Guidelines for releasing a variant effect predictor.

Computational methods for assessing the likely impacts of mutations, known as variant effect predictors (VEPs), are widely used in the assessment and interpretation of human genetic variation, as well as in other applications like protein engineering. Many different VEPs have been released to date, and there is tremendous variability in their underlying algorithms and outputs, and in the ways in which the methodologies and predictions are shared. This leads to considerable challenges for end users in knowing which VEPs to use and how to use them.

Comprehensive assessment of anaplastic lymphoma kinase in localized and metastatic prostate cancer reveals targetable alterations.

Anaplastic lymphoma kinase (ALK) is a tyrosine kinase with genomic and expression changes in many solid tumors. ALK inhibition is first line therapy for lung cancers with alterations, and an effective therapy in other tumor types, but has not been well-studied in prostate cancer. Here, we aim to delineate the role of ALK genomic and expression changes in primary and metastatic prostate cancer.

The utility of cerebrospinal fluid-derived cell-free DNA in molecular diagnostics for the -related megalencephaly-capillary malformation (MCAP) syndrome: a case report.

The megalencephaly-capillary malformation (MCAP) syndrome is an overgrowth disorder caused by mosaic gain-of-function variants in It is characterized by megalencephaly or hemimegalencephaly, vascular malformations, somatic overgrowth, among other features. Epilepsy is commonly associated with MCAP, and a subset of individuals have cortical malformations requiring resective epilepsy surgery. Like other mosaic disorders, establishing a molecular diagnosis is largely achieved by screening lesional tissues (such as brain or skin), with a low diagnostic yield from peripheral tissues (such as blood).

Connect-seq to superimpose molecular on anatomical neural circuit maps.

The mouse brain contains about 75 million neurons interconnected in a vast array of neural circuits. The identities and functions of individual neuronal components of most circuits are undefined. Here we describe a method, termed "Connect-seq," which combines retrograde viral tracing and single-cell transcriptomics to uncover the molecular identities of upstream neurons in a specific circuit and the signaling molecules they use to communicate.