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QIAGEN CLC Microbial Genomics Module

Analysis of microbial genomics and metagenomics made easy

The QIAGEN CLC Microbial Genomics Module offers tools and workflows for microbiome analysis, isolate characterization, functional metagenomics, resistance identification and other bioinformatics needs. Extend the capabilities of QIAGEN CLC Genomics Workbench to support the analysis of bacterial, viral and eukaryotic (fungal) genomes and metagenomes. It is also compatible with QIAGEN CLC Genomics Cloud Engine and QIAGEN CLC Genomics Server.

 

Microbiome taxonomic profiling

QIAGEN CLC Microbial Genomics Module offers unparalleled options for analyzing both amplicon and whole metagenome sequencing data. Conduct Operation Taxonomic Unit (OTU) clustering or Amplicon Sequence Variants (ASV) detection of short read amplicon data, classify long read amplicons and run taxonomic profiling on your whole metagenome samples with dedicated tools.

Aggregate results for large-scale comparative genomics studies using QIAGEN CLC’s metadata tools. Conduct metagenome analysis with preconfigured workflows and compare microbial communities across many samples.

 

Advance your microbial genome typing

Whether you are focused on public health epidemiology, clinical microbiology research or basic microbial genomics research, QIAGEN CLC Microbial Genomics Module provides state-of-the-art tools for strain typing of bacterial, fungal and viral genomes. For bacterial isolates, Type with MLST Scheme enables rapid typing and comparative genomics with globally accepted schemes from public MLST databases. Additionally, you can download and modify MLST schemes to meet the specific needs of your lab.

QIAGEN CLC Microbial Genomics Module also offers assembly- and reference-free tools, such as Find Best Matches using K-mer Spectra and Create K-mer Tree, which are useful for organisms for which MLST typing is not appropriate, such as viruses or fungi. Create SNP Tree helps you compare novel isolates to gold-standard reference genomes using a read-mapping and SNP variant calling approach. Collectively, these tools provide researchers with a comprehensive set of tools for the analysis of isolates.

 

Characterizing antimicrobial resistance

To support your fight against the worldwide threat of emerging antimicrobial-resistant (AMR) pathogens, an extensive set of tools and databases designed to work together are readily available for download and immediate use. We have developed a set of tools to detect AMR that support the analysis of assembled isolate genomes or metagenomes and the assembly-free detection of AMR markers directly from your FASTQ data.

QIAGEN CLC Microbial Genomics Module supports integrated access to popular public databases for AMR and virulence factor characterization, including the Comprehensive Antimicrobial Resistance Database (CARD) (1), ResFinder (2), Antibiotic Resistance Gene-Annotation (ARG-ANNOT) (3), NCBI Bacterial Antimicrobial Resistance Reference Gene Database (4), PointFinder (5) and Virulence Factor Database (VFDB) (6). As part of our commitment to develop novel resources for AMR research, we also offer access to databases specifically for AMR bioinformatics research: QMI-AR Nucleotide Database and QMI-AR Peptide Marker Database.

 

De novo assembly of isolates and metagenomes

If you want to explore the underlying functional classes of genes and organisms in your sample, the QIAGEN CLC Microbial Genomics Module can help. You can carry out assembly of both individual genomes and metagenomes with De Novo Assembly, including genomes from all branches of the phylogenetic tree. It has been used to assemble novel RNA viruses for the FDA ARGOS Genome Standards Project (7) and to succeed where other assemblers failed in assembling the largest eukaryotic genome ever attempted (8).

De Novo Assemble Metagenome is an assembler optimized for metagenomics samples that performs well with large, complex samples. To learn how it has contributed to large-scale metagenomics assembly, see the study where it recovered over 8000 novel genomes from SRA (9).

 

Functional metagenomics – Go beyond the assembly

QIAGEN CLC Microbial Genomics Module offers tools for deeply characterizing samples without the command line. This includes tools for binning contigs into distinct groups using Bin Pangenomes by Sequence or Bin Pangenomes by Taxonomy, which can identify plasmids and metagenomic assembled genomes (MAGs) in metagenomics data. Find Prokaryotic Genes can identify coding sequences (CDSs) for assemblies of bacterial microbiome samples. These CDSs can be annotated with Annotate CDS with BLAST or DIAMOND and characterized using Gene Ontology classifications or by identifying PFAM domains within them. These tools can be used for functional metagenomics or metatranscriptomic analysis of microbiome samples. Finally, Identify Pathways can translate EC abundance tables and differential abundance tables into MetaCyc pathways.

 

Quick and easy reference database customization

Using the right reference data is crucial for accurate microbial genomics research, whether you’re working with complex microbiome samples or isolates of specific strains. While you could download over 200,000 genomes directly from NCBI, the larger your database, the greater your need to curate and maintain the content. Database size and content also affect resource requirements and the specificity of your downstream tools. Download Custom Microbial Reference Database was designed to overcome these common metagenome analysis challenges by allowing you to download only what you need.

