An efficient kk-means-type algorithm for clustering datasets with incomplete records

The $k$-means algorithm is arguably the most popular nonparametric clustering method but cannot generally be applied to datasets with incomplete records. The usual practice then is to either impute missing values under an assumed missing-completely-at-random mechanism or to ignore the incomplete records, and apply the algorithm on the resulting dataset. We develop an efficient version of the $k$-means algorithm that allows for clustering in the presence of incomplete records. Our extension is called $k_m$-means and reduces to the $k$-means algorithm when all records are complete. We also provide initialization strategies for our algorithm and methods to estimate the number of groups in the dataset. Illustrations and simulations demonstrate the efficacy of our approach in a variety of settings and patterns of missing data. Our methods are also applied to the analysis of activation images obtained from a functional Magnetic Resonance Imaging experiment.Comment: 21 pages, 12 figures, 3 tables, in press, Statistical Analysis and Data Mining -- The ASA Data Science Journal, 201

Statistical methods for estimation, testing, and clustering with gene expression data

This thesis is comprised of a collection of papers on the analysis of gene expression data, namely high-throughput RNA-sequencing (RNA-seq) data, with some methods generalizable to other scientific data. We first introduce a method for identifying differentially expressed genes using an empirical-Bayes-type analysis of RNA-seq data that employs efficient computational algorithms. A generalizable method for reparameterization is discussed, and simulation is used to demonstrate its importance in test performance. Next, exact tests for a monotone mean expression pattern are developed and incorporated into an existing pipeline for analysis of RNA-seq data. The advantages of computing exact $p$-values and of borrowing information across genes are demonstrated. The monotone tests are compared to existing tests and shown to perform favorably, particularly on data where the monotone hypothesis is appropriate. Finally, we extend existing $k$-means clustering algorithms to accommodate data with missing values and replicates. Among many other uses, clustering is often performed on gene expression patterns as an exploratory or summarizing tool. We show that in many cases, the extended algorithms improve upon existing methods and techniques without requiring significantly more computational expenditure

Transcriptomic and anatomical complexity of primary, seminal, and crown roots highlight root type-specific functional diversity in maize (Zea mays L.)

Maize develops a complex root system composed of embryonic and post-embryonic roots. Spatio-temporal differences in the formation of these root types imply specific functions during maize development. A comparative transcriptomic study of embryonic primary and seminal, and post-embryonic crown roots of the maize inbred line B73 by RNA sequencing along with anatomical studies were conducted early in development. Seminal roots displayed unique anatomical features, whereas the organization of primary and crown roots was similar. For instance, seminal roots displayed fewer cortical cell files and their stele contained more meta-xylem vessels. Global expression profiling revealed diverse patterns of gene activity across all root types and highlighted the unique transcriptome of seminal roots. While functions in cell remodeling and cell wall formation were prominent in primary and crown roots, stress-related genes and transcriptional regulators were over-represented in seminal roots, suggesting functional specialization of the different root types. Dynamic expression of lignin biosynthesis genes and histochemical staining suggested diversification of cell wall lignification among the three root types. Our findings highlight a cost-efficient anatomical structure and a unique expression profile of seminal roots of the maize inbred line B73 different from primary and crown roots

Complexity and specificity of the maize (Zea mays L.) root hair transcriptome

Root hairs are tubular extensions of epidermis cells. Transcriptome profiling demonstrated that the single cell-type root hair transcriptome was less complex than the transcriptome of multiple cell-type primary roots without root hairs. In total, 831 genes were exclusively and 5585 genes were preferentially expressed in root hairs [false discovery rate (FDR) ≤1%]. Among those, the most significantly enriched Gene Ontology (GO) functional terms were related to energy metabolism, highlighting the high energy demand for the development and function of root hairs. Subsequently, the maize homologs for 138 Arabidopsis genes known to be involved in root hair development were identified and their phylogenetic relationship and expression in root hairs were determined. This study indicated that the genetic regulation of root hair development in Arabidopsis and maize is controlled by common genes, but also shows differences which need to be dissected in future genetic experiments. Finally, a maize root view of the eFP browser was implemented including the root hair transcriptome of the present study and several previously published maize root transcriptome data sets. The eFP browser provides color-coded expression levels for these root types and tissues for any gene of interest, thus providing a novel resource to study gene expression and function in maize roots

Genes and Small RNA Transcripts Exhibit Dosage-Dependent Expression Pattern in Maize Copy-Number Alterations

Copy-number alterations are widespread in animal and plant genomes, but their immediate impact on gene expression is still unclear. In animals, copy-number alterations usually exhibit dosage effects, except for sex chromosomes which tend to be dosage compensated. In plants, genes within small duplications (\u3c100 kb) often exhibit dosage-dependent expression, whereas large duplications (\u3e50 Mb) are more often dosage compensated. However, little or nothing is known about expression in moderately-sized (1–50 Mb) segmental duplications, and about the response of small RNAs to dosage change. Here, we compared maize (Zea mays) plants with two, three, and four doses of a 14.6-Mb segment of chromosome 1 that contains ∼300 genes. Plants containing the duplicated segment exhibit dosage-dependent effects on ear length and flowering time. Transcriptome analyses using GeneChip and RNA-sequencing methods indicate that most expressed genes and unique small RNAs within the duplicated segments exhibit dosage-dependent transcript levels. We conclude that dosage effect is the predominant regulatory response for both genes and unique small RNA transcripts in the segmental dosage series we tested. To our knowledge this is the first analysis of small RNA expression in plant gene dosage variants. Because segmental duplications comprise a significant proportion of eukaryotic genomes, these findings provide important new insight into the regulation of genes and small RNAs in response to dosage changes

