Literature DB >> 32491285

Taxamat: Automated biodiversity data management tool - Implications for microbiome studies.

A Vida1,2, B L Bodrogi3, B Balogh1, P Bai1,2,4.   

Abstract

Working with biodiversity data is a computationally intensive process. Numerous applications and services provide options to deal with sequencing and taxonomy data. Professional statistics software are also available to analyze these type of data. However, in-between the two processes there is a huge need to curate biodiversity sample files. Curation involves creating summed abundance values for chosen taxonomy ranks, excluding certain taxa from analysis, and finally merging and downsampling data files. Very few tools, if any, offer a solution to this problem, thus we present Taxamat, a simple data management application that allows for curation of biodiversity data files before they can be imported to other statistics software. Taxamat is a downloadable application for automated curation of biodiversity data featuring taxonomic classification, taxon filtering, sample merging, and downsampling. Input and output files are compatible with most widely used programs. Taxamat is available on the web at http://www.taxamat.com either as a single executable or as an installable package for Microsoft Windows platforms.

Keywords:  biodiversity; data management; diversity indices; taxonomy

Mesh:

Year:  2020        PMID: 32491285     DOI: 10.1556/2060.2020.00004

Source DB:  PubMed          Journal:  Physiol Int        ISSN: 2498-602X            Impact factor:   2.090


  2 in total

Review 1.  Oncobiosis and Microbial Metabolite Signaling in Pancreatic Adenocarcinoma.

Authors:  Borbála Kiss; Edit Mikó; Éva Sebő; Judit Toth; Gyula Ujlaki; Judit Szabó; Karen Uray; Péter Bai; Péter Árkosy
Journal:  Cancers (Basel)       Date:  2020-04-25       Impact factor: 6.639

Review 2.  The role of the microbiome in ovarian cancer: mechanistic insights into oncobiosis and to bacterial metabolite signaling.

Authors:  Adrienn Sipos; Gyula Ujlaki; Edit Mikó; Eszter Maka; Judit Szabó; Karen Uray; Zoárd Krasznai; Péter Bai
Journal:  Mol Med       Date:  2021-04-01       Impact factor: 6.354

  2 in total

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