 

QIAseq xHyb workflows

 

Supported features

Databases

  • Access to leading Antimicrobial Resistance Gene Databases: QMI-AR, CARD, ResFinder and PointFinder
  • Access to Marker Databases derived from the QMI-AR, CARD and ARG-ANNOT resources
  • Access to common reference databases such as Greengenes, Silva and UNITE
  • Custom-built genome reference database by direct import of microbial genomes from NCBI for highly precise taxonomic assignment

Detection and identification

  • Antimicrobial resistance detection
  • Microbial gene finding
  • Identifying viral integration sites into host genome
  • Identifying resistances, acquired genes and mutations in metagenomic or isolate NGS samples
  • Find genes on finished genomes or contigs and annotate with PFAM, Gene Ontology, BLAST or DIAMOND
  • Amplicon Sequence Variants (ASV) detection
  • Biochemical pathway identification using MetaCyc

Analysis

  • Microbiome profiling
  • Taxonomic profiling of amplicon and full metagenomic data
  • De novo or reference-based OTU-clustering of 16S, 18S and ITS amplicon data
  • Classification of long read amplicon data
  • De novo assembly of metagenomes
  • Metagenome de novo assembly, binning of contigs, gene finding and functional profiling of microbiomes using PFAM, Gene Ontology and BLAST
  • User-friendly statistical tools deliver leading-class performance for alpha and beta diversity estimation, PERMANOVA analysis and differential abundance analysis
  • Pathogen typing and outbreak analysis
  • Automated identification and characterization of microbes using whole genome data – one easy-to-use workflow that reports NGS-MLST, taxonomy, closest known reference genome and antimicrobial resistance genes for microbial isolates
  • K-mer trees and whole genome SNP trees for accurate outbreak investigation and source tracking of pathogens
  • Stacked bar charts, area charts, sunburst charts and heat maps to explore and compare the taxonomic composition of samples or sample groups

 

Latest improvements

We frequently release updates and improvements such as new features or bug fixes. To get a complete overview, please visit the latest improvements page.

 

References

  1. Jia B. et al. CARD 2017: Expansion and Model-Centric Curation of the Comprehensive Antibiotic Resistance Database. Nucleic Acids Res. 2017;45:D566–73.
  2. Zankari E. et al. Identification of Acquired Antimicrobial Resistance Genes. J. Antimicrob. Chemother. 2012;67:2640–2644.
  3. Gupta SK. et al. ARG-ANNOT, a New Bioinformatic Tool to Discover Antibiotic Resistance Genes in Bacterial Genomes. Antimicrob. Agents Chemother. 2014;58:212–220.
  4. Feldgarden M. et al. Validating the NCBI AMRFinder Tool and Resistance Gene Database Using Antimicrobial Resistance Genotype-Phenotype Correlations in a Collection of NARMS Isolates. Antimicrob. Agents Chemother. 2019;A63:e00483-19.
  5. Zankari E, Allesøe R, Joensen KG, Cavaco LM, Lund O, Aarestrup FM. PointFinder: A Novel Web Tool for WGS-Based Detection of Antimicrobial Resistance Associated with Chromosomal Point Mutations in Bacterial Pathogens. J. Antimicrob. Chemother. 2017;72:2764–2768.
  6. Liu B, Zheng D, Jin Q, Chen L, Yang J. VFDB 2019: A Comparative Pathogenomic Platform with an Interactive Web Interface. Nucleic Acids Res. 2019;47:D687–D692.
  7. Sichtig H. et al. FDA-ARGOS Is a Database with Public Quality-Controlled Reference Genomes for Diagnostic Use and Regulatory Science. Nat. Commun. 2019;10(1):3313.
  8. Kuzmin DA. et al. Stepwise Large Genome Assembly Approach: A Case of Siberian Larch (Larix Sibirica Ledeb). BMC Bioinform. 2019;20(S1):37–52.
  9. Parks DH. et al. Recovery of Nearly 8,000 Metagenome-Assembled Genomes Substantially Expands the Tree of Life. Nat. Microbiol. 2017;2(11):1533–1542.

 

Downloads

Plugin Manual
Online manual Download manual
Plugin Download
Download plugin
Download CLC Microbial Genomics Module

Version

Platform support

Download

23.0.4

QIAGEN CLC Genomics Workbench


 [23.9.9, 23.0.3, 23.0.1]

23.0.0

QIAGEN CLC Genomics Workbench


 [23.0]

22.1.2

QIAGEN CLC Genomics Workbench


 [22.0.3, 22.0.2, 22.0.1, 22.0]

21.1.1

QIAGEN CLC Genomics Workbench


 [21.0.6, 21.0.5, 21.0.4, 21.0.3, 21.0.2, 21.0.1, 21.0]

20.1.1

QIAGEN CLC Genomics Workbench


 [20.0.5, 20.0.4, 20.0.3, 20.0.2, 20.0.1, 20.0]

4.8.0

QIAGEN CLC Genomics Workbench


 [12.0.4, 12.0.3]

4.5.0

QIAGEN CLC Genomics Workbench


 [12.0.2, 12.0.1]

4.1.0

QIAGEN CLC Genomics Workbench


 [12.0]

