13 papers · ranked by Valyu relevance
Joan Saurina-i-Ricos, Daniel Mas Montserrat, Alexander G. Ioannidis
Estimating genetic clusters from sequencing data is a fundamental task in population and medical genetics, enabling demographic inference and adjustment for population structure in association studies. ADMIXTURE, a widely used model-based clustering method, employs an accelerated Expectation–Maximization (EM) algorithm…
Zihao Chen, Changhu Wang, Siyuan Huang, Yang Shi + 1 more
In single-cell RNA sequencing (scRNA-seq) studies, cell-types and their associated marker genes are often identified by clustering and differential expression gene (DEG) analysis. scRNA-seq data contain many genes not relevant to cell-types and gene selection procedures are needed for more accurate clustering. An ideal…
Chin-Sheng Teng, Xuesong Wang, Cheng Liu, Qishan Wang + 2 more
Genome-wide association studies (GWAS) often analyze one trait at a time, but multivariate GWAS can increase the power by leveraging trait correlations. However, existing methods struggle with high computational demands, especially when analyzing over five traits. We present EMmvGWAS, an efficient multivariate GWAS…
Tien-Wen Lee
The General Linear Model (GLM) has been widely used in research, where error term has been treated as noise. However, compelling evidence suggests that in biological systems, the target variables may possess their innate variances. A modified GLM was proposed to explicitly model biological variance and non-biological…
Amnon Balanov, Wasim Huleihel, Tamir Bendory
“Einstein from noise” (EfN) is a prominent example of the model bias phenomenon, where systematic errors in the statistical model lead to spurious but consistent estimates. In the EfN experiment, one falsely believes that a set of observations contains noisy, shifted copies of a template signal (e.g., an Einstein…
Amnon Balanov, Wasim Huleihel, Tamir Bendory
“Einstein from noise” (EfN) is a prominent example of the model bias phenomenon: systematic errors in the statistical model that lead to spurious but consistent estimates. In the EfN experiment, one falsely believes that a set of observations contains noisy, shifted copies of a template signal (e.g., an Einstein…
Joshua P. Kulasingham, Jonathan Z. Simon
The Temporal Response Function (TRF) is a linear model of neural activity time-locked to continuous stimuli, including continuous speech. TRFs based on speech envelopes typically have distinct components that have provided remarkable insights into the cortical processing of speech. However, current methods may lead to…
Anthony Santella, Irina Kolotuev, Caroline Kizilyaprak, Zhirong Bao
Analyses across imaging modalities allow the integration of complementary spatiotemporal information about brain development, structure and function. However, systematic atlasing across modalities is limited by challenges to effective image alignment. We combine highly spatially resolved electron microscopy (EM) and…
James C.R. Whittington, William Dorrell, Timothy E.J. Behrens, Surya Ganguli + 1 more
Remembering events in the past is crucial to intelligent behaviour. Flexible memory retrieval, beyond simple recall, requires a cognitive map, or model of how sensations, actions, and latent environmental or task states are all related to one another. Two key brain systems are implicated in this process: the…
Jonathan Nir, Leon Y. Deouell
Eye movement (EM) detection is a critical step in most eye-tracking (ET) research, typically relying on detectors – specialized algorithms designed to segment raw ET data into discrete oculomotor events. However, variability in detection algorithms and the lack of standardized evaluation frameworks hinder transparency…
Wai Shing Tang, Jeff Soules, Aaditya Rangan, Pilar Cossio
Extracting conformational heterogeneity from cryo-electron microscopy (cryo-EM) images is particularly challenging for flexible biomolecules, where traditional 3D classification approaches often fail. Over the past few decades, advancements in experimental and computational techniques have been made to tackle this…
Yilai Li, Quanfu Fan, Ziping Xu, Emma Rose Lee + 6 more
Cryo-electron microscopy (cryo-EM) represents a powerful technology for determining atomic models of biological macromolecules(15). Despite this promise, human-guided cryo-EM data collection practices limit the impact of cryo-EM because of a path planning problem: cryo-EM datasets typically represent 2-5% of the total…
CS Parker, NP Oxtoby, DC Alexander, H Zhang
Estimating the temporal evolution of biomarker abnormalities in disease informs understanding of early disease processes and facilitates subject staging, which may augment the development of early therapeutic interventions and provide personalised treatment tools. Event-based modelling of disease progression (EBM) is a…