Litcius/Paper detail

HashSeq: a Simple, Scalable, and Conservative <i>De Novo</i> Variant Caller for 16S rRNA Gene Data Sets

Farnaz Fouladi, Jacqueline B. Young, Anthony A. Fodor

2021mSystems15 citationsDOIOpen Access PDF

Abstract

Recent bioinformatics development has enabled the detection of sequence variants with a high resolution of only one single-nucleotide difference in 16S rRNA gene sequence data. Despite this progress, there are several limitations that can be associated with variant calling pipelines, such as producing a large number of low-abundance sequence variants which need to be filtered out with arbitrary thresholds in downstream analyses or having a slow runtime.

Topics & Concepts

Sequence (biology)Computational biologyInferenceSmoothingBiologyScalabilityAlignment-free sequence analysisGeneticsComputer scienceSet (abstract data type)DNA sequencingGeneData miningFunction (biology)Sequence analysisRibosomal RNAGene predictionPipeline (software)Data set16S ribosomal RNASequence alignmentAlgorithmDeep sequencingGenomics and Phylogenetic StudiesGenomics and Rare DiseasesGenomic variations and chromosomal abnormalities