Daniele Cagnazzi

dblp:231/1450 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2018
0000-0002-7901-4565ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › genomics
genotyping
0.312018
SONiCS: PCR stutter noise correction in genome-scale microsatellites · Bioinform. 2018
Bioinformatics and computational biology
microsatellite genotyping
0.312018
SONiCS: PCR stutter noise correction in genome-scale microsatellites · Bioinform. 2018
Bioinformatics and computational biology › sequence analysis
sequencing error correction
0.312018
SONiCS: PCR stutter noise correction in genome-scale microsatellites · Bioinform. 2018

Methods — techniques the papers use, named apart from their topics

monte carlo simulation · 0.3
YearPublicationVenuePosition
2018 SONiCS: PCR stutter noise correction in genome-scale microsatellites
abstract
Motivation: Massively parallel capture of short tandem repeats (STRs, or microsatellites) provides a strategy for population genomic and demographic analyses at high resolution with or without a reference genome. However, the high Polymerase Chain Reaction (PCR) cycle numbers needed for target capture experiments create genotyping noise through polymerase slippage known as PCR stutter. Results: We developed SONiCS-Stutter mONte Carlo Simulation-a solution for stutter correction based on dense forward simulations of PCR and capture experimental conditions. To test SONiCS, we genotyped a 2499-marker STR panel in 22 humpback dolphins (Sousa sahulensis) using target capture, and generated capillary-based genotypes to validate five of these markers. In these 110 comparisons, SONiCS showed a 99.1% accuracy rate and a 98.2% genotyping success rate, miscalling a single allele in a marker with low sequence coverage and rejecting another as un-callable. Availability and implementation: Source code and documentation for SONiCS is freely available at https://github.com/kzkedzierska/sonics. Raw read data used in experimental validation of SONiCS have been deposited in the Sequence Read Archive under accession number SRP135756. Supplementary information: Supplementary data are available at Bioinformatics online.
Katarzyna Z. Kedzierska, Livia Gerber, Daniele Cagnazzi, Michael Krützen, Aakrosh Ratan, Logan Kistler
Bioinform.3