scholarly journals Addressing Unusual Assay Variability with Robust Statistics

2021 ◽  
pp. 247255522110383
Author(s):  
Jason Haelewyn ◽  
Philip W. Iversen ◽  
Jeffrey R. Weidner
Keyword(s):  
Best Practices ◽  
Statistical Methods ◽  
Robust Statistics ◽  
Biological Process ◽  
Primary Efficacy ◽  
Efficacy Data ◽  
Assay Optimization ◽  
Bioassay Data ◽  
Robust Statistical Methods

Well-behaved, in vitro bioassays generally produce normally distributed values in their primary (efficacy) data. Accordingly, the best practices for statistical analysis are well documented and understood. However, assays may occasionally display unusually high variability and fall outside the assumptions inherent in these standard analyses. These assays may still be in the optimization phase, in which the source of variation could be identified and addressed. They might also represent the best available option to address the biological process being examined. In these cases, the use of robust statistical methods may provide a more appropriate set of tools for both data analysis and assay optimization. This article provides guidance on best practices for the use of robust statistical methods for the analysis of bioassay data as an alternative to standard methods. Impacts on experimental design and interpretation will be discussed.

scholarly journals Editorial, special issue on “Advances in Robust Statistics”

METRON ◽  
2021 ◽  
Author(s):  
Marco Riani ◽  
Mia Hubert
Keyword(s):  
Statistical Methods ◽  
Robust Statistics ◽  
Statistical Analyses ◽  
Striking Feature ◽  
Special Issue ◽  
Current State ◽  
Editorial Special Issue ◽  
Data Points ◽  
Robust Statistical Methods

AbstractStarting with 2020 volume, the journal Metron has decided to celebrate the centenary since its foundation with three special issues. This volume is dedicated to robust statistics. A striking feature of most applied statistical analyses is the use of methods that are well known to be sensitive to outliers or to other departures from the postulated model. Robust statistical methods provide useful tools for reducing this sensitivity, through the detection of the outliers by first fitting the majority of the data and then by flagging deviant data points. The six papers in this issue cover a wide orientation in all fields of robustness. This editorial first provides some facts about the history and current state of robust statistics and then summarizes the contents of each paper.

scholarly journals PGC7 suppresses TET3 for protecting DNA methylation

2013 ◽  
Vol 42 (5) ◽  
pp. 2893-2905 ◽  
Author(s):  
Chunjing Bian ◽  
Xiaochun Yu
Keyword(s):  
Dna Methylation ◽  
Molecular Mechanism ◽  
Biological Process ◽  
Cpg Islands ◽  
Binding Motifs ◽  
Genome Wide Analysis ◽  
Dna Motif ◽  
Genome Wide

Abstract Ten-eleven translocation (TET) family enzymes convert 5-methylcytosine to 5-hydroxylmethylcytosine. However, the molecular mechanism that regulates this biological process is not clear. Here, we show the evidence that PGC7 (also known as Dppa3 or Stella) interacts with TET2 and TET3 both in vitro and in vivo to suppress the enzymatic activity of TET2 and TET3. Moreover, lacking PGC7 induces the loss of DNA methylation at imprinting loci. Genome-wide analysis of PGC7 reveals a consensus DNA motif that is recognized by PGC7. The CpG islands surrounding the PGC7-binding motifs are hypermethylated. Taken together, our study demonstrates a molecular mechanism by which PGC7 protects DNA methylation from TET family enzyme-dependent oxidation.

Abstract 211: Myocardial Hypertrophy and Circulating RNAs

2017 ◽  
Vol 121 (suppl_1) ◽  
Author(s):  
Ravi V Shah ◽  
Olivia Ziegler ◽  
Kahraman Tanriverdi ◽  
Jian Rong ◽  
Martin Larson ◽  
...  
Keyword(s):  
Biological Process ◽  
Molecular Level ◽  
Myocardial Hypertrophy ◽  
Clinical Phenotype ◽  
Left Ventricular ◽  
Loss Of Function ◽  
Heart Study ◽  
Non Coding Rnas

While increased left ventricular mass (LVM) is strongly associated with incident heart failure (HF), events during transition from increased LVM to HF remain unclear. Extracellular non-coding RNAs (ex-RNAs) have been implicated in cardiac hypertrophy, though whether these ex-RNAs reflect important pathways in HF in humans is underexplored. In >2,000 individuals with concomitant M-mode echocardiography and ex-RNA measurements in the Framingham Heart Study, we found that lower circulating concentrations of three ex-RNAs—miR-20a-5p, miR-106b-5p, miR-17-5p—were associated with (1) greater LVM (+ one other pre-clinical phenotype, e.g., left atrial dimension or LVEDV) and (2) greater incident HF risk over a median follow-up 7.7 years ( Fig. A ). These 3 miRNAs were members of a tight cluster, regulating 883 mRNAs in common, associated with “hypertension” (OMIM) and biological process relevant to HF, including TGF-β signaling. We observed an increase in myocardial expression of these miRNAs during different phases of hypertrophy/HF development ( Fig. C, D ). Using gain and loss of function in vitro , our preliminary results suggest up-regulation of cardiomyocyte miR-106b expression abrogates expression of pathologic hypertrophy markers (ANP and BNP) during phenylephrine treatment, consistent with in silico results suggesting broad connections between miR-106b targets and natriuretic peptide signaling ( Fig. B, E-F ). These results provide translational evidence that circulating miRNAs associated with hypertrophy in patients may be protective in the transition from hypertrophy to HF at the molecular level.

