https://github.com/cometsong/ma-genta

Targeted Probe Design Pipeline. Using mWGS genome bin clusters, prokka annotation predictions, and blast+ databases for generation, processing and filtering probe sequences.
https://github.com/cometsong/ma-genta

annotation bioinformatics genome microbes microbiome ncbi-blast pipeline predictors probe sequence targeted

Last synced: about 2 months ago
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Targeted Probe Design Pipeline. Using mWGS genome bin clusters, prokka annotation predictions, and blast+ databases for generation, processing and filtering probe sequences.

• Host: GitHub
• URL: https://github.com/cometsong/ma-genta
• Owner: cometsong
• License: mit
• Created: 2019-05-29T20:26:46.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2020-11-25T19:23:08.000Z (about 4 years ago)
• Last Synced: 2023-10-20T19:00:43.073Z (about 1 year ago)
• Topics: annotation, bioinformatics, genome, microbes, microbiome, ncbi-blast, pipeline, predictors, probe, sequence, targeted
• Language: Python
• Homepage:
• Size: 18.5 MB
• Stars: 1
• Watchers: 2
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# MA-GenTA

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## Abstract:

Current sequencing-based methods for profiling microbial communities rely on marker gene (e.g. 16S rRNA) or metagenome shotgun sequencing (mWGS) analysis. We present a quantitative, straightforward, cost-effective method for microbiome profiling that combines desirable features of both approaches termed MA‑GenTA: Microbial Abundances from Genome Tagged Analysis. MA-GenTA employs highly multiplexed oligonucleotide probes designed from reference genomes in a pooled primer-extension reaction during library construction to derive relative abundance data. To test the utility of the MA-GenTA assay, probes were designed for 830 high quality metagenome-assembled genomes representing bacteria present in mouse stool specimens. Comparison of the MA-GenTA data with mWGS data demonstrated excellent correlation down to 0.01% relative abundance and a similar number of organisms detected per sample. Despite the incompleteness of the reference database, NMDS clustering based on the Bray-Curtis dissimilarity metric of sample groups was consistent between MA-GenTA, mWGS and 16S rRNA datasets.  MA-GenTA represents a potentially useful new method for microbiome community profiling based on reference genomes.

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## Overview:

There are 4 components of the MA-GenTA assay presented here. 

1. Probe design pipeline - this pipeline starts with reference genomes for probe design, filtering, and ends  with probe selection.

2. Probes used in MA-GenTA - these are the probes used in the MA-GenTA assay.

3. Data processing - starting with raw sequencing reads ending with count tables of MAGs and probes per sample.

4. Downstream analysis - starting with count tables and ending with statistical analyses and figure generation.