OMAMO: orthology-based model organism selection

Related tags

Deep Learningomamo
Overview

OMAMO: orthology-based model organism selection

workflow diagram

OMAMO is a tool that suggests the best model organism to study a biological process based on orthologous relationship between a species and human.

The user can consider several species as potential model organisms and the algorithm will rank them and report the output for a given biological process (searched as a GO term or a GO ID) is produced in the dataframe format.

Pipeline

Firstly, download the OMA dataset:

wget  https://omabrowser.org/All/OmaServer.h5  -O data/OmaServer.h5  #caution: 94GB

Secondly, using the file data/oma-species.txt find the five-letter UniProt code for species of interest. For example, consider three species Dicdyostelium discodeium , Neurospora crassa and Schizosaccharomyces pombe. Their UniProt codes are DICDI, NEUCR and SCHPO, respectively.

Then, run the code omamo_base.py for each species code (DICDI, NEUCR and SCHPO):

species="DICDI"
mkdir output; cd output

python3 ../omamo_base.py ../data/OmaServer.h5 ../data/go_positive_annotations.tsv ${species}

Once the code finished running, the outputs include ${species}2.csv files which should be combined to create a final dataframe using the code omamo_dataframe.py:

python3 omamo_dataframe.py output

where output is the name of the directory where the user wishes to save the output.

Finally, the output data frame is ready as a CSV file omamo_output_df.csv.

OMAMO Website

You can also visit the OMAMO website, where you can browse biological processes to study in 50 unicellular species.

Change log

Version 0.0.1

  • Initial release

Citation

Alina Nicheperovich, Adrian M Altenhoff, Christophe Dessimoz, Sina Majidian, "OMAMO: orthology-based model organism selection", submitted to Bioinformatics journal.

License

OMAMO is a free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

OMAMO is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details.

You should have received a copy of the GNU Lesser General Public License along with OMAMO. If not, see http://www.gnu.org/licenses/.

Owner
Dessimoz Lab
Dessimoz Lab
A Java implementation of the experiments for the paper "k-Center Clustering with Outliers in Sliding Windows"

OutliersSlidingWindows A Java implementation of the experiments for the paper "k-Center Clustering with Outliers in Sliding Windows" Dataset generatio

PaoloPellizzoni 0 Jan 05, 2022
(CVPR2021) DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation

DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation CVPR2021(oral) [arxiv] Requirements python3.7 pytorch==

W-zx-Y 85 Dec 07, 2022
This repo is for segmentation of T2 hyp regions in gliomas.

T2-Hyp-Segmentor This repo is for segmentation of T2 hyp regions in gliomas. By downloading the model from here you can use it to segment your T2w ima

1 Jan 18, 2022
Python wrappers to the C++ library SymEngine, a fast C++ symbolic manipulation library.

SymEngine Python Wrappers Python wrappers to the C++ library SymEngine, a fast C++ symbolic manipulation library. Installation Pip See License section

136 Dec 28, 2022
ICCV2021 - A New Journey from SDRTV to HDRTV.

ICCV2021 - A New Journey from SDRTV to HDRTV.

XyChen 82 Dec 27, 2022
PyTorch implementation of Barlow Twins.

Barlow Twins: Self-Supervised Learning via Redundancy Reduction PyTorch implementation of Barlow Twins. @article{zbontar2021barlow, title={Barlow Tw

Facebook Research 839 Dec 29, 2022
Object detection on multiple datasets with an automatically learned unified label space.

Simple multi-dataset detection An object detector trained on multiple large-scale datasets with a unified label space; Winning solution of E

Xingyi Zhou 407 Dec 30, 2022
Parameter Efficient Deep Probabilistic Forecasting

PEDPF Parameter Efficient Deep Probabilistic Forecasting (PEDPF) is a repository containing code to run experiments for several deep learning based pr

Olivier Sprangers 10 Jun 13, 2022
The implementation of ICASSP 2020 paper "Pixel-level self-paced learning for super-resolution"

Pixel-level Self-Paced Learning for Super-Resolution This is an official implementaion of the paper Pixel-level Self-Paced Learning for Super-Resoluti

Elon Lin 41 Dec 15, 2022
Code for our paper "SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization", ACL 2021

SimCLS Code for our paper: "SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization", ACL 2021 1. How to Install Requirements

Yixin Liu 150 Dec 12, 2022
3D cascade RCNN for object detection on point cloud

3D Cascade RCNN This is the implementation of 3D Cascade RCNN: High Quality Object Detection in Point Clouds. We designed a 3D object detection model

Qi Cai 22 Dec 02, 2022
Deep learning models for change detection of remote sensing images

Change Detection Models (Remote Sensing) Python library with Neural Networks for Change Detection based on PyTorch. ⚡ ⚡ ⚡ I am trying to build this pr

Kaiyu Li 176 Dec 24, 2022
Face2webtoon - Despite its importance, there are few previous works applying I2I translation to webtoon.

Despite its importance, there are few previous works applying I2I translation to webtoon. I collected dataset from naver webtoon 연애혁명 and tried to transfer human faces to webtoon domain.

이상윤 64 Oct 19, 2022
Repo for "TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets" at [email protected]

TableParser Repo for "TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets" at DS3 Lab 11 Dec 13, 2022

Data Consistency for Magnetic Resonance Imaging

Data Consistency for Magnetic Resonance Imaging Data Consistency (DC) is crucial for generalization in multi-modal MRI data and robustness in detectin

Dimitris Karkalousos 19 Dec 12, 2022
This is the repository for the paper "Have I done enough planning or should I plan more?"

Metacognitive Learning Tool box https://re.is.mpg.de What Is This? This repository contains two modules used to analyse metacognitive learning in huma

0 Dec 01, 2021
Implementation for our AAAI2021 paper (Entity Structure Within and Throughout: Modeling Mention Dependencies for Document-Level Relation Extraction).

SSAN Introduction This is the pytorch implementation of the SSAN model (see our AAAI2021 paper: Entity Structure Within and Throughout: Modeling Menti

benfeng 69 Nov 15, 2022
AI pipelines for Nvidia Jetson Platform

Jetson Multicamera Pipelines Easy-to-use realtime CV/AI pipelines for Nvidia Jetson Platform. This project: Builds a typical multi-camera pipeline, i.

NVIDIA AI IOT 96 Dec 23, 2022
Only a Matter of Style: Age Transformation Using a Style-Based Regression Model

Only a Matter of Style: Age Transformation Using a Style-Based Regression Model The task of age transformation illustrates the change of an individual

444 Dec 30, 2022
A Robust Unsupervised Ensemble of Feature-Based Explanations using Restricted Boltzmann Machines

A Robust Unsupervised Ensemble of Feature-Based Explanations using Restricted Boltzmann Machines Understanding the results of deep neural networks is

Johan van den Heuvel 2 Dec 13, 2021