CPAP: Cancer Panel Analysis Pipeline

Targeted sequencing using next‐generation sequencing technologies is currently being rapidly adopted for clinical sequencing and cancer marker tests. However, no existing bioinformatics tool is available for the analysis and visualization of multiple targeted sequencing datasets. In the present study, we use cancer panel targeted sequencing datasets generated by the Life Technologies Ion Personal Genome Machine Sequencer as an example to illustrate how to develop an automated pipeline for the comparative analyses of multiple datasets. Cancer Panel Analysis Pipeline (CPAP) uses standard output files from variant calling software to generate a distribution map of SNPs among all of the samples in a circular diagram generated by Circos. The diagram is hyperlinked to a dynamic HTML table that allows the users to identify target SNPs by using different filters. CPAP also integrates additional information about the identified SNPs by linking to an integrated SQL database compiled from SNP‐related databases, including dbSNP, 1000 Genomes Project, COSMIC, and dbNSFP. CPAP only takes 17 min to complete a comparative analysis of 500 datasets. CPAP not only provides an automated platform for the analysis of multiple cancer panel datasets but can also serve as a model for any customized targeted sequencing project.     

Disentangling Pooled Triad Genotypes for Association Studies

Association studies that genotype affected offspring and their parents (triads) offer robustness to genetic population structure while enabling assessments of maternal effects, parent‐of‐origin effects, and gene‐by‐environment interaction. We propose case‐parents designs that use pooled DNA specimens to make economical use of limited available specimens. One can markedly reduce the number of genotyping assays required by randomly partitioning the case‐parent triads into pooling sets of h triads each and creating three pools from every pooling set, one pool each for mothers, fathers, and offspring. Maximum‐likelihood estimation of relative risk parameters proceeds via log‐linear modeling using the expectation‐maximization algorithm. The approach can assess offspring and maternal genetic effects and accommodate genotyping errors and missing genotypes. We compare the power of our proposed analysis for testing offspring and maternal genetic effects to that based on a difference approach and that of the gold standard based on individual genotypes, under a range of allele frequencies, missing parent proportions, and genotyping error rates. Power calculations show that the pooling strategies cause only modest reductions in power if genotyping errors are low, while reducing genotyping costs and conserving limited specimens.     

系列RNA-seq数据的表达模式聚类方法研究

目的转录组测序技术为研究特定组织细胞生理状态和分子水平变化提供有力方法。为了建立分子水平变化和组织细胞生理功能之间的关系并排除随机因素的干扰,需要建立基于系列RNA-seq数据的表达模式分析方法。方法本文提出了一种整合的方法（geneexpressionclustermethod,GECluster）用于对系列样本模式聚类。整合曲线拟合以及信息熵建立模型并提取特征属性,最后按照上面模型提供的特征属性对基因进行层次聚类分析。结果表达趋势一致的基因被很好地聚到一个类别中,功能富集分析发现这些基因具有很强的功能相关性,并与文献报道相吻合。结论GECluster可以更灵活客观对多样本系列RNA—seq数据挖掘共表达基因,为后期功能分析提供了更有效的研究方案。     

Pooled sera for cytotoxicity testing: accurate, time- and cost-effective preliminary crossmatches

To conserve sera, reduce technologist time and facilitate distribution of kidneys to the most likely recipient from groups of highly sensitized patients, we studied the feasibility of using pooled sera in preliminary crossmatches. From 16 chronic renal failure patients, 275 sera were studied against fresh cell panels from 24 to 35 donors. Using the antiglobulin crossmatch technique, sera were studied individually, in consecutive pools of five and in consecutive pools of 10. Reactions of component sera were assessed on a cell-by-cell comparison with their pools of five and 10 sera. Crossmatches performed with pools of five sera and pools of 10 sera detected the same cytotoxic reactions as did their component sera in 97.6% and 97.8% of the reactions, respectively. We conclude that 10 sera can be pooled so that preliminary crossmatch testing of all positive sera of all theoretically potential allograft recipients can be accomplished with accuracy and efficiency, even in the larger regional distribution centers.     

PKU in Minas Gerais State,Brazil: Mutation Analysis

This work was undertaken in order to ascertain the PKU mutational spectrum in Minas Gerais, Brazil, the relative frequency of the mutations in the State and the origin of these mutations by haplotype determination. Minas Gerais is a trihybrid population formed by miscegenation from Europeans, Africans and Amerindians. All 13 exons of the PAH gene from 78 PKU patients were analyzed, including splicing sites and the promoter region. We identified 30 different mutations and 98% of the PAH alleles were established. A new mutation (Q267X) was identified as well. The most common mutations found were V388M (21.2), R261Q (16.0%), IVS10‐11G>A (15.3%), I65T (5.8%), IVS2+5G>C (5.8%), R252W (5.1%), IVS2+5G>A (4.5%), P281L (3.8%) and L348V (3.2%). These nine mutations correspond to 80% of the PKU alleles in the state. Haplotypes were determined to characterize the origin of the PAH alleles. The majority of the mutations found, with respective haplotypes, are frequent in the Iberian Peninsula. However, there were some mutations that are rare in Europe and four previously unreported mutation‐haplotype associations. I65T and Q267X were found in association with haplotype 38 and may be African in origin or the result of miscegenation in the Brazilian population.     

