scholarly journals Children with 5′-end NF1 gene mutations are more likely to have glioma

2017 ◽  
Vol 3 (5) ◽  
pp. e192 ◽  
Author(s):  
Corina Anastasaki ◽  
Stephanie M. Morris ◽  
Feng Gao ◽  
David H. Gutmann
Keyword(s):  
Gene Mutation ◽  
Statistical Significance ◽  
Gene Mutations ◽  
Neurofibromatosis Type ◽  
Published Data ◽  
Data Sets ◽  
Nonsense Mutations ◽  
Data Set ◽  
Nf1 Gene ◽  
The Relationship

Objective:To ascertain the relationship between the germline NF1 gene mutation and glioma development in patients with neurofibromatosis type 1 (NF1).Methods:The relationship between the type and location of the germline NF1 mutation and the presence of a glioma was analyzed in 37 participants with NF1 from one institution (Washington University School of Medicine [WUSM]) with a clinical diagnosis of NF1. Odds ratios (ORs) were calculated using both unadjusted and weighted analyses of this data set in combination with 4 previously published data sets.Results:While no statistical significance was observed between the location and type of the NF1 mutation and glioma in the WUSM cohort, power calculations revealed that a sample size of 307 participants would be required to determine the predictive value of the position or type of the NF1 gene mutation. Combining our data set with 4 previously published data sets (n = 310), children with glioma were found to be more likely to harbor 5′-end gene mutations (OR = 2; p = 0.006). Moreover, while not clinically predictive due to insufficient sensitivity and specificity, this association with glioma was stronger for participants with 5′-end truncating (OR = 2.32; p = 0.005) or 5′-end nonsense (OR = 3.93; p = 0.005) mutations relative to those without glioma.Conclusions:Individuals with NF1 and glioma are more likely to harbor nonsense mutations in the 5′ end of the NF1 gene, suggesting that the NF1 mutation may be one predictive factor for glioma in this at-risk population.

scholarly journals Uncovering Proximity of Chromosome Territories using Classical Algebraic Statistics

2015 ◽  
Vol 6 (2) ◽  
Author(s):  
Javier Arsuaga ◽  
Ido Heskia ◽  
Serkan Hosten ◽  
Tatiana Maskalevich
Keyword(s):  
Statistical Significance ◽  
Three Dimensional ◽  
Spatial Proximity ◽  
Published Data ◽  
Algebraic Statistics ◽  
Data Sets ◽  
Complex Data ◽  
Data Set ◽  
Complex Data Sets ◽  
Human Blood Lymphocyte

Exchange type chromosome aberrations (ETCAs) are rearrangements of the genome that occur when chromosomes break and the resulting fragments rejoin with fragments from other chromosomes or from other regions within the same chromosome. ETCAs are commonly observed in cancer cells and in cells exposed to radiation. The frequency of these chromosome rearrangements is correlated with their spatial proximity, therefore it can be used to infer the three dimensional organization of the genome. Extracting statistical significance of spatial proximity from cancer and radiation data has remained somewhat elusive because of the sparsity of the data. We here propose a new approach to study the three dimensional organization of the genome using algebraic statistics. We test our method on a published data set of irradiated human blood lymphocyte cells. We provide a rigorous method for testing the overall organization of the genome, and in agreement with previous results we find a random relative positioning of chromosomes with the exception of the chromosome pairs {1,22} and {13,14} that have a significantly larger number of ETCAs than the rest of the chromosome pairs suggesting their spatial proximity. We conclude that algebraic methods can successfully be used to analyze genetic data and have potential applications to larger and more complex data sets. 

PSVI-8 Meta-regression Analysis to Determine the Relationship Between Growing Pig Body Weight and Variation

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 218-219
Author(s):  
Andres Fernando T Russi ◽  
Mike D Tokach ◽  
Jason C Woodworth ◽  
Joel M DeRouchey ◽  
Robert D Goodband ◽  
...  
Keyword(s):  
Body Weight ◽  
Regression Analysis ◽  
Sample Size ◽  
Polynomial Regression ◽  
Data Sets ◽  
Regression Equations ◽  
Prediction Equations ◽  
Data Set ◽  
Rate Of Increase ◽  
The Relationship

