Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

A sensitivity analysis to determine the robustness of STRmix™ with respect to laboratory calibration.

Forensic science international. Genetics - 1 Jul 2018

Kelly Hannah, Bright Jo-Anne, Kruijver Maarten, Cooper Stuart, Taylor Duncan, Duke Kyle, Strong Melissa, Beamer Vickie, Buettner Christina, Buckleton John

Abstract excerpt

STRmix™ uses several laboratory specific parameters to calibrate the stochastic model for peak heights. These are modelled on empirical observations specific to the instruments and protocol used in the analysis. The extent to which these parameters can be borrowed from laboratories with similar technology and protocols without affecting the accuracy of the system is investigated using a sensitivity analysis....

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Alleles
Share to DNA Fingerprinting

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Share to Forensic Genetics

Share to Genotyping Techniques

Share to Microsatellite Repeats

Share to Models, Statistical

Share to Probability

Share to Software

Source

Identifiers

PMID: 29727813
DOI: 10.1016/j.fsigen.2018.04.009

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

A sensitivity analysis to determine the robustness of STRmix™ with respect to laboratory calibration.PMID 29727813Read ↗

PeakPerformance - a tool for Bayesian inference-based fitting of LC-MS/MS peaksSemantic proximity Read ↗

Standardization of milk infrared spectra for the retroactive application of calibration models.Semantic proximity Read ↗

A benchmarking workflow for assessing the reliability of batch correction methodsSemantic proximity Read ↗

A Method to adjust for measurement error in multiple exposure variables measured with correlated errors in the absence of an internal validation studySemantic proximity Read ↗

A Data Calibration Method of Micro Air Quality Detector Based on LASSO Regression and NARX Neural Network Combined ModelSemantic proximity Read ↗

Evaluation of Analysis by Cross-Validation. Part I: Using Verification MetricsSemantic proximity Read ↗

A comprehensive approach to soil‐atmosphere trace‐gas flux estimation with static chambersSemantic proximity Read ↗

Consensus design of a calibration experiment for human fear conditioningSemantic proximity Read ↗

Genetic algorithm with a Bayesian approach for the detection of multiple points of change of time series of counting exceedances of specific thresholds.Semantic proximity Read ↗

Evaluating HOMER Software's Decision-Making Capabilities in Terms of Ecological Impact and Financial BenefitsSemantic proximity Read ↗

Impact of small sample sizes on the internal quality control: statistical uncertainties in the determination of root mean square deviations with respect to the sample mean (RMSD) or to a target value (RMSTD)Semantic proximity Read ↗

Accuracy verification of low-cost CO<sub>2</sub> concentration measuring devices for general use as a countermeasure against COVID-19Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.