Workflows
What is a Workflow?Filters
EC-Earth3 workflow with wrappers running in MeluXina with Autosubmit v3.15.14, used to assess the effects of task aggregation on queueing times. Workflow configuration is based on the Auto-EC-Earth3's testing suite [1].
In order to reduce the size of the workflow, the /tmp directory has been deleted. Additionally, the experiment has been cleaned up with the Autosubmit clean
command. The
...
Type: Autosubmit
Creators: Pablo Goitia, Eric Ferrer, Alejandro Garcia, Genis Bonet, Gilbert Montane, Miguel Castrillo
Submitter: Pablo Goitia
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 ...
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
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 ...
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 ...
Overview
Developmental version of MSC: This github page contains developmental version of R package for Multi-scale clustering (MSC) to perform single-cell transcriptome clustering. The manuscript is currently under review.
Installation:
MEGENA needs to be installed, prior to MSC installation: library(devtools); install_github("songw01/MEGENA");
For installation for developmental github version: library(devtools); install_github("songlabcodes/MSC");
Vignettes [PBMC 8k ...
MRanalysis is an interactive R Shiny application designed for Mendelian randomization analysis.
MRanalysis
Mendelian randomization (MR) has emerged as a powerful epidemiological method for inferring causal relationships between exposures and outcomes using genome-wide association study (GWAS) summary data. By leveraging instrumental variables (IVs), such as single nucleotide polymorphisms (SNPs), MR can revolutionize our understanding of disease etiology, ...
VIsoQLR: an interactive tool for the detection, quantification and fine-tuning of isoforms using long-read sequencing
VIsoQLR is an interactive analyzer, viewer and editor for the semi-automated identification and quantification of known and novel isoforms using long-read sequencing data. VIsoQLR is tailored to thoroughly analyze mRNA expression and maturation in low-throughput splicing assays. This tool takes sequences aligned to a reference, defines consensus splice sites, and quantifies ...
Workflow for long read quality control, contamination filtering, assembly, variant calling and annotation.
Steps:
- Preprocessing of reference file : https://workflowhub.eu/workflows/1818
- LongReadSum before and after filtering (read quality control)
- Filtlong filter on quality and length
- Flye assembly
- Minimap2 mapping of reads and assembly
- Clair3 variant calling of reads
- Freebayes variant calling of assembly
- Optional Bakta annotation of genomes with no reference
- SnpEff building ...