LIKELIHOOD OF A PARTICULAR ORDER OF GENETIC MARKERS AND THE CONSTRUCTION OF GENETIC MAPS

2008 ◽  
Vol 06 (01) ◽  
pp. 125-162 ◽  
Author(s):  
S. TEWARI ◽  
J. ARNOLD ◽  
S. M. BHANDARKAR
Keyword(s):  
Genetic Markers ◽  
Expectation Maximization ◽  
Goodness Of Fit ◽  
Genomic Sequence ◽  
Probability Model ◽  
Genetic Maps ◽  
Model Framework ◽  
Marker Data ◽  
Chi Squared ◽  
Genetic Interval

We model the recombination process of fungal systems via chromatid exchange in meiosis, which accounts for any type of bivalent configuration in a genetic interval in any specified order of genetic markers, for both random spore and tetrad data. First, a probability model framework is developed for two genes and then generalized for an arbitrary number of genes. Maximum likelihood estimators (MLEs) for both random and tetrad data are developed. It is shown that the MLE of recombination for tetrad data is uniformly more efficient over that from random spore data by a factor of at least 4 usually. The MLE for the generalized probability framework is computed using the expectation-maximization (EM) algorithm. Pearson's chi-squared statistic is computed as a measure of goodness of fit using a product-multinomial setup. We implement our model with genetic marker data on the whole genome of Neurospora crassa. Simulated annealing is used to search for the best order of genetic markers for each chromosome, and the goodness of fit value is evaluated for model assumptions. Inferred map orders are corroborated by genomic sequence, with the exception of linkage groups I, II, and V.

DESIGN AND ANALYSIS OF AN EFFICIENT RECURSIVE LINKING ALGORITHM FOR CONSTRUCTING LIKELIHOOD BASED GENETIC MAPS FOR A LARGE NUMBER OF MARKERS

2007 ◽  
Vol 05 (02a) ◽  
pp. 201-250 ◽  
Author(s):  
S. TEWARI ◽  
S. M. BHANDARKAR ◽  
J. ARNOLD
Keyword(s):  
Genetic Markers ◽  
Time Complexity ◽  
Recursive Algorithm ◽  
Genetic Maps ◽  
Fungal Genome ◽  
Worst Case Analysis ◽  
Worst Case ◽  
Computation Process ◽  
Genetic Interval ◽  
Using Data

A multi-locus likelihood of a genetic map is computed based on a mathematical model of chromatid exchange in meiosis that accounts for any type of bivalent configuration in a genetic interval in any specified order of genetic markers. The computational problem is to calculate the likelihood (L) and maximize L by choosing an ordering of genetic markers on the map and the recombination distances between markers. This maximum likelihood estimate (MLE) could be found either with a straightforward algorithm or with the proposed recursive linking algorithm that implements the likelihood computation process involving an iterative procedure is called Expectation Maximization (EM). The time complexity of the straightforward algorithm is exponential without bound in the number of genetic markers, and implementation of the model with a straightforward algorithm for more than seven genetic markers is not feasible, thus motivating the critical importance of the proposed recursive linking algorithm. The recursive linking algorithm decomposes the pool of genetic markers into segments and renders the model implementable for hundreds of genetic markers. The recursive algorithm is shown to reduce the order of time complexity from exponential to linear in the number of markers. The improvement in time complexity is shown theoretically by a worst-case analysis of the algorithm and supported by run time results using data on linkage group-II of the fungal genome Neurospora crassa.

Physical mapping of 38 highly informative genetic markers to 10 intervals of chromosome 11q: integration of the physical and genetic maps

1994 ◽  
Vol 58 (2) ◽  
pp. 81-85 ◽  
Author(s):  
D. HUNT ◽  
V. VAN HEYNINGEN ◽  
C. JONES ◽  
C. McCONVILLE ◽  
F. J. BENHAM
Keyword(s):  
Genetic Markers ◽  
Physical Mapping ◽  
Genetic Maps

Reversing the Friday peak in metastatic cord compression referrals: Not as simple as previously thought?

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e14050-e14050
Author(s):  
Olusola Michael Adeleke ◽  
Rubyyat A Hakim ◽  
Laurence Dean ◽  
Huma Zahid ◽  
Rongyu Lin ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Single Point ◽  
District General Hospital ◽  
Cord Compression ◽  
Radiology Reporting ◽  
Goodness Of Fit Test ◽  
Tertiary Centre ◽  
Chi Squared ◽  
Early Case ◽  
The Uk