Abstract The swine industry has been constantly evolving to select animals with improved performance traits and to minimize variation in body weight (BW) in order to meet packer specifications. Therefore, understanding variation presents an opportunity for producers to find strategies that could help reduce, manage, or deal with variation of pigs in a barn. A systematic review and meta-analysis was conducted by collecting data from multiple studies and available data sets in order to develop prediction equations for coefficient of variation (CV) and standard deviation (SD) as a function of BW. Information regarding BW variation from 16 papers was recorded to provide approximately 204 data points. Together, these data included 117,268 individually weighed pigs with a sample size that ranged from 104 to 4,108 pigs. A random-effects model with study used as a random effect was developed. Observations were weighted using sample size as an estimate for precision on the analysis, where larger data sets accounted for increased accuracy in the model. Regression equations were developed using the nlme package of R to determine the relationship between BW and its variation. Polynomial regression analysis was conducted separately for each variation measurement. When CV was reported in the data set, SD was calculated and vice versa. The resulting prediction equations were: CV (%) = 20.04 – 0.135 × (BW) + 0.00043 × (BW)2, R2=0.79; SD = 0.41 + 0.150 × (BW) - 0.00041 × (BW)2, R2 = 0.95. These equations suggest that there is evidence for a decreasing quadratic relationship between mean CV of a population and BW of pigs whereby the rate of decrease is smaller as mean pig BW increases from birth to market. Conversely, the rate of increase of SD of a population of pigs is smaller as mean pig BW increases from birth to market.

scholarly journals Do galactic bars depend on environment?: an information theoretic analysis of Galaxy Zoo 2

2020 ◽  
Vol 501 (1) ◽  
pp. 994-1001
Author(s):  
Suman Sarkar ◽  
Biswajit Pandey ◽  
Snehasish Bhattacharjee
Keyword(s):  
Spatial Distribution ◽  
Mutual Information ◽  
Local Density ◽  
Statistical Significance ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Host Galaxy ◽  
Data Sets ◽  
Data Set ◽  
Information Theoretic

ABSTRACT We use an information theoretic framework to analyse data from the Galaxy Zoo 2 project and study if there are any statistically significant correlations between the presence of bars in spiral galaxies and their environment. We measure the mutual information between the barredness of galaxies and their environments in a volume limited sample (Mr ≤ −21) and compare it with the same in data sets where (i) the bar/unbar classifications are randomized and (ii) the spatial distribution of galaxies are shuffled on different length scales. We assess the statistical significance of the differences in the mutual information using a t-test and find that both randomization of morphological classifications and shuffling of spatial distribution do not alter the mutual information in a statistically significant way. The non-zero mutual information between the barredness and environment arises due to the finite and discrete nature of the data set that can be entirely explained by mock Poisson distributions. We also separately compare the cumulative distribution functions of the barred and unbarred galaxies as a function of their local density. Using a Kolmogorov–Smirnov test, we find that the null hypothesis cannot be rejected even at $75{{\ \rm per\ cent}}$ confidence level. Our analysis indicates that environments do not play a significant role in the formation of a bar, which is largely determined by the internal processes of the host galaxy.

Relative testis size and mating systems in anurans: large testis in multiple-male mating in foam-nesting frogs

2011 ◽  
Vol 61 (2) ◽  
pp. 225-238 ◽  
Author(s):  
Wen Bo Liao ◽  
Zhi Ping Mi ◽  
Cai Quan Zhou ◽  
Ling Jin ◽  
Xian Han ◽  
...  
Keyword(s):  
Sperm Competition ◽  
Published Data ◽  
Male Mating ◽  
Data Sets ◽  
Testis Size ◽  
Data Set ◽  
Monogamous Species ◽  
Large Testis ◽  
Testes Size ◽  
Testis Mass

AbstractComparative studies of the relative testes size in animals show that promiscuous species have relatively larger testes than monogamous species. Sperm competition favours the evolution of larger ejaculates in many animals – they give bigger testes. In the view, we presented data on relative testis mass for 17 Chinese species including 3 polyandrous species. We analyzed relative testis mass within the Chinese data set and combining those data with published data sets on Japanese and African frogs. We found that polyandrous foam nesting species have relatively large testes, suggesting that sperm competition was an important factor affecting the evolution of relative testes size. For 4 polyandrous species testes mass is positively correlated with intensity (males/mating) but not with risk (frequency of polyandrous matings) of sperm competition.

