scholarly journals Tensor P-Spline Smoothing for Spatial Analysis of Plant Breeding Trials

2021 ◽  
Author(s):  
Hans-Peter Piepho ◽  
Martin Boer ◽  
Emlyn R. Williams
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Null Space ◽  
Spatial Interaction ◽  
Natural Extension ◽  
Covariance Structure ◽  
Spatial Modelling ◽  
Field Trials ◽  
Agricultural Field ◽  
Randomized Field Trials

Large agricultural field trials may display irregular spatial trends that cannot be fully captured by a purely randomization-based analysis. For this reason, paralleling the development of analysis-of-variance procedures for randomized field trials, there is a long history of spatial modelling for field trials, starting with the early work of Papadakis on nearest neighbour analysis, which can be cast in terms of first or second differences among neighbouring plot values. This kind of spatial modelling is amenable to a natural extension using P-splines, as has been demonstrated in recent publications in the field. Here, we consider the P-spline framework, focussing on model options that are easy to implement in linear mixed model packages. Two examples serve to illustrate and evaluate the methods. A key conclusion is that first differences are rather competitive with second differences. A further key observation is that second differences require special attention regarding the representation of the null space of the smooth terms for spatial interaction, and that an unstructured variance-covariance structure is required to ensure invariance to translation and rotation of eigenvectors associated with that null space. We develop a strategy that permits fitting this model with ease, but the approach is more demanding than that needed for fitting models using first differences. Hence, even though in other areas second differences are very commonly used in the application of P-splines, our main conclusion is that with field trials first differences have advantages for routine use.

scholarly journals Deep Sclerectomy with Goniosynechiolysis Ab Interno for Chronic Glaucoma Associated with Peripheral Anterior Synechiae

2015 ◽  
Vol 2015 ◽  
pp. 1-5 ◽  
Author(s):  
Alireza Mirshahi ◽  
Peter Raak ◽  
Katharina Ponto ◽  
Bernhard Stoffelns ◽  
Katrin Lorenz ◽  
...  
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Covariance Structure ◽  
Glaucoma Surgery ◽  
Deep Sclerectomy ◽  
Chronic Glaucoma ◽  
Target Pressure ◽  
The Mean ◽  
One Year ◽  
Ab Interno

Purpose. To report one-year results of phacoemulsification combined with deep sclerectomy and goniosynechiolysis ab interno for chronic glaucoma associated with peripheral anterior synechiae (PAS).Methods. We retrospectively analyzed medical charts of 16 patients (20 eyes) treated by one-site combined phacoemulsification and deep sclerectomy with goniosynechiolysis ab interno. PAS were transected by a spatula introduced into the anterior chamber through a paracentesis. To account for the correlation of right and left eyes a linear mixed model with unstructured covariance structure was calculated.Results. The mean preoperative intraocular pressure (IOP) was20.3±5.2 mmHg with2.4±1.0medications. One year postoperatively, the mean IOP was15.3±3.3 mmHg (P=0.004, pairedt-test) with0.6±1.0medications. A postoperative IOP of ≤21 mmHg without medication was achieved in 17 of 19 eyes (89.5%) and in 12/19 eyes (63.2%) at 3 and 12 months after surgery, respectively. In the remaining eyes (10.5% at 3 months and 36.8% at 12 months), additional medication led to an IOP ≤21 mmHg or the target pressure. No case required further glaucoma surgery. In one eye, conversion of the surgery to trabeculectomy was necessary due to Descemet’s window rupture.Conclusions. With goniosynechiolysis ab interno, effective and safe nonpenetrating glaucoma surgery is possible in presence of PAS.

scholarly journals Bayesian Linear Mixed Models for Motif Activity Analysis

2019 ◽  
Author(s):  
Simone Lederer ◽  
Tom Heskes ◽  
Simon J. van Heeringen ◽  
Cornelis A. Albers
Keyword(s):  
Gene Expression ◽  
Dna Sequences ◽  
Ridge Regression ◽  
Mixed Model ◽  
Target Genes ◽  
Linear Mixed Model ◽  
Covariance Structure ◽  
Regulatory Elements ◽  
Mathematical Explanation ◽  
Experimental Conditions

