Literature DB >> 34245921

A Curriculum for Genomic Education of Molecular Genetic Pathology Fellows: A Report of the Association for Molecular Pathology Training and Education Committee.

Jason N Rosenbaum1, Anna B Berry2, Alanna J Church3, Kristy Crooks4, Jeffrey R Gagan5, Dolores López-Terrada6, John D Pfeifer7, Hanna Rennert8, Iris Schrijver9, Anthony N Snow10, David Wu11, Mark D Ewalt12.   

Abstract

Molecular genetic pathology (MGP) is a subspecialty of pathology and medical genetics and genomics. Genomic testing, which is defined as that which generates large data sets and interrogates large segments of the genome in a single assay, is increasingly recognized as essential for optimal patient care through precision medicine. The most common genomic testing technologies in clinical laboratories are next-generation sequencing and microarray. It is essential to train in these methods and to consider the data generated in the context of the diagnosis, medical history, and other clinical findings of individual patients. Accordingly, updating the MGP fellowship curriculum to include genomics is timely, important, and challenging. At the completion of training, an MGP fellow should be capable of independently interpreting and signing out results of a wide range of genomic assays and, given the appropriate context and institutional support, of developing and validating new assays in compliance with applicable regulations. The Genomics Task Force of the MGP Program Directors, a working group of the Association for Molecular Pathology Training and Education Committee, has developed a genomics curriculum framework and recommendations specific to the MGP fellowship. These recommendations are presented for consideration and implementation by MGP fellowship programs with the understanding that MGP programs exist in a diversity of clinical practice environments with a spectrum of available resources.
Copyright © 2021 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

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Year:  2021        PMID: 34245921     DOI: 10.1016/j.jmoldx.2021.07.001

Source DB:  PubMed          Journal:  J Mol Diagn        ISSN: 1525-1578            Impact factor:   5.568


  1 in total

1.  The Clinical Variant Analysis Tool: Analyzing the evidence supporting reported genomic variation in clinical practice.

Authors:  Hui-Lin Chin; Nour Gazzaz; Stephanie Huynh; Iulia Handra; Lynn Warnock; Ashley Moller-Hansen; Pierre Boerkoel; Julius O B Jacobsen; Christèle du Souich; Nan Zhang; Kent Shefchek; Leah M Prentice; Nicole Washington; Melissa Haendel; Linlea Armstrong; Lorne Clarke; Wenhui Laura Li; Damian Smedley; Peter N Robinson; Cornelius F Boerkoel
Journal:  Genet Med       Date:  2022-04-19       Impact factor: 8.864

  1 in total

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