Dataset Information

ToRQuEMaDA: tool for retrieving queried Eubacteria, metadata and dereplicating assemblies.

ABSTRACT: TQMD is a tool for high-performance computing clusters which downloads, stores and produces lists of dereplicated prokaryotic genomes. It has been developed to counter the ever-growing number of prokaryotic genomes and their uneven taxonomic distribution. It is based on word-based alignment-free methods (k-mers), an iterative single-linkage approach and a divide-and-conquer strategy to remain both efficient and scalable. We studied the performance of TQMD by verifying the influence of its parameters and heuristics on the clustering outcome. We further compared TQMD to two other dereplication tools (dRep and Assembly-Dereplicator). Our results showed that TQMD is primarily optimized to dereplicate at higher taxonomic levels (phylum/class), as opposed to the other dereplication tools, but also works at lower taxonomic levels (species/strain) like the other dereplication tools. TQMD is available from source and as a Singularity container at [https://bitbucket.org/phylogeno/tqmd ].

SUBMITTER: Leonard RR

PROVIDER: S-EPMC8106394 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

ToRQuEMaDA: tool for retrieving queried Eubacteria, metadata and dereplicating assemblies.

Léonard Raphaël R RR Leleu Marie M Van Vlierberghe Mick M Cornet Luc L Kerff Frédéric F Baurain Denis D

PeerJ 20210505

TQMD is a tool for high-performance computing clusters which downloads, stores and produces lists of dereplicated prokaryotic genomes. It has been developed to counter the ever-growing number of prokaryotic genomes and their uneven taxonomic distribution. It is based on word-based alignment-free methods (<i>k</i>-mers), an iterative single-linkage approach and a divide-and-conquer strategy to remain both efficient and scalable. We studied the performance of TQMD by verifying the influence of its ...[more]

PMID: 33996287

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Project description:BackgroundAn individual's genetics play a role in how RNA transcripts are generated from DNA and consequently in their translation into protein. Transcriptional and translational profiling of patients furnishes the information that a specific marker is present; however, it fails to provide evidence whether the marker correlates with response to a therapeutic agent. A comparative analysis of the frequency of genetic variants, such as single nucleotide polymorphisms (SNPs), in diseased and general populations can identify pathogenic variants in individual patients. This is in part because SNPs have considerable effects on protein function and gene expression when they occur in coding regions and regulatory sequences, respectively. Therefore, a tool that can help users to obtain the allele frequency for a corresponding transcript is the need of the day. Several annotation tools such as SNPnexus and VariED are publicly available; however, none of them can use transcript IDs as input and provide the corresponding genomic positions of variants.ResultsIn this study, we developed an R package, called transcript annotation tool (TransAT), that provides (i) SNP ID and genomic position for a user-provided transcript ID from patients, and (ii) allele frequencies for the SNPs from publicly available global populations. All data elements are extracted, collected, and displayed in an easily downloadable format in two simple command lines. TransAT is available on Windows/Linux/MacOS and is operative for R version 4.0.4 or later. It is available at https://github.com/ShihChingYu/TransAT and can be downloaded and installed using devtools::install_github("ShihChingYu/TransAT", force=T) on the R execution page. Thereafter, all functions can be executed by loading the package into R with library(TransAT).ConclusionsTransAT is a novel tool that seamlessly provides genetic annotations for queried transcripts. Such easily obtainable information would be greatly advantageous for physicians, assisting them to make individualized decisions about specific drug treatments. Moreover, allele frequencies from user-chosen global ethnic populations will highlight the importance of ethnicity and its effect on patient pathogenicity.

Dataset Information

ToRQuEMaDA: tool for retrieving queried Eubacteria, metadata and dereplicating assemblies.

Publications

ToRQuEMaDA: tool for retrieving queried Eubacteria, metadata and dereplicating assemblies.

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