3.6.1

Biomedical Genomics Workbench


 [5.0.2, 5.0.1]

QIAGEN CLC Genomics Workbench


 [11.0.2, 11.0.1]

3.0.0

Biomedical Genomics Workbench


 [5.0.0]

QIAGEN CLC Genomics Workbench


 [11.0.0]

2.5.5

Biomedical Genomics Workbench


 [4.1.3, 4.1.2]

QIAGEN CLC Genomics Workbench


 [10.1.3, 10.1.2]

2.5.1

Biomedical Genomics Workbench


 [4.1.1, 4.1.0]

QIAGEN CLC Genomics Workbench


 [10.1.1, 10.1.0]

2.0.0

Biomedical Genomics Workbench


 [4.0]

QIAGEN CLC Genomics Workbench


 [10.0.1, 10.0]

1.6.2

Biomedical Genomics Workbench


 [3.5.4]

QIAGEN CLC Genomics Workbench


 [9.5.4]

1.6.1

Biomedical Genomics Workbench


 [3.5.3, 3.5.2, 3.5.1, 3.5]

QIAGEN CLC Genomics Workbench


 [9.5.3, 9.5.2, 9.5.1, 9.5]

1.5.1

Biomedical Genomics Workbench


 [3.0.1, 3.0]

QIAGEN CLC Genomics Workbench


 [9.0.1, 9.0]

1.4.1

Biomedical Genomics Workbench


 [2.5.4, 2.5.3]

QIAGEN CLC Genomics Workbench


 [8.5.4, 8.5.3]

1.2.2

Biomedical Genomics Workbench


 [2.5.2]

QIAGEN CLC Genomics Workbench


 [8.5.2]

1.2.1

Biomedical Genomics Workbench


 [2.5.1, 2.5]

QIAGEN CLC Genomics Workbench


 [8.5.1, 8.5]

1.0

Biomedical Genomics Workbench


 [2.1.2, 2.1.1, 2.1]

QIAGEN CLC Genomics Workbench


 [8.0.3, 8.0.2, 8.0.1, 8.0]
Server Plugin Download
Download plugin
Download CLC Microbial Genomics Server Extension

Version

Platform support

Download

23.0.4

QIAGEN CLC Genomics Server


 [23.0.1]

23.0.0

QIAGEN CLC Genomics Server


 [23.0]

22.1.2

QIAGEN CLC Genomics Server


 [22.0.3, 22.0.2, 22.0.1, 22.0]

21.1.1

QIAGEN CLC Genomics Server


 [21.0.6, 21.0.5, 21.0.4, 21.0.3, 21.0.2, 21.0.1, 21.0]

20.1.1

QIAGEN CLC Genomics Server


 [20.0.5, 20.0.4, 20.0.3, 20.0.2, 20.0.1, 20.0]

4.8.0

QIAGEN CLC Genomics Server


 [11.0.4, 11.0.3]

4.5.0

QIAGEN CLC Genomics Server


 [11.0.2, 11.0.1]

4.1.0

QIAGEN CLC Genomics Server


 [11.0]

3.6.1

Biomedical Genomics Server Solution


 [10.0.2, 10.0.1]

QIAGEN CLC Genomics Server


 [10.0.2, 10.0.1]

3.0.0

Biomedical Genomics Server Solution


 [10.0]

QIAGEN CLC Genomics Server


 [10.0.0]

2.5.5

Biomedical Genomics Server Solution


 [9.1.3, 9.1.2]

QIAGEN CLC Genomics Server


 [9.1.3, 9.1.2]

2.5.1

Biomedical Genomics Server Solution


 [9.1.1, 9.1]

QIAGEN CLC Genomics Server


 [9.1.1, 9.1.0]

2.0.0

Biomedical Genomics Server Solution


 [9.0]

QIAGEN CLC Genomics Server


 [9.0]

1.6.2

Biomedical Genomics Server Solution


 [8.5.4]

QIAGEN CLC Genomics Server


 [8.5.4]

1.6.1

Biomedical Genomics Server Solution


 [8.5.3, 8.5.2, 8.5.1, 8.5]

QIAGEN CLC Genomics Server


 [8.5.3, 8.5.2, 8.5.1, 8.5]

1.5.1

Biomedical Genomics Server Solution


 [8.0.1, 8.0]

QIAGEN CLC Genomics Server


 [8.0.1, 8.0]

1.4.1

Biomedical Genomics Server Solution


 [7.5.4, 7.5.3]

QIAGEN CLC Genomics Server


 [7.5.4, 7.5.3]

1.2.2

Biomedical Genomics Server Solution


 [7.5.2]

QIAGEN CLC Genomics Server


 [7.5.2]

1.2.1

Biomedical Genomics Server Solution


 [7.5.1, 7.5]

QIAGEN CLC Genomics Server


 [7.5.1, 7.5]

1.0

Biomedical Genomics Server Solution


 [7.0.3, 7.0.2, 7.0.1, 7.0]

QIAGEN CLC Genomics Server


 [7.0.3, 7.0.2, 7.0.1, 7.0]
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