Shotgun proteomic data are affected by a variety of known and unknown systematic biases
as well as high proportions of missing values. Typically, normalization is performed in an …

Mass spectrometry-based proteomics has become the tool of choice for identifying and
quantifying the proteome of an organism. Though recent years have seen a tremendous …

10.7554/eLife.20777.001 Variation in the presence or absence of transposable elements (TEs)
is a major source of genetic variation between individuals. Here, we identified 23,095 TE …

Motivation: Quantitative mass spectrometry-based proteomics requires protein-level estimates
and associated confidence measures. Challenges include the presence of low quality or …

Background Seed germination involves progression from complete metabolic dormancy to
a highly active, growing seedling. Many factors regulate germination and these interact …

Motivation: The size and complex nature of mass spectrometry-based proteomics datasets
motivate development of specialized software for statistical data analysis and exploration. We …

Quantitative proteomics analysis of cortical samples of 10 Alzheimer’s disease (AD) brains
versus 10 normally aged brains was performed by following the accurate mass and time tag (…

Liquid chromatography mass spectrometry has become one of the analytical platforms of
choice for metabolomics studies. However, LC-MS metabolomics data can suffer from the …

Motivation: LC-MS allows for the identification and quantification of proteins from biological
samples. As with any high-throughput technology, systematic biases are often observed in LC…

Many mass spectrometry-based studies, as well as other biological experiments produce
cluster-correlated data. Failure to account for correlation among observations may result in a …