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Overview
CZ ID integrates a variety of next-generation sequencing (NGS) data analysis tools into a single platform. Here we provide an overview of the workflow and tools implemented within pipelines used for metagenomic NGS (mNGS) analyses, antimicrobial resistance (AMR) gene detection, and viral consensus genome generation, including a pipeline for SARS-CoV-2 genome assembly.
mNGS Analyses
The CZ ID mNGS pipeline is designed to quickly identify microbes present in datasets containing random genomic sequences from mixed microbial communities. For example, a tissue sample from a patient will contain genetic material from the patient, a diversity of microbes that naturally live on the patient’s body (e.g., bacteria, fungi, and viruses) and microbes causing disease. CZ ID allows users to quickly explore these complex datasets to identify potential etiological agents and/or better understand microbiome composition. After uploading data to the CZ ID mNGS pipeline, users can view which microbes are present in their samples with just a few clicks.
Below we provide diagrams summarizing what happens with mNGS short- (Illumina) and long-read (Nanopore) data behind the scenes. Diagrams list implemented analysis tools during data processing and microbial species identification and summarize sample reports, data analyses, and download options available to users.
mNGS Illumina Pipeline Overview
Interested in mNGS analyses using short-read data? See Guide to mNGS Analysis and Illumina Pipeline Details in our Help Center.
mNGS Nanopore Pipeline Overview
Interested in mNGS analysis using long-read data?
- Read preprint describing the Nanopore mNGS pipeline and its implementation.
- See Upload and Analyze Nanopore Data guides in our Help Center.
- To learn more about the pipeline, see Nanopore Pipeline Validation or click here to view pipeline changes over time.
Antimicrobial Resistance Gene Detection
Antimicrobial resistance (AMR) is a leading cause of death around the world, highlighting the need to track and better understand AMR dynamics. CZ ID's AMR pipeline enables users to quickly identify bacterial AMR sequences in their metagenomic or whole genome sequence datasets. The pipeline implements the Resistance Gene Identifier (RGI) tool for AMR sequence detection. The RGI tool is used to compare quality controlled reads and assembled contigs against AMR references sequences from the Comprehensive Antibiotic Resistance Database (CARD).
Below is an overview of the AMR pipeline summarizing what happens with the data behind the scenes. The diagrams lists implemented analysis tools during AMR gene identification and summarizes sample reports and download options available to users.
Interested in AMR gene detection? See available resources for AMR analysis, including step-by-step guides, in our Help Center. You can also read a preprint describing the implementation of the AMR gene detection module in CZ ID and example use cases.
SARS-CoV-2 Consensus Genome Generation
Genomic data has been essential for surveillance efforts during the SARS-CoV-2 pandemic. The CZ ID SARS-CoV-2 pipeline enables users to quickly assemble consensus genomes obtained from metagenomic sequencing with spiked primer enrichment (MSSPE) or PCR-based protocols. The pipeline accepts short- and long-read data from Illumina and Nanopore sequencing platforms, respectively.
Below we provide a diagram summarizing what happens with short-read data behind the scenes, including implemented analysis tools, during SARS-CoV-2 consensus genome generation. We also summarize sample reports, data analyses, and download options available to users. Click here to see details about the workflow for long-read nanopore data, which follows the ARTIC Network’s nCoV-2019 novel coronavirus bioinformatics protocol. Note that reporting and download options are the same for both short- and long-read data.
SARS-CoV-2 Pipeline Overview for Illumina Data
Interested in assembling SARS-CoV-2 genomes? See Uploading SARS-CoV-2 Samples and SARS-CoV-2 Pipeline in our Help Center.
Viral Consensus Genome Pipeline
Virus genome-level analyses are important to inform molecular epidemiology, evolutionary genomics, and therapeutics. CZ ID's Viral Consensus Genome pipeline enables you to quickly assemble genomes for any virus in bulk. The pipeline was adapted from the SARS-CoV-2 pipeline and can be used to process Illumina data obtained through target enrichment (e.g., MSSPE), PCR, whole genome, or metagenomic sequencing methods.
Below we provide a diagram summarizing what happens with short-read data behind the scenes, including implemented analysis tools, during viral consensus genome generation. We also summarize sample reports, data analyses, and download options available to users.
Interested in assembling viral genomes? See Viral Consensus Genome Resources in our Help Center.
Want to learn more about tools implemented in CZ ID?
CZ ID provides an interactive pipeline visualization that allows you to view all of the tools implemented throughout the pipeline workflows along with their description and parameters. This visualization can be viewed on a per sample basis and will reflect any pipeline updates. Learn how to view the pipeline visualization here.
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