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SQMtools: automated processing and visual analysis of ’omics data with R and anvi’o

Authors: Puente-Sánchez, Fernando; García-García, Natalia; Tamames, Javier;
APC: 1,790 EUR

SQMtools: automated processing and visual analysis of ’omics data with R and anvi’o

Abstract

Abstract Background The dramatic decrease in sequencing costs over the last decade has boosted the adoption of high-throughput sequencing applications as a standard tool for the analysis of environmental microbial communities. Nowadays even small research groups can easily obtain raw sequencing data. After that, however, non-specialists are faced with the double challenge of choosing among an ever-increasing array of analysis methodologies, and navigating the vast amounts of results returned by these approaches. Results Here we present a workflow that relies on the SqueezeMeta software for the automated processing of raw reads into annotated contigs and reconstructed genomes (bins). A set of custom scripts seamlessly integrates the output into the anvi’o analysis platform, allowing filtering and visual exploration of the results. Furthermore, we provide a software package with utility functions to expose the SqueezeMeta results to the R analysis environment. Conclusions Altogether, our workflow allows non-expert users to go from raw sequencing reads to custom plots with only a few powerful, flexible and well-documented commands.

Country
Spain
Keywords

Databases, Factual, QH301-705.5, Automatic, Methodology Article, Computer applications to medicine. Medical informatics, R858-859.7, Computational Biology, High-Throughput Nucleotide Sequencing, Microbial ecology, Contig Mapping, Pipeline, Metagenomics, Biology (General), Software, Metatranscriptomics, Visualization

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
80
Top 1%
Top 10%
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57
183
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gold