Comparison of Sequencing Utility Programs

By Erik Aronesty. 2013

1,094 citations recorded by the source corpus.

High throughput sequencing (HTS) has resulted in extreme growth rates of sequencing data. At our lab, we generate terabytes of data every day. It is usually seen as required for data output to be "cleaned" and processed in various ways prior to use for common tasks such as variant calling, expression quantification and assembly. Two common tasks associated with HTS are adapter trimming and paired-end joining. I have developed two tools at Expression Analysis, Inc. to address these common tasks. The names of these programs are fastq-mcf and fastq-join. I compared the performance of these tools to similar open-source utilities, both in terms of resource efficiency, and effectiveness.

Subfields: Artificial Intelligence, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/0f24db0e2d39aa5b8526960cec075ad899acb0fb

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Citations in the corpus

Dietary emulsifiers impact the mouse gut microbiota promoting colitis and metabolic syndrome (2015, neutral): “26, 1641–1650 (2009). 44.”
Age-related changes in gut microbiota composition from newborn to centenarian: a cross-sectional study (2016, neutral): “2–537) [50].”
Trimmomatic: a flexible trimmer for Illumina sequence data (2014, methodology): “com/najoshi/), which fully support paired-end data and EA-Utils (Aronesty, 2013), which maintains read pairing but loses singletons (reads whose mate has been filtered).”
Fungal community homogenization, shift in dominant trophic guild, and appearance of novel taxa with biotic invasion (2017, methodology): “The remaining forward and reverse reads were then merged using fastq-join (Aronesty 2013) with a 50-bp overlap and allowing 5% mismatch.”