A novel NF1 gene mutation in an Italian family with neurofibromatosis type 1

2010 ◽  
Vol 27 (4) ◽  
pp. 635-638
Author(s):  
Anna Lia Gabriele ◽  
Martino Ruggieri ◽  
Alessandra Patitucci ◽  
Angela Magariello ◽  
Francesca Luisa Conforti ◽  
...  
Keyword(s):  
Gene Mutation ◽  
Neurofibromatosis Type 1 ◽  
Neurofibromatosis Type ◽  
Italian Family ◽  
Nf1 Gene

scholarly journals Recommendations for bacterial ribosome profiling experiments based on bioinformatic evaluation of published data

2020 ◽  
Vol 295 (27) ◽  
pp. 8999-9011 ◽  
Author(s):  
Alina Glaub ◽  
Christopher Huptas ◽  
Klaus Neuhaus ◽  
Zachary Ardern
Keyword(s):  
Ribosome Profiling ◽  
Published Data ◽  
Data Sets ◽  
Drug Induced ◽  
Data Set ◽  
Protein Coding ◽  
Bacterial Ribosome ◽  
Translation Start ◽  
Selection Step ◽  
Basic Characteristics

Ribosome profiling (RIBO-Seq) has improved our understanding of bacterial translation, including finding many unannotated genes. However, protocols for RIBO-Seq and corresponding data analysis are not yet standardized. Here, we analyzed 48 RIBO-Seq samples from nine studies of Escherichia coli K12 grown in lysogeny broth medium and particularly focused on the size-selection step. We show that for conventional expression analysis, a size range between 22 and 30 nucleotides is sufficient to obtain protein-coding fragments, which has the advantage of removing many unwanted rRNA and tRNA reads. More specific analyses may require longer reads and a corresponding improvement in rRNA/tRNA depletion. There is no consensus about the appropriate sequencing depth for RIBO-Seq experiments in prokaryotes, and studies vary significantly in total read number. Our analysis suggests that 20 million reads that are not mapping to rRNA/tRNA are required for global detection of translated annotated genes. We also highlight the influence of drug-induced ribosome stalling, which causes bias at translation start sites. The resulting accumulation of reads at the start site may be especially useful for detecting weakly expressed genes. As different methods suit different questions, it may not be possible to produce a “one-size-fits-all” ribosome profiling data set. Therefore, experiments should be carefully designed in light of the scientific questions of interest. We propose some basic characteristics that should be reported with any new RIBO-Seq data sets. Careful attention to the factors discussed should improve prokaryotic gene detection and the comparability of ribosome profiling data sets.

scholarly journals Statistical issues about solar–climate relations

2010 ◽  
Vol 6 (5) ◽  
pp. 565-573 ◽  
Author(s):  
P. Yiou ◽  
E. Bard ◽  
P. Dandin ◽  
B. Legras ◽  
P. Naveau ◽  
...  
Keyword(s):  
Time Series ◽  
Solar Activity ◽  
Geomagnetic Field ◽  
Degrees Of Freedom ◽  
Statistical Significance ◽  
Data Sets ◽  
Statistical Issues ◽  
The Relationship ◽  
Temperature Time ◽  
Field Variability

Abstract. The relationship between solar activity and temperature variation is a frequently discussed issue in climatology. This relationships is usually hypothesized on the basis of statistical analyses of temperature time series and time series related to solar activity. Recent studies (Le Mouël et al., 2008, 2009; Courtillot et al., 2010) focus on the variabilities of temperature and solar activity records to identify their relationships. We discuss the meaning of such analyses and propose a general framework to test the statistical significance for these variability-based analyses. This approach is illustrated using European temperature data sets and geomagnetic field variations. We show that tests for significant correlation between observed temperature variability and geomagnetic field variability is hindered by a low number of degrees of freedom introduced by excessively smoothing the variability-based statistics.

Spinal neurofibromatosis in a family with classical neurofibromatosis type 1 and a novel NF1 gene mutation

2014 ◽  
Vol 21 (2) ◽  
pp. 328-330 ◽  
Author(s):  
Francesco Nicita ◽  
Isabella Torrente ◽  
Alberto Spalice ◽  
Irene Bottillo ◽  
Laura Papetti ◽  
...  
Keyword(s):  
Gene Mutation ◽  
Neurofibromatosis Type 1 ◽  
Neurofibromatosis Type ◽  
Nf1 Gene

Nature of intrafractional and interfractional prostate motion during stereotactic radiation.