Extensive tissue-specific transcriptomic plasticity in maize primary roots upon water deficit

Water deficit is the most important environmental constraint severely limiting global crop growth and productivity. This study investigated early transcriptome changes in maize (Zea mays L.) primary root tissues in response to moderate water deficit conditions by RNA-Sequencing. Differential gene expression analyses revealed a high degree of plasticity of the water deficit response. The activity status of genes (active/inactive) was determined by a Bayesian hierarchical model. In total, 70% of expressed genes were constitutively active in all tissues. In contrast, \u3c3% (50 genes) of water deficit-responsive genes (1915) were consistently regulated in all tissues, while \u3e75% (1501 genes) were specifically regulated in a single root tissue. Water deficit-responsive genes were most numerous in the cortex of the mature root zone and in the elongation zone. The most prominent functional categories among differentially expressed genes in all tissues were ‘transcriptional regulation’ and ‘hormone metabolism’, indicating global reprogramming of cellular metabolism as an adaptation to water deficit. Additionally, the most significant transcriptomic changes in the root tip were associated with cell wall reorganization, leading to continued root growth despite water deficit conditions. This study provides insight into tissue-specific water deficit responses and will be a resource for future genetic analyses and breeding strategies to develop more drought-tolerant maize cultivars

Root Type-Specific Reprogramming of Maize Pericycle Transcriptomes by Local High Nitrate Results in Disparate Lateral Root Branching Patterns

The adaptability of root system architecture to unevenly distributed mineral nutrients in soil is a key determinant of plant performance. The molecular mechanisms underlying nitrate dependent plasticity of lateral root branching across the different root types of maize are only poorly understood. In this study, detailed morphological and anatomical analyses together with cell type-specific transcriptome profiling experiments combining laser capture microdissection with RNA-seq were performed to unravel the molecular signatures of lateral root formation in primary, seminal, crown, and brace roots of maize (Zea mays) upon local high nitrate stimulation. The four maize root types displayed divergent branching patterns of lateral roots upon local high nitrate stimulation. In particular, brace roots displayed an exceptional architectural plasticity compared to other root types. Transcriptome profiling revealed root type-specific transcriptomic reprogramming of pericycle cells upon local high nitrate stimulation. The alteration of the transcriptomic landscape of brace root pericycle cells in response to local high nitrate stimulation was most significant. Root type-specific transcriptome diversity in response to local high nitrate highlighted differences in the functional adaptability and systemic shoot nitrogen starvation response during development. Integration of morphological, anatomical, and transcriptomic data resulted in a framework underscoring similarity and diversity among root types grown in heterogeneous nitrate environments

Abemaciclib in Combination With Endocrine Therapy for Patients With Hormone Receptor-Positive, HER2-Negative Metastatic Breast Cancer: A Phase 1b Study

Background Cyclin-dependent kinases (CDK) 4 and 6 regulate G1 to S cell cycle progression and are often altered in cancers. Abemaciclib is a selective inhibitor of CDK4 and CDK6 approved for administration on a continuous dosing schedule as monotherapy or as combination therapy with an aromatase inhibitor or fulvestrant in patients with advanced or metastatic breast cancer. This Phase 1b study evaluated the safety and tolerability, pharmacokinetics, and antitumor activity of abemaciclib in combination with endocrine therapy for metastatic breast cancer (MBC), including aromatase inhibitors (letrozole, anastrozole, or exemestane) or tamoxifen. Patients and Methods Women ≥18 years old with hormone receptor positive (HR+), human epidermal growth factor receptor 2 negative (HER2-) MBC were eligible for enrollment. Eligibility included measurable disease or non-measurable but evaluable bone disease by Response Evaluation Criteria in Solid Tumours (RECIST) v1.1, Eastern Cooperative Oncology Group performance status 0–1, and no prior chemotherapy for metastatic disease. Adverse events were graded by the National Cancer Institute Common Terminology Criteria for Adverse Events v4.0 and tumor response were assessed by RECIST v1.1. Results Sixty-seven patients were enrolled and received abemaciclib 200 mg every 12 hours in combination with letrozole (Part A, n=20), anastrozole (Part B, n=16), tamoxifen (Part C, n=16), or exemestane (Part D, n=15). The most common treatment-emergent adverse events (TEAE) were diarrhea, fatigue, nausea, and abdominal pain. Grade 4 TEAEs were reported in five patients (one each with hyperglycemia, hypertension, neutropenia, procedural hemorrhage, and sepsis). There was no effect of abemaciclib or endocrine therapy on the pharmacokinetics of any combination study drug. Across all treated patients, the median progression-free survival was 25.4 months (95% confidence interval: 18.0, 35.8). The objective response rate was 38.9% in 36 patients with measurable disease. Conclusions Abemaciclib in combination with multiple endocrine therapy options exhibited manageable safety and promising antitumor activity in patients with HR+, HER2- MBC. Clinical Trial Registration https://clinicaltrials.gov/, identifier NCT0205713