Great differences in performance and outcome of high-throughput sequencing data analysis platforms for fungal metabarcoding

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61388971%3A_____%2F18%3A00498742" target="_blank" >RIV/61388971:_____/18:00498742 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.3897/mycokeys.39.28109" target="_blank" >http://dx.doi.org/10.3897/mycokeys.39.28109</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3897/mycokeys.39.28109" target="_blank" >10.3897/mycokeys.39.28109</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Great differences in performance and outcome of high-throughput sequencing data analysis platforms for fungal metabarcoding

Popis výsledku v původním jazyce

Along with recent developments in high-throughput sequencing (HTS) technologies and thus fast accumulation of HTS data, there has been a growing need and interest for developing tools for HTS data processing and communication. In particular, a number of bioinformatics tools have been designed for analysing metabarcoding data, each with specific features, assumptions and outputs. To evaluate the potential effect of the application of different bioinformatics workflow on the results, we compared the performance of different analysis platforms on two contrasting high-throughput sequencing data sets. Our analysis revealed that the computation time, quality of error filtering and hence output of specific bioinformatics process largely depends on the platform used. Our results show that none of the bioinformatics workflows appears to perfectly filter out the accumulated errors and generate Operational Taxonomic Units, although PipeCraft, LotuS and PIPITS perform better than QIIME2 and Galaxy for the tested fungal amplicon dataset. We conclude that the output of each platform requires manual validation of the OTUs by examining the taxonomy assignment values.

Název v anglickém jazyce

Great differences in performance and outcome of high-throughput sequencing data analysis platforms for fungal metabarcoding

Popis výsledku anglicky

Along with recent developments in high-throughput sequencing (HTS) technologies and thus fast accumulation of HTS data, there has been a growing need and interest for developing tools for HTS data processing and communication. In particular, a number of bioinformatics tools have been designed for analysing metabarcoding data, each with specific features, assumptions and outputs. To evaluate the potential effect of the application of different bioinformatics workflow on the results, we compared the performance of different analysis platforms on two contrasting high-throughput sequencing data sets. Our analysis revealed that the computation time, quality of error filtering and hence output of specific bioinformatics process largely depends on the platform used. Our results show that none of the bioinformatics workflows appears to perfectly filter out the accumulated errors and generate Operational Taxonomic Units, although PipeCraft, LotuS and PIPITS perform better than QIIME2 and Galaxy for the tested fungal amplicon dataset. We conclude that the output of each platform requires manual validation of the OTUs by examining the taxonomy assignment values.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10606 - Microbiology

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

MycoKeys

ISSN

1314-4057

e-ISSN

—

Svazek periodika

39

Číslo periodika v rámci svazku

SEP 10

Stát vydavatele periodika

BG - Bulharská republika

Počet stran výsledku

12

Strana od-do

29-40

Kód UT WoS článku

000444106400001

EID výsledku v databázi Scopus

2-s2.0-85054060226