Open, accessible platform for microbial bioinformatics


Pre-process

Examine and improve the read quality

Analyze

Run an analysis pipeline for your data

Explore

Run additional analysis and visualizations


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survey or shotgun metagenomics

Bacteria

viral (SARS-CoV-2)

COVID

Short read quality check

Nephele provides a pre-processing quality check pipeline for demultiplexed paired-end and single-end FASTQ files. Please see this FAQ on why you may want to run QC pipeline before you run a microbiome analysis. The Nephele QC pipeline can run a quality control check (FastQC), trim primers and/or adapters, trim and/or filter reads based on quality scores, merge read pairs, and provides summary graphs of the QC steps.

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Nanopore quality check

Nephele provides a pre-processing quality check pipeline for Oxford Nanopore Technology (ONT) long read sequences. The Nephele NanoporeQC pipeline runs a quality control check (NanoPlot), trims known or unknown primers and/or adapters (Porechop_abi), trims and/or filters reads (nanoq), and provides summary graphs of the QC steps.

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Amplicon metagenomics

Paired-end only

mothur

The mothur pipeline only operates on amplicon paired-end FASTQ data. Limited to datasets below 2GB zipped.

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Paired-end or Single-end

dada2 recommended

The DADA2 pipeline accepts amplicon single or paired-end FASTQ data, and generates sequence variants with their sample-wise abundances after removing substitution and chimera errors. The pipeline provides rarefaction plots, taxonomy barplots and a biom file for use in the Downstream Analysis pipeline. Also, see Where is QIIME2?

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DADA2 ITS

The DADA2 ITS pipeline accepts ITS amplicon FASTQ data, and generates sequence variants with their sample-wise abundances after removing substitution and chimera errors. The pipeline provides rarefaction plots, taxonomy barplots and a biom file for use in the Downstream Analysis pipeline.

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qiime2/vsearch

The QIIME2/VSEARCH 16S pipeline starts with FASTQ data and finishes with a rarefaction plot, taxonomy barplot and a biom file that can be further explored using the Downstream Analysis pipeline. It relies on VSEARCH for De novo, Open, and Closed reference clustering into OTUs. For Single-End data, it also provides the DEBLUR denoising algorithm.

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Shotgun metagenomics

Paired-end only

WGSA2 recommended

The WGSA2 pipeline uses paired-end shotgun reads to produce de novo assemblies for each sample in a metagenomic dataset and extract taxonomic and functional information about the microbial community.

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Paired-end or Single-end

WGS - bioBakery

The pipeline runs the BioBakery Whole Metagenome Shotgun (wmgx) for taxonomic profiling and functional annotation, and Visualization for Whole Metagenome Shotgun (wmgx_vis) bioBakery workflows. It is assembly-free.

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Single-end

LoRA

The long read assembly-based pipeline uses ONT or PacBio long sequence reads from metagenomic datasets, to produce longer de novo assemblies per sample, taxonomic and functional profiles and other features of the microbial community.

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Viral genomics

Paired-end or Single-end

sars-cov-2

This pipeline assembles SARS-CoV-2 genome and calls mutations from Illumina sequence data generated using a tiled multiplexed primers strategy (example: Artic protocol). Users can select from primers such as ARTIC and NEB-Varskip. Alternatively, users can upload a custom primers design (in .bed format). See more info below.

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Downstream Analysis: Diversity

You can use biom files from your 16S or ITS pipeline outputs to run the downstream analysis (DA) pipeline. Nephele's DA pipeline uses QIIME 2 to provide sample observation and taxonomic summaries and diversity analyses of an OTU table.

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Viral metagenomics: DiscoVir

The DiscoVir pipeline uses metagenome assemblies (.fasta files) and sequence alignments (.bam files) to identify viral sequences, taxonomically and functionally characterize the virome, and predict phage hosts.

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Metagenome Inference: PICRUSt2

This pipeline uses PICRUSt2 to predict the functional potential of a community based on marker gene sequencing profiles. It is compatible with the outputs from OTU-picking or denoising algorithm employed in QIIME2 and DADA2 pipelines. The output folder contains inferred genes and protein families and tables of predicted KEGG orthologs (KO), Enzymes (EC) and pathways.

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