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FIGARO: An efficient and objective tool for optimizing microbiome rRNA gene trimming parameters

Michael M. Weinstein, Aishani Prem, Mingda Jin, Shuiquan Tang, Jeffrey M. Bhasin
doi: https://doi.org/10.1101/610394
Michael M. Weinstein
1Department of Bioinformatics, Zymo Research Corp., Irvine, CA, USA
2Molecular, Cell, and Developmental Biology/Quantitative and Computational Biosciences Institute, University of California, Los Angeles, CA, USA
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Aishani Prem
1Department of Bioinformatics, Zymo Research Corp., Irvine, CA, USA
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Mingda Jin
1Department of Bioinformatics, Zymo Research Corp., Irvine, CA, USA
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Shuiquan Tang
1Department of Bioinformatics, Zymo Research Corp., Irvine, CA, USA
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Jeffrey M. Bhasin
1Department of Bioinformatics, Zymo Research Corp., Irvine, CA, USA
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ABSTRACT

Summary Microbiome studies continue to provide tremendous insight into the importance of microorganism populations to the macroscopic world. High-throughput DNA sequencing technology (i.e., Next-generation Sequencing) has enabled the cost-effective, rapid assessment of microbial populations when combined with bioinformatic tools capable of identifying microbial taxa and calculating the diversity and composition of biological and environmental samples. Ribosomal RNA gene sequencing, where 16S and 18S rRNA gene sequences are used to identify prokaryotic and eukaryotic species, respectively, is one of the most widely-used techniques currently employed in microbiome analysis. Prior to bioinformatic analysis of these sequences, trimming parameters must be set so that post-trimming sequence information is maximized while expected errors in the sequences themselves are minimized. In this application note, we present FIGARO: a Python–based application designed to maximize read retention after trimming and filtering for quality. FIGARO was designed specifically to increase reproducibility and minimize trial-and-error in trimming parameter selection for a DADA2–based pipeline and will likely be useful for optimizing trimming parameters and minimizing sequence errors in other pipelines as well where paired-end overlap is required.

Availability and implementation The FIGARO application is freely available as source code at https://github.com/Zymo-Research/figaro.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted April 16, 2019.
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FIGARO: An efficient and objective tool for optimizing microbiome rRNA gene trimming parameters
Michael M. Weinstein, Aishani Prem, Mingda Jin, Shuiquan Tang, Jeffrey M. Bhasin
bioRxiv 610394; doi: https://doi.org/10.1101/610394
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FIGARO: An efficient and objective tool for optimizing microbiome rRNA gene trimming parameters
Michael M. Weinstein, Aishani Prem, Mingda Jin, Shuiquan Tang, Jeffrey M. Bhasin
bioRxiv 610394; doi: https://doi.org/10.1101/610394

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