The ultimate-level complexity workflow is one among a collection of workflows designed to address tasks up to CTF estimation. In addition to the functionalities provided by layer 0 and 1 workflows, this workflow aims to enhance the quality of both acquisition images and processing.

Quality control protocols

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Combination of methods

• CTF consensus
• New methods to compare ctf estimations
• CTF xmipp criteria (richer parameters i.e. ice detection)

Advantages: 

• Control of ...

PAIRED-END workflow. Align reads on fasta reference/assembly using bwa mem, get a consensus, variants, mutation explanations.

IMPORTANT:

• For "bcftools call" consensus step, the --ploidy file is in "Données partagées" (Shared Data) and must be imported in your history to use the worflow by providing this file (tells bcftools to consider haploid variant calling).
• SELECT THE MOST ADAPTED VADR MODEL for annotation (see vadr parameters).

SINGLE-END workflow. Align reads on fasta reference/assembly using bwa mem, get a consensus, variants, mutation explanations.

IMPORTANT:

• For "bcftools call" consensus step, the --ploidy file is in "Données partagées" (Shared Data) and must be imported in your history to use the worflow by providing this file (tells bcftools to consider haploid variant calling).
• SELECT the mot ADAPTED VADR MODEL for annotation (see vadr parameters).

This repository contains the python code to reproduce the experiments in Dłotko, Gurnari "Euler Characteristic Curves and Profiles: a stable shape invariant for big data problems"

This workflow represents the Default ML Pipeline for AutoML feature from MLme. Machine Learning Made Easy (MLme) is a novel tool that simplifies machine learning (ML) for researchers. By integrating four essential functionalities, namely data exploration, AutoML, CustomML, and visualization, MLme fulfills the diverse requirements of researchers while eliminating the need for extensive coding efforts. MLme serves as a valuable resource that empowers researchers of all technical levels to leverage ...

We present an R script that describes the workflow for analysing honey bee (Apis mellifera) wing shape. It is based on a dataset of wing images and landmark coordinates available at Zenodo: https://doi.org/10.5281/zenodo.8128010. The dataset can be used as a reference for the identification of local bees from southern Kazakhstan, which most probably belong to the subspecies Apis mellifera pomonella. It was compared with data from Nawrocka et al. (2018), available at Zenodo: ...

This workflow is designed to analyze to a multi-omics data set that comprises genome-wide DNA methylation profiles, targeted metabolomics, and behavioral data of two cohorts that participated in the ACTION Biomarker Study (ACTION, Aggression in Children: Unraveling gene-environment interplay to inform Treatment and InterventiON strategies. (Boomsma 2015, Bartels 2018, Hagenbeek 2020, van Dongen 2021, Hagenbeek 2022). The ACTION-NTR cohort consists of twins that are either longitudinally concordant ...

GERONIMO

Introduction

GERONIMO is a bioinformatics pipeline designed to conduct high-throughput homology searches of structural genes using covariance models. These models are based on the alignment of sequences and the consensus of secondary structures. The pipeline is built using Snakemake, a workflow management tool that allows for the reproducible execution of analyses on various computational platforms.

The idea for developing GERONIMO emerged from a comprehensive search for [telomerase ...

About SnakeMAGs

SnakeMAGs is a workflow to reconstruct prokaryotic genomes from metagenomes. The main purpose of SnakeMAGs is to process Illumina data from raw reads to metagenome-assembled genomes (MAGs). SnakeMAGs is efficient, easy to handle and flexible to different projects. The workflow is CeCILL licensed, implemented in Snakemake (run on multiple cores) and available ...

This repository hosts Metabolome Annotation Workflow (MAW). The workflow takes MS2 .mzML format data files as an input in R. It performs spectral database dereplication using R Package Spectra and compound database dereplication using SIRIUS OR MetFrag . Final candidate selection is done in Python using RDKit and PubChemPy.