The Use of Pooled Sera for HLA Cytotoxicity Crossmatching

A two-stage procedure is described for cytotoxicity tests in which three different sera from a prospective kidney recipient are pooled in each well of a standard microcytotoxicity test plate. The results are reproducible and as sensitive as those obtained with single sera tests. The technique permits a reduction in time required for a test and the number of wells that must be evaluated to screen a series of sera. It enables a laboratory to run all available sera on patients for cadaver kidney crossmatching and to eliminate hyperacute rejections. Serum pooling may also be used for screening of many sera against random cell panels.     

A Comparison of Individual Genotyping and Pooled DNA Analysis for Polymorphism Validation Prior to Large-Scale Genetic Studies

Polymorphism validation is an important issue in genetic studies because only polymorphic markers provide useful information. We analyzed genetic data for 180 SNPs in the human major histocompatibility complex region in Caucasian and Taiwanese populations, and evaluated ethnic heterogeneity between these populations to illustrate the importance of polymorphism validation. An initial individual genotyping experiment (IGE) with 95 samples was compared with a DNA pooling allele-typing experiment (PAE) of 630 individuals for polymorphism validation based on authentic data sets. Afterwards, all samples were genotyped individually in a confirmation study. Under narrow (broad) polymorphism criteria, 24 (41) polymorphic SNPs in Caucasians could not be validated in the Taiwanese population, suggesting a 13% (23%) inconsistency rate and revealing a strong discrepancy between genetic backgrounds, probably due to ethnic heterogeneity. IGE yielded high sensitivity and specificity for polymorphism validation, but may be sensitive to sampling variation. PAE showed high sensitivity (97%) and specificity (100%) using a narrow polymorphism criterion, but reduced specificity (83%) using a broad criterion. Public domain polymorphism databases should therefore be used with caution and polymorphism validation should be performed routinely prior to conducting large-scale genetic studies. PAE is a cost-saving, reliable alternative to IGE for polymorphism validation, especially for a stringent polymorphism criterion.     

Issues with RNA-seq analysis in non-model organisms: A salmonid example

High throughput sequencing (HTS) is useful for many purposes as exemplified by the other topics included in this special issue. The purpose of this paper is to look into the unique challenges of using this technology in non-model organisms where resources such as genomes, functional genome annotations or genome complexity provide obstacles not met in model organisms. To describe these challenges, we narrow our scope to RNA sequencing used to study differential gene expression in response to pathogen challenge. As a demonstration species we chose Atlantic salmon, which has a sequenced genome with poor annotation and an added complexity due to many duplicated genes. We find that our RNA-seq analysis pipeline deciphers between duplicates despite high sequence identity. However, annotation issues provide problems in linking differentially expressed genes to pathways. Also, comparing results between approaches and species are complicated due to lack of standardized annotation.     

Family-Based Association Tests for Different Family Structures Using Pooled DNA

DNA pooling is a cost‐effective strategy for genomewise association studies to identify disease genes. In the context of family‐based association studies, Risch & Teng (1998) mainly considered families of identical structures to detect associations between genetic markers and disease, and suggested possible approaches to incorporating different family types without a thorough study of their properties. However, families collected in real genetic studies often have different structures and, more importantly, the informativeness of each family structure depends on the disease model which is generally unknown. So there is a need to develop and investigate statistical methods to combine information from diverse family types. In this article, we propose a general strategy to incorporate different family types by assigning each family an “optimal” weight in association tests. In addition, we consider measurement errors in our analysis. When we evaluate our approach under different disease models and measurement errors, we find that our weighting scheme may lead to a substantial reduction in sample size required over the approach suggested by Risch & Teng (1998) , and measurement errors may have significant impact on the required sample size when the error rates are not negligible.     

Design and Analysis of Association Studies using Pooled DNA from Large Twin Samples

Evidence is mounting that multiple genes are involved in complex traits and that these each account for very small proportions of the overall phenotypic variance. Association studies of many markers in 1000s of individuals will be required to identify such genes. A number of large twin cohorts have already been collected and provide a valuable resource for carrying out studies that are robust to the effect of population stratification. Technologies based on microarrays will soon allow 1,000,000 SNPs to be typed at one time, however financial considerations prevent most researchers from using these approaches to genotype all individuals. Recently, microarrays have been shown to give accurate allele frequency measurements in pooled DNA samples and provide a simple way to select the best markers for individual genotyping. This drastically reduces the cost and workload of large scale association studies. One limitation of this methodology relates to the analytical procedures which have only been developed to allow comparison of two pools e.g. case/control pools. In this paper we use meta-regression to analyze pooled DNA data allowing the allele frequency in each pool to be related to the average quantitative phenotypic measure of the individuals whose DNA were used to construct the pools. Alongside this we describe a technique that can be used to determine the power for such studies. We present results from some preliminary investigations of different pooling strategies that can be applied to large twin samples and demonstrate that the method retains a large proportion of the power available from individual genotyping.     

Implementation of Automated Pipeline for Resting-State fMRI Analysis with PACS Integration

Journal of Digital Imaging - In recent years, the quantity and complexity of medical imaging acquisition and processing have increased tremendously. The explosion in volume and need for advanced...