e14050 Background: Historically, metastatic spinal cord compression (MSCC) referrals trend towards a Friday peak in incidence (Koiter E, Radioth Onc 2013). However, data from a single, tertiary centre in the UK showed a reversal in the Friday peak (Adeleke S, Annals of Oncology 2020). This was attributed to early case referrals and quicker treatment decisions. In this new study, we explored whether a similar pattern was apparent in multiple district general hospital (DGH) settings and attempt to identify underlying causes. DGHs manage a larger proportion of cancer patients in the UK. Methods: 1,069 patients between 1 Jan 2015 and 31 Dec 2020 were identified across 4 hospitals in Kent, UK with a population of 1.6 million people. 220, 181, 182, 159, 134 and 193 MSCC patients were identified annually (2015-2020). Commonest cancers were prostate (24.1%), lung (19.3%) and breast (12.3%). Thoracic and lumbar regions constituted 80% of MSCC sites. Kruskal Wallis was used to compare differences in referrals across weekdays. Data was then dichotomised to Fridays only vs. other days of the week combined, as previously reported (De Bono B, Acta Neurochir 2019). Chi squared was used to compare frequency of referrals between the two groups. Chi squared goodness of fit test was conducted to detect if Friday reflected the day with highest referrals across the week. Results: Across the region, 2015 saw the highest number of Friday referrals relative to other days, p= 0.002. Friday referrals continued to drop, year on year, until 2018 with a corresponding increase in mid-week referrals. After 2018, there was a return in trend to a further Friday peak across the region, though p= 0.836. On an individual hospital basis, the persistent Friday peak in the region was driven by two hospitals. Having a 7-day acute oncology service (AOS), 7-day radiology reporting and single referral point of contact in the department, were factors identified that kept the referrals across the week uniform. On another note, a substantial shift towards a single 8Gy fraction vs. 20Gy in 5 fractions was observed across the region. This change coincided with SCORAD III data (Hoskin P, ASCO 2017) and demonstrates adherence to evidence-based practice in the region. Conclusions: This large multi-centre retrospective study shows a differential referral pattern in the region, with hospitals with 7-day AOS/Radiology reporting and single point of referral (e.g, similar to MSCC coordinator role) having a quicker treatment turnaround and uniform referrals across the week. The MSCC coordinator has been shown to streamline service, ensure timely decision-making and improved survival outcomes (Richards L, Spine J 2017). The role is recommended by NICE UK. DGHs should consider appointing an MSCC coordinator when designing/auditing their service. The shift towards single 8Gy fraction can provide a ‘one-stop’ service where patients are scanned, planned and treated on the same day.

Edinburgh Handedness Inventory Scores: Caucasian and American Indian College Students

1994 ◽  
Vol 78 (2) ◽  
pp. 675-680 ◽  
Author(s):  
Sherry M. Dingman ◽  
Mary A. Mroczka
Keyword(s):  
College Students ◽  
American Indian ◽  
American Indians ◽  
Goodness Of Fit ◽  
Single Gene ◽  
Empirical Support ◽  
Racial Groups ◽  
Frequency Distributions ◽  
Chi Squared ◽  
American Indian College Students

Laterality Quotients for 80 American Indian college students were less right-biased than those for 80 Caucasian college students on the Edinburgh Handedness Inventory. Oldfield's 1971 empirically derived deciles for the Edinburgh Handedness Inventory were used to assign decile levels to the data. Deciles were then used to assign data to one of three proposed handedness phenotype classifications. Pheno-type classifications were based on Annett's 1985 proposed distribution for a single gene theorized to underlie human handedness. Chi-squared goodness-of-fit analysis showed that the data for Caucasian college students did not differ significantly from what would be anticipated by Annett's model, but American Indians differed significantly. Results provide empirical support for the hypothesis that frequency distributions for Annett's hypothesized right-shift gene may differ across racial groups.

scholarly journals MENENTUKAN DISTRIBUSI REPRESENTATIF FREQUENSI CURAHAN HUJAN HARIAN MAKSIMUM DENGAN METODEHISTOGRAM DAN METODE PARAMETIK DI PROVINSI SUMATERA BARAT

2018 ◽  
Vol 1 (1) ◽  
Author(s):  
Selpa Dewi
Keyword(s):  
Goodness Of Fit ◽  
Type Iii ◽  
Pearson Type ◽  
Chi Squared ◽  
Anderson Darling

Penelitian ini bertujuan untuk menentukan distribusi yang representatif frequensi curahan hujan harian maksimum di Provinsi Sumatera Barat. Data yang digunakan untuk penelitian ini diambil dari data hujan maksimum harian selama 20 sampai 40 tahunan, dengan 24 stasiun penakar hujan untuk provinsi Sumatera Barat. Data masing-masing stasiun kemudian disusun dalam dua jenis deret data, yaitu deret data annual maxima dan deret data annual exceedances. Dari hasil uji deret data ini diharapkan mengikuti satu atau beberapa dari distribusi yang umum dipakai dalam hidrologi rekayasa, yaitu distribusi normal, normal-log, Gumbel, Gama-II, Gama-III dan distribusi Log-Pearson Type III (LP-III). Dengan mengunakan uji kecocokan (goodness of fit), uji parametrik, Chi-Squared test, Kolmogorov-Smirnovtest dan Anderson-Darling test ditambah dengan metode histrogram (visual).Kata kunci:Intensitas hujan distribusi representative annual maxima, annual exceendances, goodness of fitprovinsi Sumatera Barat.

scholarly journals A theory of memory for binary sequences: Evidence for a mental compression algorithm in humans