2016 ◽  
Vol 34 (2_suppl) ◽  
pp. 152-152
Author(s):  
Karthikeyan Perumal ◽  
Mahadev Potharaju
Keyword(s):  
Treatment Time ◽  
Published Data ◽  
Data Sets ◽  
Data Set ◽  
Stereotactic Radiation ◽  
X Ray ◽  
Total Treatment Time ◽  
Prostate Motion ◽  
Predictable Pattern ◽  
Total Treatment

152 Background: To characterize the intra-fraction and inter-fraction prostate motion as tracked by the X-ray images of the implanted gold fiducials during stereotactic radiotherapy with CyberKnife. The published data have analysed the linear and angular prostate motion intrafraction and interfraction prostate motion among patients. We sought to quantify the same within each patient. Methods: Twenty Five patients with localized prostate cancer treated with CyberKnife radiosurgery between January 2013 and August 2015 were studied retrospectively. A data set constitutes the deviations derived from X-ray images obtained between two consecutive couch motions. Results: Included in the analysis were 3926 data sets. A total of 210 non-coplanar fields were used per fraction. The mean total treatment time for all fields per fraction was 36.13 minutes. The detected and corrected movements over all were in a range of ± 10.1 mm in linear direction (Right: mean 1.1±0.4 mm; Left: mean 1.0±0.6 mm; Superior: mean 0.7±0.3 mm; Inferior: mean 1.6±0.6 mm; Anterior: mean 1.6±0.7 mm; Posterior: mean 0.5±0.3 mm with maximum (max) movement range of Right max 9.9±6.4 mm, Left max 7.1±3.4 mm, Superior max 8.6±5.4 mm, Inferior max 10.1±8.5 mm, Anterior max 9.2±6.5 mm, Posterior max 8.4±2.9 mm) and angular movements were in a range of ± 6.7 deg in all directions (Right Angle: mean 0.6±0.3 deg; Left Angle: mean 0.6±0.3 deg; Head Up(H-U): mean 1.3±0.6 deg; Head Down(H-D): mean 1.4±0.6 deg; Counter-Clockwise movement (CCW): mean 0.7±0.3 deg; Clockwise movement (CW): mean 0.5±0.3 deg with max rotation range of Right angle max 2.4±2 deg, Left angle max 2.7±2 deg, H-U max 10.2±3.5 deg, H-D max 6.7±4.8 deg, CCW 4±2.9 deg, CW max 2.8±2.4 deg). There was an unpredictable change in prostate motion inter-fraction in each patient. But, a unique observation is that a predictable pattern exists for prostate motion intra-fraction within a patient. Change in the linear or angular prostate motion intra-fraction in any direction is not erratic. Conclusions: The linear and rotational prostate motion intra-fraction in any direction has a predictable pattern and any change is gradual and not erratic. The motion shows secular trend during the course of treatment.

Determination of Optimal Clusters Using a Genetic Algorithm

2008 ◽  
pp. 98-117 ◽  
Author(s):  
Tushar ◽  
Tushar ◽  
Shibendu Shekhar Roy ◽  
Dilip Kumar Pratihar
Keyword(s):  
Genetic Algorithm ◽  
Threshold Value ◽  
Data Sets ◽  
Self Organizing Map ◽  
Data Set ◽  
Fcm Algorithm ◽  
Data Points ◽  
The Relationship

Clustering is a potential tool of data mining. A clustering method analyzes the pattern of a data set and groups the data into several clusters based on the similarity among themselves. Clusters may be either crisp or fuzzy in nature. The present chapter deals with clustering of some data sets using Fuzzy C-Means (FCM) algorithm and Entropy-based Fuzzy Clustering (EFC) algorithm. In FCM algorithm, the nature and quality of clusters depend on the pre-defined number of clusters, level of cluster fuzziness and a threshold value utilized for obtaining the number of outliers (if any). On the other hand, the quality of clusters obtained by the EFC algorithm is dependent on a constant used to establish the relationship between the distance and similarity of two data points, a threshold value of similarity and another threshold value used for determining the number of outliers. The clusters should ideally be distinct and at the same time compact in nature. Moreover, the number of outliers should be as minimum as possible. Thus, the above problem may be posed as an optimization problem, which will be solved using a Genetic Algorithm (GA). The best set of multi-dimensional clusters will be mapped into 2-D for visualization using a Self-Organizing Map (SOM).

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