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metaGEM Alternatives
Similar projects and alternatives to metaGEM
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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EukRep
Classification of Eukaryotic and Prokaryotic sequences from metagenomic datasets
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cookiecutter-snakemake-workflow
A cookiecutter template for Snakemake workflows
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PhaMers
A bioinformatic tool for identifying bacteriophages using machine learning and k-mers
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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GraphBin2
☯️🧬 Refined and Overlapped Binning of Metagenomic Contigs Using Assembly Graphs
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embl_gems
EMBL GEMs: A collection of GEnome-scale Models for bacterial species
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PPR-Meta
A tool for identifying phages and plasmids from metagenomic fragments using deep learning
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ViraMiner
CNN based classifier for detecting viral sequences among metagenomic contigs
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DeePhage
A tool for distinguish temperate phage-derived and virulent phage-derived sequence in metavirome data using deep learning
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VirusSeeker-Virome
VirusSeeker is a set of fully automated and modular software package designed for mining sequence data to identify sequences of microbial origin.
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RNN-VirSeeker
This is a deep learning method for identification of viral contigs with short length from metagenomic data.
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Cenote_Unlimited_Breadsticks
DEPRECATED: Discover divergent virus sequences, prune flanking cellular sequences, make basic report
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MetaRon
Metagenomic opeRon Prediction pipeline. MetaRon presents the first pipeline for the prediction of metagenomic operons without any functional or experimental data.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
metaGEM reviews and mentions
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Favorite Pipeline/Methods Figure
shameless self plug https://github.com/franciscozorrilla/metaGEM it helps to get feedback from your colleagues, especially the more design-minded ones. here's what mine looked like before feedback https://github.com/franciscozorrilla/metaGEM/wiki
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Why bother reconstructing MAGs ?
TLDR you get higher genomic resolution compared to 16S. Also consider the fact that there is a lot of strain level variation within species, which you completely miss out on without shotgun or long read sequencing. Self plugging our workflow that takes in shotgun sequencing reads, assembles MAGs and then reconstructs metabolic models that can be used for flux balance analysis simulations https://github.com/franciscozorrilla/metaGEM
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Bad tools that NEED improvement
Paper: https://academic.oup.com/nar/article/49/21/e126/6382386 GitHub: https://github.com/franciscozorrilla/metaGEM
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Advice on how to go about genome scale metabolic model construction
GitHub: https://github.com/franciscozorrilla/metaGEM Paper: https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkab815/6382386
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metaGEM: metagenomes -> genomes -> metabolic models
Hi all, I made a post a while back advertising the metaGEM pipeline for reconstructing metagenome assembled genomes (MAGs) and genome scale metabolic models (GEMs) from metagenomes. The paper has now been published in Nucleic Acids Research, I hope some of you here may find it interesting or useful for your own research! I will also leave the GitHub repo here 💻 🧬
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Deciding on genome assembly software
Have you looked into QUAST for comparison of assemblies? How big is the bacterial community? You may need to do some binning of your contigs to separate them into species specific genomes. I can suggest metaGEM (developed by me! should be online in NAR any day now) for generating MAGs for your bacterial species. Although it currently only supports short reads, it may give you an idea of what the bacterial community looks like. Maybe also look into EukCC for estimating fungal genome completeness and/or EukRep for splitting the contigs according to prokaryotic/eukaryotic provenance. You could also try estimating community composition directly from short read analysis using e.g. mOTUs2, kraken/braken, metaphlan, etc.
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Almost zero serotonin producing bacteria, wat do?
Having said that, I think unseen bio is the best one out there because they do whole metagenome shotgun sequencing instead of amplicon sequencing. They even provide you with the sequencing samples so I ran my own analysis on them here, using these methods.
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metaGEM: create your own genome scale metabolic models directly from metagenomes
Although the workflow is meant to run on a high performance computer cluster (largely due to computational resources required for assembly), many steps can be run on a standard laptop. You can find code, documentation, and tutorials on GitHub! I am always looking for ways to improve the workflow's performance, accessibility, user experience, etc. so please let me know if you have any suggestions!
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A note from our sponsor - WorkOS
workos.com | 17 Apr 2024
Stats
franciscozorrilla/metaGEM is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of metaGEM is Python.