tested with novoWorx but have limited support until further releases:

  1. Microsoft Edge (All builds)
  2. Opera (All builds)

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