AbstractMotivationCellular identity and behavior is controlled by complex gene regulatory networks. Transcription factors (TFs) bind to specific DNA sequences to regulate the transcription of their target genes. On the basis of these TF motifs in cis-regulatory elements we can model the influence of TFs on gene expression. In such models of TF motif activity the data is usually modeled assuming a linear relationship between the motif activity and the gene expression level. A commonly used method to model motif influence is based on Ridge Regression. One important assumption of linear regression is the independence between samples. However, if samples are generated from the same cell line, tissue, or other biological source, this assumption may be invalid. This same assumption of independence is also applied to different, yet similar, experimental conditions, which may also be inappropriate. In theory, the independence assumption between samples could lead to loss in signal detection. Here we investigate whether a Bayesian model that allows for correlations results in more accurate inference of motif activities.ResultsWe extend the Ridge Regression to a Bayesian Linear Mixed Model, which allows us to model dependence between different samples. In a simulation study, we in-vestigate the differences between the two model assumptions. We show that our Bayesian Linear Mixed Model implementation outperforms Ridge Regression in a simulation scenario where the noise, the signal that can not be explained by TF motifs, is uncorrelated. However, we demonstrate that there is no such gain in performance if the noise has a similar covariance structure over samples as the signal that can be explained by motifs. We give a mathematical explanation to why this is the case. Using two representative real data sets we show that at most ∼ 40% of the signal is explained by motifs using the linear model. With these data there is no advantage to using the Bayesian Linear Mixed Model, due to the similarity of the covariance structure.Availability & ImplementationThe project implementation is available at https://github.com/Sim19/SimGEXPwMotifs.

scholarly journals 15 EFFECT OF SEMEN THAW METHOD ON CONCEPTION RATE IN DAIRY HEIFER HERDS

2005 ◽  
Vol 17 (2) ◽  
pp. 157 ◽  
Author(s):  
M. Kaproth ◽  
H. Rycroft ◽  
G. Gilbert ◽  
G. Abdel-Azim ◽  
B. Putnam ◽  
...  
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Semen Quality ◽  
Sperm Quality ◽  
Field Trials ◽  
Conception Rate ◽  
Warm Water ◽  
Dairy Heifer

Semen processed with procedures permitting a flexible thaw method is used to breed millions of cows yearly. “Pocket thawing” is widely used as an alternative to warm-water thawing with such semen. To pocket thaw, a straw is retrieved from cryostorage, immediately wrapped in a folded paper towel, and moved to a thermally protected pocket for 2 to 3 min of thawing within the pocket before AI gun loading. Published field data are lacking for comparisons of such a thaw method with those for semen prepared to permit flexible-thawing. We measured the effect of warm-water or pocket thaw on conception rate in four dairy heifer herds using semen prepared with methods previously optimized for flexible-thawing success. Semen processing (Anderson S et al. 1994 J. Dairy Sci. 77, 2302–2307) includes two-step whole-milk extension, static vapor tank freezing (0.5-mL straws), and IMV Digitcool mechanical freezing (0.25-mL straws). It is unclear which specific processing steps permit flexible thawing. These procedures have been developed using breeding results from decades of field trials by professional inseminators using both pocket and warm-water thaw. Semen prepared from each of 12 sires produced equal straw units at 10 and 15 million total sperm per straw, in both 0.5- and 0.25-mL straw packages. Professional inseminators used each combination evenly over 16 months. Additional commercial semen (55% of total) from the same source was used. The thaw methods alternated weekly. Thaw effect on conception status, from 70 day non-return data for 11,215 services (67.6% conception rate), was estimated by a generalized linear mixed model. Neither thaw method nor total sperm per straw significantly affected conception rate (P = 0.658, 0.769, respectively). Bull, herd, inseminator within herd, year, season, and straw size did significantly affect conception rate (P < 0.05). No thaw method interactions with herd, sperm number, season, and straw package size were significant (P = 0.297, 0.526, 0.365, 0.723, respectively). This suggests that if semen has been prepared with procedures specific to flexible-thawing, it can be either pocket thawed or warm-water thawed within a range of herdsman or inseminator practices, season, or straw packaging choices. Even at 10 million, the lowest total sperm per straw, pocket thaw was equally as successful as warm-water thaw. We generally observe that in vitro sperm quality, as expected, is maximal for rapidly thawed straws, with slower thawing resulting in lower values. However, while it appears that conventional measures of in vitro semen quality are improved with fast thaw rates, these measures do not appear to correspond to higher in vivo fertility for semen prepared intentionally to be flexibly thawed. We conclude that, for semen prepared with procedures that permit flexible thawing, the thaw method, whether pocket or warm-water thaw, does not affect conception under commercial conditions and with routine semen handling methods. We thank the herd owners and their staff, the inseminators, and Hap Allen, Ron Hunt, Gordon Nickerson, and Bryan Krick of Genex for their help and cooperation.

