DeepAnnotation can be used to perform genomic selection (GS), which is a promising breeding strategy for agricultural breeding. DeepAnnotation predicts phenotypes from comprehensive multi-omics functional annotations with interpretable deep learning framework. The effectiveness of DeepAnnotation has been demonstrated in predicting three pork production traits (lean meat percentage at 100 kg [LMP], loin muscle depth at 100 kg [LMD], back fat thickness at 100 kg [BF]) on a population of 1940 Duroc ...

High-throughput phenotyping is addressing the current bottleneck in phenotyping within breeding programs. Imaging tools are becoming the primary resource for improving the efficiency of phenotyping processes and providing large datasets for genomic selection approaches. The advent of AI brings new advantages by enhancing phenotyping methods using imaging, making them more accessible to breeding programs. In this context, we have developed an open Python workflow for analyzing morphology, colour ...

Documentation: https://sanjaynagi.github.io/AmpSeeker/ ...

Code for the high risk autism phenotype paper

This repository implements a fully reproducible pipeline for the autism signature project. It uses invoke tasks and a Docker container for consistent, cross-platform execution.

The entire workflow—data fetching, processing, and figure generation—can be reproduced in a few commands. Much of the code in this repo originated from [ASD ...

Introduction

samba-norovirus is an adaptation of the samba workflow for the specific needs in metabarcoding analyses of norovirus. It is a FAIR scalable workflow integrating, into a unique tool, state-of-the-art bioinformatics and statistical methods to conduct reproducible metabarcoding and eDNA analyses using Nextflow (Di Tommaso et al., 2017). SAMBA performs complete metabarcoding analysis by:

...

SynProtX

An official implementation of our research paper "SynProtX: A Large-Scale Proteomics-Based Deep Learning Model for Predicting Synergistic Anticancer Drug Combinations".

SynProtX is a deep learning model that integrates large-scale proteomics data, molecular graphs, and chemical fingerprints to predict synergistic effects of anticancer drug combinations. It provides robust ...

SAMBA is a FAIR scalable workflow integrating, into a unique tool, state-of-the-art bioinformatics and statistical methods to conduct reproducible eDNA analyses using Nextflow. SAMBA starts processing by verifying integrity of raw reads and metadata. Then all bioinformatics processing is done using commonly used procedure (QIIME 2 and DADA2) but adds new steps relying on dbOTU3 and microDecon to build high quality ASV count tables. Extended statistical analyses are also performed. Finally, SAMBA ...

Introduction

wombat-p pipelines is a bioinformatics analysis pipeline that bundles different workflow for the analysis of label-free proteomics data with the purpose of comparison and benchmarking. It allows using files from the proteomics metadata standard SDRF.

The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses ...

Click-qPCR

Ultra-simple tool for interactive qPCR data analysis developed by R and Shiny.

Read this document in Japanese (日本語版のユーザーガイドはこちら)

Overview

Click-qPCR is a user-friendly Shiny web application designed for the straightforward analysis of real-time quantitative PCR (qPCR) data.

This tool is readily accessible via a web browser at https://kubo-azu.shinyapps.io/Click-qPCR/, requiring no local installation for end-users. ...

SeuratExtend: An Enhanced Toolkit for scRNA-seq Analysis

Overview

SeuratExtend is an R package designed to provide an improved and easy-to-use toolkit for scRNA-seq analysis and visualization, built upon the Seurat object. While Seurat is a widely-used tool in the R community that offers a foundational framework for scRNA-seq analysis, it has limitations when it comes to more advanced analysis and customized visualization. SeuratExtend expands upon Seurat by offering an array of ...