Workflows

What is a Workflow?
1484 Workflows visible to you, out of a total of 1582

Generate mitochondrial assembly based on PacBio HiFi reads. Part of the VGP suite, it can be run at any time independently of the other workflows. This workflow uses MitoHiFi and a mitochondrial reference to assemble the mitochondrial genome from PacBio reads. You do not need to provide the reference yourself, only the Latin name of the species.

Type: Galaxy

Creator: VGP, Galaxy

Submitter: WorkflowHub Bot

Stable

The Spatial Transcriptomics analysis workflow for Xenium data from the PATH2XNAT project tested on the non-diseased lung dataset from 10X genomics. The analysis workflow written in R and executed in the interactive RStudio environment consists of visualizations, clustering, feature selection and cluster annotation.

Training materials elaborating on this analysis workflows can be found in this GitHub repository: https://github.com/HCGB-IGTP/PATH2XNAT/tree/main.

This workflow was developed in the ...

Type: Galaxy

Creators: None

Submitter: Myrthe van Baardwijk

This workflow performs quality and contamination control analysis on assembled contigs to assess bacterial genome quality and taxonomic assignment

Type: Galaxy

Creators: ABRomics , Pierre Marin, Clea Siguret, abromics-consortium

Submitter: WorkflowHub Bot

Short paired-end read analysis to provide quality analysis, read cleaning and taxonomy assignation directly from raw reads

Type: Galaxy

Creators: ABRomics , Pierre Marin, Clea Siguret, abromics-consortium

Submitter: WorkflowHub Bot

This workflow processes the CMO fastqs with CITE-seq-Count and include the translation step required for cellPlex processing. In parallel it processes the Gene Expresion fastqs with STARsolo, filter cells with DropletUtils and reformat all outputs to be easily used by the function 'Read10X' from Seurat.

Complete ChIP-seq analysis for single-end sequencing data. Processes raw FASTQ files through adapter removal (cutadapt), alignment to reference genome (Bowtie2), and quality filtering (MAPQ >= 30). Peak calling with MACS2 uses either a fixed extension parameter or built-in model to identify protein-DNA binding sites. Generates alignment files, peak calls, and quality metrics for downstream analysis.

Type: Galaxy

Creator: Lucille Delisle

Submitter: WorkflowHub Bot

Complete ChIP-seq analysis for paired-end sequencing data. Processes raw FASTQ files through adapter removal (cutadapt), alignment to reference genome (Bowtie2), and stringent quality filtering (MAPQ >= 30, concordant pairs only). Peak calling with MACS2 optimized for paired-end reads identifies protein-DNA binding sites. Generates alignment files, peak calls, and quality metrics for downstream analysis.

Type: Galaxy

Creator: Lucille Delisle

Submitter: WorkflowHub Bot

Stable

Colorectal-cancer-detection-using-ColoPola-dataset

Methods

We trained and tested three models from scratch (CNN, CNN_2 and EfficientFormerV2) and two pretrained models (DenseNet121 and EfficientNetV2-m) to classify the colorectal cancer using the ColoPola dataset.

ColoPola dataset

The dataset consists of 572 slices (specimens) with 20,592 images. There are 284 cancer samples and 288 normal samples. This dataset can download from Zenodo repository. ...

Type: Python

Creators: Thi-Thu-Hien Pham, Thao-Vi Nguyen, The-Hiep Nguyen, Quoc-Hung Phan, Thanh-Hai Le

Submitter: Thanh-Hai Le

DOI: 10.48546/workflowhub.workflow.1797.2

PanGIA: A universal framework for identifying association between ncRNAs and diseases

PanGIA is a deep learning model for predicting ncRNA-disease associations.

Model Architecture

Installation

conda create -n pangia python=3.11 
conda activate pangia 
pip install -r requirements.txt 

Prepare Datasets

The raw data can be downloaded from the following sources:

  • miRNA: The associations between miRNAs and diseases were obtained from the HMDD v4.0 ...

Type: Python

Creators: None

Submitter: qiankunzizairen Liu

GENome EXogenous (GENEX) sequence detection

This is a computational workflow for detecting coordinates of microbial-like or human-like sequences in eukaryotic and procaryotic reference genomes. The workflow accepts a reference genome in FASTA-format and outputs coordinates of microbial-like (human-like) regions in BED-format. The workflow builds a Bowtie2 index of the reference genome and aligns pre-computed microbial (GTDB v.214 or NCBI RefSeq release 213) or human (hg38) pseudo-reads to the ...

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