Error filtering, pair assembly and error correction for next-generation sequencing reads

By Robert C. Edgar, Henrik Flyvbjerg. Bioinform., 2015

1,157 citations recorded by the source corpus.

Subfields: Cancer Research, Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/c84a4abc96f5ecf2783cba9aeef579510b78af3f

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Citations in the corpus

Assessing strengths and weaknesses of DNA metabarcoding‐based macroinvertebrate identification for routine stream monitoring (2017, positive): “1.1861 with the following settings: -fastq_mergepairs with - fastq_maxdiffs 99, -fastq_maxdiffpct 99 and -fastq_trunctail 0 (Edgar & Flyvbjerg 2015).”
Validation and Development of COI Metabarcoding Primers for Freshwater Macroinvertebrate Bioassessment (2017, positive): “1.1831 -fastq_mergepairs with -fastq_merge_maxee 1.0 (Edgar and Flyvbjerg, 2015).”
Temperatures beyond the community optimum promote the dominance of heat-adapted, fast growing and stress resistant bacteria in alpine soils (2020, background): “…(Sphingomonas and J. Donhauser et al. Soil Biology and Biochemistry 148 (2020) 107873 Phenylobacterium (�Santl-Temkiv et al., 2013; Krumins et al., 2014)) and were able to thrive on rock surfaces (Edaphobacter (Esposito et al., 2015)) and to resist UV-radiation (Sphingomonas (Joux et al., 1999)).”
The ecology of environmental DNA and implications for conservation genetics (2016, background): “Bioinformatic analysis of HTS data from eDNA samples represents a complex and rapidly changing landscape (Edgar and Flyvbjerg 2015).”
Sedimentary eDNA provides different information on timescale and fish species composition compared with aqueous eDNA (2020, methodology): “Quality filtering using the “fastq_filter” command was performed to remove low-quality reads with an expected error rate (Edgar & Flyvbjerg, 2015) of >1% and too short reads of <100 bp; (d) The preprocessed reads were dereplicated using the “fastx_uniques” command, and all singletons, doubletons,…”
A practical guide to amplicon and metagenomic analysis of microbiome data (2020, methodology): “All of these steps can be completed using USEARCH (Edgar, A practical guide to amplicon and metagenomic analysis of microbiome data REVIEW 2010) or QIIME (Caporaso et al., 2010).”
UNOISE2: improved error-correction for Illumina 16S and ITS amplicon sequencing (2016, methodology): “More recently, Illumina denoisers have been described including UNOISE(Edgar and Flyvbjerg, 2014), MED(Eren et al. , 2015) and DADA2(Callahan et al. , 2016).”
Updating the 97% identity threshold for 16S ribosomal RNA OTUs (2017, background): “These reads have errors due to PCR and sequencing which can cause large numbers of spurious OTUs (e.g., (Huse et al., 2010; Edgar and Flyvbjerg, 2014)).”