Workflows
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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 ...
Find and annotate variants in ampliconic SARS-CoV-2 Illumina sequencing data and classify samples with pangolin and nextclade
COVID-19: variation analysis on WGS PE data
This workflows performs paired end read mapping with bwa-mem followed by sensitive variant calling across a wide range of AFs with lofreq and variant annotation with snpEff 4.5covid19.
Variant calling and consensus sequence generation for batches of Illumina PE sequenced viruses with uncomplicated and stable genome structure (like e.g. Morbilliviruses).
Cloning simulation workflow for sequences present in DB
Run the GoldenGate cloning simulation for a list of constructs in a CSV file and interact with a database
steps:
input: csv file (without header) : The CSV file should contain the constraints line by line in the first column, along with their associated fragments on each line. This data will be passed to the seq_from_DB tool.
workflow_1 Parameter_Maystro
- Distribute workflow parameters on the workflow tools
- Parameters ...
COVID-19: variation analysis on ARTIC ONT data
This workflow for ONT-sequenced ARTIC data is modeled after the alignment/variant-calling steps of the ARTIC pipeline. It performs, essentially, the same steps as that pipeline’s minion command, i.e. read mapping with minimap2 and variant calling with medaka. Like the Illumina ARTIC workflow it uses ivar for primer trimming. Since ONT-sequenced reads have a much ...
This workflow takes as input a SRA_manifest from SRA Run Selector and will generate one fastq file or fastq pair of file for each experiment (concatenated multiple runs if necessary). Output will be relabelled to match the column specified by the user.
This workflow performs subtyping and consensus sequence generation for batches of Illumina PE sequenced Influenza A isolates.
Type: Galaxy
Creators: Viktoria Isabel Schwarz, Wolfgang Maier, Aaron Kolbecher, Saim Momin
Submitter: WorkflowHub Bot