2021 ◽  
Vol 17 (1) ◽  
pp. e1008598
Author(s):  
Samuel Planton ◽  
Timo van Kerkoerle ◽  
Leïla Abbih ◽  
Maxime Maheu ◽  
Florent Meyniel ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Model Comparison ◽  
Transition Probability ◽  
Probability Model ◽  
Working Memory Capacity ◽  
Compression Algorithm ◽  
Binary Sequences ◽  
Fixed Sequence ◽  
Transition Probability Model ◽  
Human Adults

Working memory capacity can be improved by recoding the memorized information in a condensed form. Here, we tested the theory that human adults encode binary sequences of stimuli in memory using an abstract internal language and a recursive compression algorithm. The theory predicts that the psychological complexity of a given sequence should be proportional to the length of its shortest description in the proposed language, which can capture any nested pattern of repetitions and alternations using a limited number of instructions. Five experiments examine the capacity of the theory to predict human adults’ memory for a variety of auditory and visual sequences. We probed memory using a sequence violation paradigm in which participants attempted to detect occasional violations in an otherwise fixed sequence. Both subjective complexity ratings and objective violation detection performance were well predicted by our theoretical measure of complexity, which simply reflects a weighted sum of the number of elementary instructions and digits in the shortest formula that captures the sequence in our language. While a simpler transition probability model, when tested as a single predictor in the statistical analyses, accounted for significant variance in the data, the goodness-of-fit with the data significantly improved when the language-based complexity measure was included in the statistical model, while the variance explained by the transition probability model largely decreased. Model comparison also showed that shortest description length in a recursive language provides a better fit than six alternative previously proposed models of sequence encoding. The data support the hypothesis that, beyond the extraction of statistical knowledge, human sequence coding relies on an internal compression using language-like nested structures.

scholarly journals Estimating the Best-Fitted Probability Distribution for Monthly Maximum Temperature at the Sylhet Station in Bangladesh

2021 ◽  
Vol 2 (2) ◽  
pp. 60-67
Author(s):  
Rashidul Hasan Rashidul Hasan
Keyword(s):  
Probability Distribution ◽  
Goodness Of Fit ◽  
Probability Distributions ◽  
Probability Model ◽  
Temperature Data ◽  
Maximum Temperature ◽  
Chi Square ◽  
Goodness Of Fit Tests ◽  
Anderson Darling ◽  
Log Normal

The estimation of a suitable probability model depends mainly on the features of available temperature data at a particular place. As a result, existing probability distributions must be evaluated to establish an appropriate probability model that can deliver precise temperature estimation. The study intended to estimate the best-fitted probability model for the monthly maximum temperature at the Sylhet station in Bangladesh from January 2002 to December 2012 using several statistical analyses. Ten continuous probability distributions such as Exponential, Gamma, Log-Gamma, Beta, Normal, Log-Normal, Erlang, Power Function, Rayleigh, and Weibull distributions were fitted for these tasks using the maximum likelihood technique. To determine the model’s fit to the temperature data, several goodness-of-fit tests were applied, including the Kolmogorov-Smirnov test, Anderson-Darling test, and Chi-square test. The Beta distribution is found to be the best-fitted probability distribution based on the largest overall score derived from three specified goodness-of-fit tests for the monthly maximum temperature data at the Sylhet station.

scholarly journals Demographic Seasonality

2019 ◽  
Vol 22 (03) ◽  
pp. 187-194 ◽  
Author(s):  
Johan Fellman
Keyword(s):  
At Risk ◽  
Goodness Of Fit ◽  
Extreme Values ◽  
Demographic Data ◽  
Climatic Conditions ◽  
Data Sets ◽  
Test Statistic ◽  
Population At Risk ◽  
Chi Squared ◽  
Number Of Births

AbstractThe seasonality of demographic data has been of great interest. It depends mainly on the climatic conditions, and the findings may vary from study to study. Commonly, the studies are based on monthly data. The population at risk plays a central role. For births or deaths over short periods, the population at risk is proportional to the lengths of the months. Hence, one must analyze the number of births (and deaths) per day. If one studies the seasonality of multiple maternities, the population at risk is the total monthly number of confinements and the number of multiple maternities in a given month must be compared with the monthly number of all maternities. Consequently, when one considers the monthly rates of multiple maternities, the monthly number of births is eliminated and one obtains an unaffected seasonality measure of the rates. In general, comparisons between the seasonality of different data sets presuppose standardization of the data to indices with common means, mainly 100. If one assumes seasonality as ‘non-flatness’ throughout a year, a chi-squared test would be an option, but this test calculates only the heterogeneity and the same test statistic can be obtained for data sets with extreme values occurring in consecutive months or in separate months. Hence, chi-squared tests for seasonality are weak because of this arbitrariness and cannot be considered a model test. When seasonal models are applied, one must pay special attention to how well the applied model fits the data. If the goodness of fit is poor, nonsignificant models obtained can erroneously lead to statements that the seasonality is slight, although the observed seasonal fluctuations are marked. In this study, we investigate how the application of seasonal models can be applied to different demographic variables.

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