Timing of Newborn Blood Collection Alters Metabolic Disease Screening Performance.

Blood collection for newborn genetic disease screening is preferably performed within 24-48 h after birth. We used population-level newborn screening (NBS) data to study early postnatal metabolic changes and whether timing of blood collection could impact screening performance. Newborns were grouped based on their reported age at blood collection (AaBC) into early (12-23 h), standard (24-48 h), and late (49-168 h) collection groups.

Validation of novel forensic DNA markers using multiplex microhaplotype sequencing.

Microhaplotypes (MH) are comprised of multiple single nucleotide polymorphisms (SNPs) that are located within 300 bases of genomic sequence. Improved tools are needed to facilitate broader application of microhaplotypes in a diverse range of populations and forensic settings. We designed an assay for multiplex sequencing of 90 microhaplotypes (mMHseq) that include 46 MH loci with high Effective Number of Alleles (A) from previous studies [1], and 44 high A MH loci containing between four to fourteen SNPs that were identified from the 1000 Genomes (1KG) Project.

Ethnic variability in newborn metabolic screening markers associated with false-positive outcomes.

Newborn screening (NBS) programmes utilise information on a variety of clinical variables such as gestational age, sex, and birth weight to reduce false-positive screens for inborn metabolic disorders. Here we study the influence of ethnicity on metabolic marker levels in a diverse newborn population. NBS data from screen-negative singleton babies (n = 100 000) were analysed, which included blood metabolic markers measured by tandem mass spectrometry and ethnicity status reported by the parents.

Reducing False-Positive Results in Newborn Screening Using Machine Learning.

Newborn screening (NBS) for inborn metabolic disorders is a highly successful public health program that by design is accompanied by false-positive results. Here we trained a Random Forest machine learning classifier on screening data to improve prediction of true and false positives. Data included 39 metabolic analytes detected by tandem mass spectrometry and clinical variables such as gestational age and birth weight.

ProteomicsBrowser: MS/proteomics data visualization and investigation.

Summary: Large-scale, quantitative proteomics data are being generated at ever increasing rates by high-throughput, mass spectrometry technologies. However, due to the complexity of these large datasets as well as the increasing numbers of post-translational modifications (PTMs) that are being identified, developing effective methods for proteomic visualization has been challenging. ProteomicsBrowser was designed to meet this need for comprehensive data visualization.