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

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, nonspecialists are faced with the double challenge of choosing among an everincreasing 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 welldocumented commands.

Lake microbiome and trophy fluctuations of the ancient hemp rettery

“…Prediction of ORF resulted in 3.24–6.04 million of CDS per sample and between 29.73% and 37.85% of CDS per sample were assigned to KEGG Orthology (KO) (Supp Data 2 b,c). The data obtained in this way was then loaded into R v. 4.0.4 85 and, using the SQMtools 86 library (function loadSQM), only data taxonomically assigned to the bacterial group was selected for further analysis (function subsetTax). Tables containing the abundance and TPM (transcript per million) of each KEGG Orthologs (KOs) for each sample were exported.…”

Longitudinal and Comparative Analysis of Gut Microbiota of Tunisian Newborns According to Delivery Mode

“…Coverage and abundance estimation for genes and contigs were performed using Bedtools and normalized using the reads per kilobase per million mapped reads (RPKM) method (Quinlan and Hall, 2010 ). The statistical downstream analyses were performed using the SQMtools and phyloseq R packages (McMurdie and Holmes, 2013 ; Puente-Sánchez et al, 2020 ).…”

Stabilization of swine faecal samples influences taxonomic and functional results in microbiome analyses

“…Finally, the cleaned reads were analysed using the SqueezeMeta pipeline version 1.4.0 with the default parameters and the coassembly option [24] . The package SQMtools [25] was used to integrate SqueezeMeta data in R and for the functional analysis. Taxonomic and functional values were converted to relative abundances to compare results between samples.…”