Health-Related Quality Of Life In Transfusion-Dependent Patients With Myelodysplastic Syndromes Treated With Deferasirox. A Multicenter Prospective Study

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 2980-2980
Author(s):  
Fabio Efficace ◽  
Valeria Santini ◽  
Giorgio La Nasa ◽  
Francesco Cottone ◽  
Carlo Finelli ◽  
...  
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Ferritin Level ◽  
Covariance Structure ◽  
Transfusion Independence ◽  
Related Quality ◽  
Eortc Qlq C30 ◽  
Health Related ◽  
Eortc Qlq ◽  
Over Time

Abstract Background Anemia is a common symptom in patients with Myelodysplastic Syndromes (MDS) and although erythropoietic agents are often active, it is frequently treated with red blood cell (RBC) transfusions. A substantial proportion of patients might also eventually become transfusion-dependent and, Iron-chelating therapies might be important to minimize complications of iron overload. Objectives To investigate the impact of deferasirox therapy on health-related quality of life (HRQOL) of lower risk transfusion-dependent MDS patients over a one year period. Secondary objectives were to investigate relationships between HRQOL and ferritin levels and to explore the prognostic value of baseline HRQOL on the probability of achieving transfusion independence. Patients and Methods This was a prospective study whose clinical findings (i.e., primary endpoint was safety and tolerability) were previously reported. HRQOL was a secondary endpoint of the study and we herein report, for the first time, HRQOL prospective findings. Eligible patients included: MDS patients 18 years or older, International Prognostic Scoring System (IPSS) low or intermediate-1 risk and diagnosed with transfusional siderosis following a minimum of 20 blood transfusions. Patients received daily oral deferasirox at a dose between 10 and 30 mg/kg of body weight for a period of 1 year. HRQOL was assessed with the EORTC QLQ-C30. HRQOL at baseline and at 3, 6, 9 and 12 months after treatment start. The EORTC QLQ-C30 consists of 30 items and includes five functional scales (physical, role, emotional, social, and cognitive), three symptom (fatigue, nausea and vomiting and pain) and a global health status/QOL scale and six single items (dyspnea, insomnia, appetite loss, constipation, diarrhea and financial difficulties). The mean trend of HRQOL over time was estimated via a linear mixed model with a one-step autoregressive covariance structure. Such covariance structure provided the best model fit among those investigated. Results Overall, 159 patients were screened at 37 centers. The median duration of disease at enrollment was 32 months and median number of units of packed RBC received was 37. Seven patients did not start treatment at all and thus there were 152 expected HRQOL forms at baseline assessment. Out of these, 146 patients returned the questionnaire yielding a baseline compliance of 96%. No statistically significant differences over time were found for any scale of the EORTC QLQ-C30. Figure 1 depicts mean scores over time for selected scales of: fatigue, physical functioning, pain and global HRQOL. No HRQOL differences were found between patients with serum ferritin levels lower or higher than 2000 μg/L (pretreatment median value) at baseline. Also, the possible impact of ferritin level on HRQoL over time was estimated via a linear mixed model with a one-step autoregressive covariance structure. Coefficients and p values are reported in table 1. The prognostic impact of baseline HRQOL on the probability of achieving transfusion independence (i.e., defined as freedom from transfusion for 3 consecutive months) was investigated. Higher severity of pain (P=0.007) was associated with a greater likelihood of achieving transfusion independence. Multivariate analysis, controlling for age, IPSS risk score, time from diagnosis, number of previous blood transfusions and baseline ferritin level confirmed the independent value of pain (P=0.003). Conclusion Current findings suggest that Deferasirox therapy does not decrease HRQOL in lower risk transfusion-dependent MDS patients. Patients with higher baseline pain severity seems more likely to achieve transfusion independence and further analysis is needed to understand underlying reasons. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Fast Spectrophotometric Method as Alternative for CuO Oxidation to Assess Lignin in Soils with Different Tree Cover

Forests ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1262
Author(s):  
Tiziana Danise ◽  
Michele Innangi ◽  
Elena Curcio ◽  
Antonietta Fioretto ◽  
Georg Guggenberger
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Mineral Soil ◽  
Soil Samples ◽  
Tree Cover ◽  
Plant Residues ◽  
Agricultural Field ◽  
Acetyl Bromide ◽  
Plant Component ◽  
Cuo Oxidation

