The Bioinformatic Applications of Hi-C and Linked Reads.

Long-range sequencing grants insight into additional genetic information beyond what can be accessed by both short reads and modern long-read technology. Several new sequencing technologies, such as "Hi-C" and "Linked Reads", produce long-range datasets for high-throughput and high-resolution genome analyses, which are rapidly advancing the field of genome assembly, genome scaffolding, and more comprehensive variant identification. In this review, we focused on five major long-range sequencing technologies: high-throughput chromosome conformation capture (Hi-C), 10X Genomics Linked Reads, haplotagging, transposase enzyme linked long-read sequencing (TELL-seq), and single- tube long fragment read (stLFR).

Image2Flow: A proof-of-concept hybrid image and graph convolutional neural network for rapid patient-specific pulmonary artery segmentation and CFD flow field calculation from 3D cardiac MRI data.

Computational fluid dynamics (CFD) can be used for non-invasive evaluation of hemodynamics. However, its routine use is limited by labor-intensive manual segmentation, CFD mesh creation, and time-consuming simulation. This study aims to train a deep learning model to both generate patient-specific volume-meshes of the pulmonary artery from 3D cardiac MRI data and directly estimate CFD flow fields.

Identifying the best PCR enzyme for library amplification in NGS.

PCR amplification is a necessary step in many next-generation sequencing (NGS) library preparation methods [1, 2]. Whilst many PCR enzymes are developed to amplify single targets efficiently, accurately and with specificity, few are developed to meet the challenges imposed by NGS PCR, namely unbiased amplification of a wide range of different sizes and GC content. As a result PCR amplification during NGS library prep often results in bias toward GC neutral and smaller fragments.

Haplotype-specific assembly of shattered chromosomes in esophageal adenocarcinomas.

The epigenetic landscape of cancer is regulated by many factors, but primarily it derives from the underlying genome sequence. Chromothripsis is a catastrophic localized genome shattering event that drives, and often initiates, cancer evolution. We characterized five esophageal adenocarcinoma organoids with chromothripsis using long-read sequencing and transcriptome and epigenome profiling.

A Deep Learning Pipeline for Assessing Ventricular Volumes from a Cardiac MRI Registry of Patients with Single Ventricle Physiology.

Purpose To develop an end-to-end deep learning (DL) pipeline for automated ventricular segmentation of cardiac MRI data from a multicenter registry of patients with Fontan circulation (Fontan Outcomes Registry Using CMR Examinations [FORCE]). Materials and Methods This retrospective study used 250 cardiac MRI examinations (November 2007-December 2022) from 13 institutions for training, validation, and testing. The pipeline contained three DL models: a classifier to identify short-axis cine stacks and two U-Net 3+ models for image cropping and segmentation.