ENA Reads & Assembly Submission Workflow

Originally developed within the EVORA project, this two-step Galaxy workflow streamlines submissions to the European Nucleotide Archive (ENA). The workflow first submits raw sequencing reads via the Galaxy ENA upload tool, then submits assembled sequences using the Galaxy ENA Webin CLI tool. The process is fully interactive and GUI-driven while retaining ENA’s required validations ...

📄 Generalizable machine learning models for rapid antimicrobial resistance prediction in unseen healthcare settings

This repository contains the code used for the experiments in the paper:

Generalizable machine learning models for rapid antimicrobial resistance prediction in unseen healthcare settings by Diane Duroux, Paul P. Meyer, Giovanni Visonà, and Niko Beerenwinkel.

⚙️ Install the dependencies

You can set up the project with either pip or uv.

Option A - pip:

Install the ...

The bioinformatic workflow presented here enables the analysis of RNA sequencing data obtained from human reproductive tissues in unexplained recurrent pregnancy loss (uRPL) research. This pipeline requires a sample sheet containing the sample information (example_input_data.csv) and gene expression matrices generated using the Salmon tool in the nf-core/rnaseq bioinformatics pipeline (example_count_data.csv). For more information on how to use the nf-core/rnaseq pipeline including the required ...

Workflow for Metagenomics binning from assembly.

Minimal inputs are: Identifier, assembly (fasta) and an associated sorted BAM file

Summary

• MetaBAT2 (binning)
• MaxBin2 (binning)
• SemiBin2 (binning)
• Binette (bin merging)
• EukRep (eukaryotic classification)
• CheckM2 (bin completeness and contamination)
• BUSCO (bin completeness)
• GTDB-Tk (bin taxonomic classification)
• CoverM (bin abundances)

Including: Bin annotation (workflow: https://workflowhub.eu/workflows/1170):

• Bakta

...

MAGNETO is an automated snakemake workflow dedicated to MAG (Metagenome-Assembled Genomes) reconstruction from metagenomic data.

It includes a fully-automated coassembly step informed by optimal clustering of metagenomic distances, and implements complementary genome binning strategies, for improving MAG recovery.

Key Features

• Quality Control (QC): Automatically assesses the quality and the contamination of input reads, ensuring that low-quality data are filtered out to improve downstream ...

This project is an analysis pipeline using Snakemake for RNAseq analysis in order to find differentially expressed genes. It has been widely tested on human RNA sequencing from an Illumina HiSeq but should work on most systems and many other species, provided the necessary resource files can be downloaded.

Description

This pipeline is set for paired-end data only from Illumina HiSeq output files.

The main steps of the pipeline are:

• optionnal cleaning data with ...

Soil Metagenome Pipeline

Soil Metagenome Pipeline is a modular, Nextflow DSL2 workflow for assembling, polishing, binning, annotating, and functionally characterizing complex soil metagenomes. It orchestrates state-of-the-art tools for long- and short-read metagenomics, generates high-quality MAGs, assigns taxonomy, and screens for biosynthetic gene clusters (BGCs).

What it does

• Assembles long-read metagenomes (e.g., ONT) with Flye and optionally polishes with Medaka and/or NextPolish using ...

Workflow for quality assessment of paired reads and classification using NGTax 2.0 and functional annotation using picrust2.
In addition files are exported to their respective subfolders for easier data management in a later stage.

Steps:

• Quality plots (FastQC)
• NG-TAX 2 High-throughput Amplicon Analysis
• PICRUSt 2 - Function prediction from marker gene sequences
• Export module for ngtax

Workflow for quality assessment and taxonomic classification of amplicon long read sequences. In addition files are exported to their respective subfolders for easier data management in a later stage.

Inputs are expected to be basecalled fastq files

Steps:

• NanoPlot read quality control, before and after filtering
• fastplong read quality and length filtering
• Emu abundance; species-level taxonomic abundance for full-length 16S read

Description

The Settlement Delineation and Analysis (SDA) workflows generates a settlement network from geospatial settlement data. It can process geotiff and shapefile inputs and was originally designed to operate on the World Settlement Footprint dataset. Through multiple workflow stages, a settlement network is constructed, contracted (i.e. clustered) and ultimately analysed with centrality measures. The output shapefile stores the ...