Given the ongoing climate change, estimating the amount of less degradable plant compounds that can be stored in the soil, such as lignin, is a topic of primary importance. There are few methods applicable to soils for the determination of lignin, such as the copper oxide (CuO) oxidation method (CuOL). Acetyl bromide spectrophotometric lignin (ABSL) could be a valid alternative providing information that is less detailed compared to CuOL, but it offers data on the bulk amount of lignin and may offer a valid, fast, and cheap alternative to the CuO method. The aim of this work was to compare ABSL with the CuO method on several soils receiving plant residues from different trees. Mineral soil samples from 0 to 10 cm depth were obtained from a former agricultural site in northern Italy (Brusciana, Tuscany), where different tree plantations were established 22 years ago. The plantations were white poplar and common walnut, which were also intercropped with other species such as hazelnut, Italian alder, and autumn olive. Soil samples under these plantations were also compared to soil under an adjacent agricultural field. In general, the amount of lignin in the afforested stands was approximately double than in the agricultural field as determined by either method. The two methods returned a largely different scale of values due to their different mechanisms of action. The acid-to-aldehyde ratio of syringyl structural units highlights that forest plantation provides a plant input material that is more slowly oxidatively degraded compared to arable soil. A linear mixed model proved that ABSL performed well in relation to CuOL, especially when considering the random variation in the model given by the plantation field design. In conclusion, ABSL can be considered a valid proxy of soil C pool derived from structural plant component, although further analyses are needed.

scholarly journals Application and Analysis of a Composite Sampling Strategy to Cost-Effectively Compare Nutritive Characteristics of Perennial Ryegrass Cultivars in Field Trials

Agronomy ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 1152
Author(s):  
Clare Leddin ◽  
Khageswor Giri ◽  
Kevin Smith
Keyword(s):  
Perennial Ryegrass ◽  
Data Model ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Sampling Strategy ◽  
Field Trials ◽  
Spatial And Temporal Variation ◽  
Full Data ◽  
Composite Sampling ◽  
Composite Samples

Pasture nutritive value is economically important in south-eastern Australian dairy production systems, yet measurement of nutritive characteristics in pasture cultivar evaluation trials is not routinely undertaken, primarily due to cost. An approach aiming to reduce the total laboratory analysis costs in multi-harvest field trials by testing some entries as composite samples is provided. A field trial evaluating 31 trial entries sown in 4 replicates was used. On nine harvest occasions, samples were collected from each plot, dried, ground and analysed using near infrared spectroscopy for key nutritive characteristics (metabolisable energy (ME), crude protein (CP) and neutral detergent fibre (NDF)). Additionally, composite samples of 17 of the 31 entries from each harvest were created by combining sub-samples of material from each of four replicate plots into a single sample that was also analysed. A linear mixed model (LMM) analysis accounting for spatial and temporal variation as well as spatial and temporal correlations was conducted, comparing the full data model where all plots at all harvests were tested individually to a data model where some entries were evaluated as individual plots and others as composites. The precision and accuracy of the estimates for the two models were similar and best linear unbiased prediction (BLUP) means of the composite sampling strategy model were comparable to the full data model. It was concluded that if composite sampling is used in conjunction with testing samples from individual plots on a selection of cultivars, statistically valid inferences are possible and the total cost of determining the nutritive characteristics of perennial ryegrass cultivars in field trials can be reduced.

scholarly journals MTG2: An efficient algorithm for multivariate linear mixed model analysis based on genomic information

2015 ◽  
Author(s):  
Sang Hong Lee ◽  
Julius van der Werf
Keyword(s):  
Complex Traits ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Covariance Structure ◽  
Random Regression ◽  
Current Standard ◽  
Model Framework ◽  
Genetic Covariance ◽  
Mixed Model Analysis ◽  
Mixed Model Equation

We have developed an algorithm for genetic analysis of complex traits using genome-wide SNPs in a linear mixed model framework. Compared to current standard REML software based on the mixed model equation, our method could be more than 1000 times faster. The advantage is largest when there is only a single genetic covariance structure. The method is particularly useful for multivariate analysis, including multi-trait models and random regression models for studying reaction norms. We applied our proposed method to publicly available mice and human data and discuss advantages and limitations.

scholarly journals Modeling the longitudinal outcomes of congestive heart failure patients: A case study at Wachemo University Nigist Eleni Mohammed Memorial Referral Hospital

