bioRxiv ScienceSearch

Biology subjects

Matlock, M.

Publications and source records attributed to Matlock, M..

3 recordsLinked to original sources

Standard operating procedure for somatic variant refinement of tumor sequencing data

PurposeManual review of aligned sequencing reads is required to develop a high-quality list of somatic variants from massively parallel sequencing data (MPS). Despite widespread use in analyzing MPS data, there has been little attempt to describe methods for manual review, resulting in high inter- and intra-lab variability in somatic variant detection and characterization of tumors.\n\nMethodsOpen source software was used to develop an optimal method for manual review setup. We also developed a systemic approach to visually inspect each variant during manual review.\n\nResultsWe present a standard operating procedures for somatic variant refinement for use by manual reviewers. The approach is enhanced through representative examples of 4 different manual review categories that indicate a reviewers confidence in the somatic variant call and 19 annotation tags that contextualize commonly observed sequencing patterns during manual review. Representative examples provide detailed instructions on how to classify variants during manual review to rectify lack of confidence in automated somatic variant detection.\n\nConclusionStandardization of somatic variant refinement through systematization of manual review will improve the consistency and reproducibility of identifying true somatic variants after automated variant calling.

genetics

Evolution and Functional Information

\"Functional Information\"--estimated from the mutual information of protein sequence alignments--has been proposed as a reliable way of estimating the number of proteins with a specified function and the consequent difficulty of evolving a new function. The fantastic rarity of functional proteins computed by this approach emboldens some to argue that evolution is impossible. Random searches, it seems, would have no hope of finding new functions. Here, we use simulations to demonstrate that sequence alignments are a poor estimate functional information. The mutual information of sequence alignments fantastically underestimates of the true number of functional proteins, because it also is strongly influenced by a familys history, mutational bias, and selection. Regardless, even if functional information could be reliably calculated, it tells us nothing about the difficulty of evolving new functions, because it does not estimate the distance between a new function and existing functions. The pervasive observation of multifunctional proteins suggests that functions are actually ver close to one another and abundant. Multifunctional proteins would be impossible if the FI argument against evolution were true.

evolutionary biology

A Sign of Disparity: Racial/Ethnic Composition of Treatment Centers is an Independent Risk Factor in SPRINT Trial

The racial composition of treatment centers in the SPRINT trial is an independent risk factor for myocardial infarction (MI) and stroke. Independent of individual race or ethnicity, patients face a 39% increase in relative risk of MI or stroke when associated to treatment centers with a high proportion of African Americans. The magnitude of this effect is comparable to smoking. This suggests the strong influence of social determinants on health outcomes among hypertensive patients.

clinical trials