Preparation of fibrils for intracerebral injection v1

2021 ◽  
Author(s):  
The Michael J Fox Foundation Pff Standardization Consortium
Keyword(s):  
Quality Control ◽  
Best Practices ◽  
External Validation ◽  
Alpha Synuclein ◽  
Intracerebral Injection ◽  
Primary Neuron ◽  
Consensus Protocol ◽  
Reference Section

This is a consensus protocol developed through discussions with Laura Volpicelli-Daley, Caryl Sortwell, Kelvin Luk, Lindsey Gottler, and Virginia Lee. This protocol is intended for research purposes only, using specially-formulated monomeric alpha-synuclein protein available for purchase at Proteos, Inc as the result of efforts by The Michael J. Fox Foundation (MJFF). Each batch of the “Alpha-Synuclein Monomer Protein for Making Pre- Formed Fibrils” has undergone internal purification and quality control at Proteos in addition to external validation to confirm successful generation of pathogenic aSyn PFFs. See Reference section for methods and results from application of alpha-synuclein pre-formed fibrils (aSyn PFFs) in primary neuron cultures in vitro or in mice in vivo. This protocol is referenced in the Polinski et al 2018 paper entitled "Best Practices for Generating and Using Alpha-Synuclein Pre-Formed Fibrils to Model Parkinson's Disease in Rodents" (doi: 10.3233/JPD-171248).

Protocol for Generation of Pre-Formed Fibrils from Alpha-Synuclein Monomer v1

2021 ◽  
Author(s):  
The Michael J Fox Foundation Pff Standardization Consortium
Keyword(s):  
Parkinson’S Disease ◽  
Quality Control ◽  
Best Practices ◽  
External Validation ◽  
Alpha Synuclein ◽  
Primary Neuron ◽  
Consensus Protocol ◽  
Reference Section

This is a consensus protocol developed through discussions with Laura Volpicelli-Daley, Caryl Sortwell, Kelvin Luk, Lindsey Gottler, and Virginia Lee. This protocol is intended for research purposes only, using specially-formulated monomeric alpha-synuclein protein available for purchase at Proteos, Inc as the result of efforts by The Michael J. Fox Foundation (MJFF). Each batch of the “Alpha-Synuclein Monomer Protein for Making Pre- Formed Fibrils” has undergone internal purification and quality control at Proteos in addition to external validation to confirm successful generation of pathogenic aSyn PFFs. See Reference section for methods and results from application of alpha-synuclein pre-formed fibrils (aSyn PFFs) in primary neuron cultures in vitro or in mice in vivo. This protocol is referenced in the Polinski et al 2018 paper entitled "Best Practices for Generating and Using Alpha-Synuclein Pre-Formed Fibrils to Model Parkinson's Disease in Rodents" (doi: 10.3233/JPD-171248).

scholarly journals Methods for Assessment of Memory Reactivation

2018 ◽  
Vol 30 (8) ◽  
pp. 2175-2209 ◽  
Author(s):  
Shizhao Liu ◽  
Andres D. Grosmark ◽  
Zhe Chen
Keyword(s):  
Statistical Methods ◽  
Memory Consolidation ◽  
Slow Wave Sleep ◽  
Brain Regions ◽  
Weighted Distance ◽  
Memory Reactivation ◽  
Statistical Dependency ◽  
Stored Information ◽  
Robust Statistical Methods ◽  
Population Decoding

It has been suggested that reactivation of previously acquired experiences or stored information in declarative memories in the hippocampus and neocortex contributes to memory consolidation and learning. Understanding memory consolidation depends crucially on the development of robust statistical methods for assessing memory reactivation. To date, several statistical methods have seen established for assessing memory reactivation based on bursts of ensemble neural spike activity during offline states. Using population-decoding methods, we propose a new statistical metric, the weighted distance correlation, to assess hippocampal memory reactivation (i.e., spatial memory replay) during quiet wakefulness and slow-wave sleep. The new metric can be combined with an unsupervised population decoding analysis, which is invariant to latent state labeling and allows us to detect statistical dependency beyond linearity in memory traces. We validate the new metric using two rat hippocampal recordings in spatial navigation tasks. Our proposed analysis framework may have a broader impact on assessing memory reactivations in other brain regions under different behavioral tasks.

scholarly journals Guidelines for performing Mendelian randomization investigations

2020 ◽  
Vol 4 ◽  
pp. 186 ◽  
Author(s):  
Stephen Burgess ◽  
George Davey Smith ◽  
Neil M. Davies ◽  
Frank Dudbridge ◽  
Dipender Gill ◽  
...  
Keyword(s):  
Statistical Methods ◽  
Genetic Variants ◽  
Mendelian Randomization ◽  
Data Sources ◽  
Sensitivity Analyses ◽  
Primary Analysis ◽  
Data Presentation ◽  
Journal Editors ◽  
Robust Statistical Methods

This paper provides guidelines for performing Mendelian randomization investigations. It is aimed at practitioners seeking to undertake analyses and write up their findings, and at journal editors and reviewers seeking to assess Mendelian randomization manuscripts. The guidelines are divided into nine sections: motivation and scope, data sources, choice of genetic variants, variant harmonization, primary analysis, supplementary and sensitivity analyses (one section on robust statistical methods and one on other approaches), data presentation, and interpretation. These guidelines will be updated based on feedback from the community and advances in the field. Updates will be made periodically as needed, and at least every 18 months.

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