2021 ◽  
Author(s):  
Mohammed Sultan ◽  
Ritbano Ahmed
Keyword(s):  
Heart Failure ◽  
Congestive Heart Failure ◽  
Longitudinal Data ◽  
Mixed Models ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Linear Mixed Models ◽  
Covariance Structure ◽  
Repeated Measurements ◽  
Within Subjects

Abstract The linear mixed model is one of the common models used to analyze the longitudinal data;it may comprise of separate (Univariate), joint Bivariate, and joint Multivariate linear mixed model, which is predicted on the number of response variables incorporated in the analysis. Adjusting for correlation matrix and covariance matrix between and within subjects is one reason why modern longitudinal data analysis techniques are deemed more appropriate than some of the previous methods of analysis. Some studies assume that the correlation between observation is zero. However, it is unlikely that repeated measurements on the same individual Will actually be independent. To that end, comparing the different linear mixed models identifying the appropriate model demonstrates that the evolution of patients with congestive heart failure is necessary.In this study the separate, bivariate, and multivariate linear mixed models were compared with different covariance and correlation structures. Finally, a multivariate linear mixed model with autoregressive order one correlation structure and unstructured covariance structure for random effects, to consider within and between patient's variations, was considered as a best model to depict the evolution of patients with congestive heart failure.

A comparative study of different covariance structure models for the analysis of repeated measurement data

2016 ◽  
Vol 10 (01) ◽  
pp. 1750007
Author(s):  
Yazhou Wu ◽  
Ling Zhang ◽  
Liang Zhou ◽  
Xiaoyu Liu ◽  
Ling Liu ◽  
...  
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Random Effect ◽  
Measurement Data ◽  
Covariance Structure ◽  
Repeated Measurement ◽  
Covariance Structures ◽  
Analysis And Design ◽  
The One ◽  
The Individual

In repeated measurement data, the variables are not independent, and a certain auto-correlation typically exists between different levels of repeated measurement factors. The random error is composed of at least two parts, i.e. the individual random effect and the intra-individual multi-repeated measurement effect. Traditional statistical analysis methods (such as the [Formula: see text]-test and the one-way analysis of variance) are not applicable. The linear mixed model has been widely applied for the analysis and design of repeated measurement data. This paper focuses on medical examples and describes the selection of a covariance structure for the linear mixed model of repeated measurement in the modeling of different variance–covariance structures. By selecting different covariance structures, we can perform the parameter estimation and statistical test for the fixed effect of repeated measurement data, the parameters of random effects, and the covariance matrix. The results are analyzed and compared to provide a reference for applying the linear mixed model of repeated measurement to medical research.

scholarly journals Tracking Within-Athlete Changes in Whole-Body Fat Percentage in Wheelchair Athletes

2021 ◽  
Vol 16 (1) ◽  
pp. 13-18
Author(s):  
Victoria L. Goosey-Tolfrey ◽  
Julia O. Totosy de Zepetnek ◽  
Mhairi Keil ◽  
Katherine Brooke-Wavell ◽  
Alan M. Batterham
Keyword(s):  
Body Fat ◽  
Prediction Error ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Covariance Structure ◽  
Dual Energy ◽  
Whole Body ◽  
Body Fat Percentage ◽  
Fat Percentage ◽  
X Ray

Purpose: To evaluate the tracking of within-athlete changes in criterion measures of whole-body fat percentage (BF%; dual-energy X-ray absorptiometry) with skinfold thickness (Σ 4, 6, or 8) in wheelchair basketball players. Methods: Dual-energy X-ray absorptiometry-derived whole BF% and Σ 4, 6, or 8 skinfolds were obtained at 5 time points over 15 months (N = 16). A linear mixed model with restricted maximum likelihood (random intercept, with identity covariance structure) to derive the within-athlete prediction error for predicting criterion BF% from Σ skinfolds was used. This prediction error allowed us to evaluate how well a simple measure of the Σ skinfolds could track criterion changes in BF %; that is, the authors derived the change in Σ skinfolds that would have to be observed in an individual athlete to conclude that a substantial change in criterion BF% had occurred. Data were log-transformed prior to analysis. Results: The Σ 8 skinfolds was the most precise practical measure for tracking changes in BF%. For the monitoring of an individual player, a change in Σ 8 skinfolds by a factor of greater than 1.28 (multiply or divide by 1.28) is associated with a practically meaningful change in BF% (≥1 percentage point). Conclusions: The Σ 8 skinfolds can track changes in BF% within individuals with reasonable precision, providing a useful field monitoring tool in the absence of often impractical criterion measures.

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