Citations

Abstract Motivation: Reference genome assemblies are subject to change and refinement from time to time. Generally, researchers need to convert the results that have been analyzed according to old assemblies to newer versions, or vice versa, to facilitate meta-analysis, direct comparison, data integration and visualization. Several useful conversion tools can convert genome interval files in browser extensible data or general feature format, but none have the functionality to convert files in sequence alignment map or BigWig format. This is a significant gap in computational genomics tools, as these formats are the ones most widely used for representing high-throughput sequencing data, such as RNA-seq, chromatin immunoprecipitation sequencing, DNA-seq, etc. Results: Here we developed CrossMap, a versatile and efficient tool for converting genome coordinates between assemblies. CrossMap supports most of the commonly used file formats, including BAM, sequence alignment map, Wiggle, BigWig, browser extensible data, general feature format, gene transfer format and variant call format. Availability and implementation: CrossMap is written in Python and C. Source code and a comprehensive user’s manual are freely available at: http://crossmap.sourceforge.net/. Contact: Kocher.JeanPierre@mayo.edu or wang.liguo@mayo.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Background— Regenerative cell-based therapies are associated with limited myocardial retention of delivered stem cells. The objective of this study is to develop an endocardial delivery system for enhanced cell retention. Methods and Results— Stem cell retention was simulated in silico using 1- and 3-dimensional models of tissue distortion and compliance associated with delivery. Needle designs, predicted to be optimal, were accordingly engineered using nitinol, a nickel and titanium alloy displaying shape memory and superelasticity. Biocompatibility was tested with human mesenchymal stem cells. Experimental validation was performed with species-matched cells directly delivered into Langendorff-perfused porcine hearts or administered percutaneously into the endocardium of infarcted pigs. Cell retention was quantified by flow cytometry and real-time quantitative polymerase chain reaction methodology. Models, computing optimal distribution of distortion calibrated to favor tissue compliance, predicted that a 75°-curved needle featuring small-to-large graded side holes would ensure the highest cell retention profile. In isolated hearts, the nitinol curved needle catheter (C-Cath) design ensured 3-fold superior stem cell retention compared with a standard needle. In the setting of chronic infarction, percutaneous delivery of stem cells with C-Cath yielded a 37.7±7.1% versus 10.0±2.8% retention achieved with a traditional needle without effect on biocompatibility or safety. Conclusions— Modeling-guided development of a nitinol-based curved needle delivery system with incremental side holes achieved enhanced myocardial stem cell retention.

Abstract Recently, the term monoclonal gammopathy of renal significance (MGRS) was introduced to distinguish monoclonal gammopathies that result in the development of kidney disease from those that are benign. By definition, patients with MGRS have B-cell clones that do not meet the definition of multiple myeloma or lymphoma. Nevertheless, these clones produce monoclonal proteins that are capable of injuring the kidney resulting in permanent damage. Except for immunoglobulin light chain amyloidosis with heart involvement in which death can be rapid, treatment of MGRS is often indicated more to preserve kidney function and prevent recurrence after kidney transplantation rather than the prolongation of life. Clinical trials are rare for MGRS-related kidney diseases, except in immunoglobulin light chain amyloidosis. Treatment recommendations are therefore based on the clinical data obtained from treatment of the clonal disorder in its malignant state. The establishment of these treatment recommendations is important until data can be obtained by clinical trials of MGRS-related kidney diseases.

Key Points In combination with cyclophosphamide, intravenous busulfan is associated with better leukemia-free and overall survival in AML than TBI.

Glioma cell migration correlates with Pyk2 activity, but the intrinsic mechanism that regulates the activity of Pyk2 is not fully understood. Previous studies have supported a role for the N-terminal FERM domain in the regulation of Pyk2 activity as mutations in the FERM domain inhibit Pyk2 phosphorylation. To search for novel protein-protein interactions mediated by the Pyk2 FERM domain, we utilized a yeast two-hybrid genetic selection to identify the mammalian Ste20 homolog MAP4K4 as a binding partner for the Pyk2 FERM domain. MAP4K4 coimmunoprecipitated with Pyk2 and was a substrate for Pyk2 but did not coimmunoprecipitate with the closely related focal adhesion kinase FAK. Knockdown of MAP4K4 expression inhibited glioma cell migration and effectively blocked Pyk2 stimulation of glioma cell. Increased expression of MAP4K4 stimulated glioma cell migration; however, this stimulation was blocked by knockdown of Pyk2 expression. These data support that the interaction of MAP4K4 and Pyk2 is integrated with glioma cell migration and suggest that inhibition of this interaction may represent a potential therapeutic strategy to limit glioblastoma tumor dispersion.

Abstract Background: Given the high technical reproducibility and orders of magnitude greater resolution than microarrays, next-generation sequencing of mRNA (RNA-Seq) is quickly becoming the de facto standard for measuring levels of gene expression in biological experiments. Two important questions must be taken into consideration when designing a particular experiment, namely, 1) how deep does one need to sequence? and, 2) how many biological replicates are necessary to observe a significant change in expression? Results: Based on the gene expression distributions from 127 RNA-Seq experiments, we find evidence that 91% ± 4% of all annotated genes are sequenced at a frequency of 0.1 times per million bases mapped, regardless of sample source. Based on this observation, and combining this information with other parameters such as biological variation and technical variation that we empirically estimate from our large datasets, we developed a model to estimate the statistical power needed to identify differentially expressed genes from RNA-Seq experiments. Conclusions: Our results provide a needed reference for ensuring RNA-Seq gene expression studies are conducted with the optimally sample size, power, and sequencing depth. We also make available both R code and an Excel worksheet for investigators to calculate for their own experiments.

Abstract Motivation: Batch effects are due to probe-specific systematic variation between groups of samples (batches) resulting from experimental features that are not of biological interest. Principal component analysis (PCA) is commonly used as a visual tool to determine whether batch effects exist after applying a global normalization method. However, PCA yields linear combinations of the variables that contribute maximum variance and thus will not necessarily detect batch effects if they are not the largest source of variability in the data. Results: We present an extension of PCA to quantify the existence of batch effects, called guided PCA (gPCA). We describe a test statistic that uses gPCA to test whether a batch effect exists. We apply our proposed test statistic derived using gPCA to simulated data and to two copy number variation case studies: the first study consisted of 614 samples from a breast cancer family study using Illumina Human 660 bead-chip arrays, whereas the second case study consisted of 703 samples from a family blood pressure study that used Affymetrix SNP Array 6.0. We demonstrate that our statistic has good statistical properties and is able to identify significant batch effects in two copy number variation case studies. Conclusion: We developed a new statistic that uses gPCA to identify whether batch effects exist in high-throughput genomic data. Although our examples pertain to copy number data, gPCA is general and can be used on other data types as well. Availability and implementation: The gPCA R package (Available via CRAN) provides functionality and data to perform the methods in this article. Contact: reesese@vcu.edu or eckel@mayo.edu Supplementary information: Supplementary data are available at Bioinformatics online.