Estimating the sample mean and standard deviation from commonly reported quantiles in meta-analysis

Researchers increasingly use meta-analysis to synthesize the results of several studies in order to estimate a common effect. When the outcome variable is continuous, standard meta-analytic approaches assume that the primary studies report the sample mean and standard deviation of the outcome. However, when the outcome is skewed, authors sometimes summarize the data by reporting the sample median and one or both of (i) the minimum and maximum values and (ii) the first and third quartiles, but do not report the mean or standard deviation. To include these studies in meta-analysis, several methods have been developed to estimate the sample mean and standard deviation from the reported summary data. A major limitation of these widely used methods is that they assume that the outcome distribution is normal, which is unlikely to be tenable for studies reporting medians. We propose two novel approaches to estimate the sample mean and standard deviation when data are suspected to be non-normal. Our simulation results and empirical assessments show that the proposed methods often perform better than the existing methods when applied to non-normal data

Long-term impact of sewage sludge application on soil microbial biomass: An evaluation using meta-analysis

The Long-Term Sludge Experiments (LTSE) began in 1994 as part of continuing research into the effects of sludge-borne heavy metals on soil fertility. The long-term effects of Zn, Cu, and Cd on soil microbial biomass carbon (Cmic) were monitored for 8 years (1997-2005) in sludge amended soils at nine UK field sites. To assess the statutory limits set by the UK Sludge (Use in Agriculture) Regulations the experimental data has been reviewed using the statistical methods of meta-analysis. Previous LTSE studies have focused predominantly on statistical significance rather than effect size, whereas meta-analysis focuses on the magnitude and direction of an effect, i.e. the practical significance, rather than its statistical significance. The results presented here show that significant decreases in Cmic have occurred in soils where the total concentrations of Zn and Cu fall below the current UK statutory limits. For soils receiving sewage sludge predominantly contaminated with Zn, decreases of approximately 7–11% were observed at concentrations below the UK statutory limit. The effect of Zn appeared to increase over time, with increasingly greater decreases in Cmic observed over a period of 8 years. This may be due to an interactive effect between Zn and confounding Cu contamination which has augmented the bioavailability of these metals over time. Similar decreases (7–12%) in Cmic were observed in soils receiving sewage sludge predominantly contaminated with Cu; however, Cmic appeared to show of recovery after a period of 6 years. Application of sewage sludge predominantly contaminated with Cd appeared to have no effect on Cmic at concentrations below the current UK statutory limit

Gallus GBrowse: a unified genomic database for the chicken

Gallus GBrowse (http://birdbase.net/cgi-bin/gbrowse/gallus/) provides online access to genomic and other information about the chicken, Gallus gallus. The information provided by this resource includes predicted genes and Gene Ontology (GO) terms, links to Gallus In Situ Hybridization Analysis (GEISHA), Unigene and Reactome, the genomic positions of chicken genetic markers, SNPs and microarray probes, and mappings from turkey, condor and zebra finch DNA and EST sequences to the chicken genome. We also provide a BLAT server (http://birdbase.net/cgi-bin/webBlat) for matching user-provided sequences to the chicken genome. These tools make the Gallus GBrowse server a valuable resource for researchers seeking genomic information regarding the chicken and other avian species

Chimpanzee and Human Y Chromosomes Are Remarkably Divergent in Structure and Gene Content

LetterThe human Y chromosome began to evolve from an autosome hundreds of millions of years ago, acquiring a sex-determining function and undergoing a series of inversions that suppressed crossing over with the X chromosome[1, 2]. Little is known about the recent evolution of the Y chromosome because only the human Y chromosome has been fully sequenced. Prevailing theories hold that Y chromosomes evolve by gene loss, the pace of which slows over time, eventually leading to a paucity of genes, and stasis [3, 4]. These theories have been buttressed by partial sequence data from newly emergent plant and animal Y chromosomes [5, 6, 7, 8], but they have not been tested in older, highly evolved Y chromosomes such as that of humans. Here we finished sequencing of the male-specific region of the Y chromosome (MSY) in our closest living relative, the chimpanzee, achieving levels of accuracy and completion previously reached for the human MSY. By comparing the MSYs of the two species we show that they differ radically in sequence structure and gene content, indicating rapid evolution during the past 6 million years. The chimpanzee MSY contains twice as many massive palindromes as the human MSY, yet it has lost large fractions of the MSY protein-coding genes and gene families present in the last common ancestor. We suggest that the extraordinary divergence of the chimpanzee and human MSYs was driven by four synergistic factors: the prominent role of the MSY in sperm production, ‘genetic hitchhiking’ effects in the absence of meiotic crossing over, frequent ectopic recombination within the MSY, and species differences in mating behaviour. Although genetic decay may be the principal dynamic in the evolution of newly emergent Y chromosomes, wholesale renovation is the paramount theme in the continuing evolution of chimpanzee, human and perhaps other older MSYs.National Institutes of Health (U.S.)Howard Hughes Medical Institut

The Origin and Evolution of Mutations in Acute Myeloid Leukemia

SummaryMost mutations in cancer genomes are thought to be acquired after the initiating event, which may cause genomic instability and drive clonal evolution. However, for acute myeloid leukemia (AML), normal karyotypes are common, and genomic instability is unusual. To better understand clonal evolution in AML, we sequenced the genomes of M3-AML samples with a known initiating event (PML-RARA) versus the genomes of normal karyotype M1-AML samples and the exomes of hematopoietic stem/progenitor cells (HSPCs) from healthy people. Collectively, the data suggest that most of the mutations found in AML genomes are actually random events that occurred in HSPCs before they acquired the initiating mutation; the mutational history of that cell is “captured” as the clone expands. In many cases, only one or two additional, cooperating mutations are needed to generate the malignant founding clone. Cells from the founding clone can acquire additional cooperating mutations, yielding subclones that can contribute to disease progression and/or relapse

Model-Based Deconvolution of Cell Cycle Time-Series Data Reveals Gene Expression Details at High Resolution

In both prokaryotic and eukaryotic cells, gene expression is regulated across the cell cycle to ensure “just-in-time” assembly of select cellular structures and molecular machines. However, present in all time-series gene expression measurements is variability that arises from both systematic error in the cell synchrony process and variance in the timing of cell division at the level of the single cell. Thus, gene or protein expression data collected from a population of synchronized cells is an inaccurate measure of what occurs in the average single-cell across a cell cycle. Here, we present a general computational method to extract “single-cell”-like information from population-level time-series expression data. This method removes the effects of 1) variance in growth rate and 2) variance in the physiological and developmental state of the cell. Moreover, this method represents an advance in the deconvolution of molecular expression data in its flexibility, minimal assumptions, and the use of a cross-validation analysis to determine the appropriate level of regularization. Applying our deconvolution algorithm to cell cycle gene expression data from the dimorphic bacterium Caulobacter crescentus, we recovered critical features of cell cycle regulation in essential genes, including ctrA and ftsZ, that were obscured in population-based measurements. In doing so, we highlight the problem with using population data alone to decipher cellular regulatory mechanisms and demonstrate how our deconvolution algorithm can be applied to produce a more realistic picture of temporal regulation in a cell

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Transcriptome-Wide Identification of Novel Imprinted Genes in Neonatal Mouse Brain

Imprinted genes display differential allelic expression in a manner that depends on the sex of the transmitting parent. The degree of imprinting is often tissue-specific and/or developmental stage-specific, and may be altered in some diseases including cancer. Here we applied Illumina/Solexa sequencing of the transcriptomes of reciprocal F1 mouse neonatal brains and identified 26 genes with parent-of-origin dependent differential allelic expression. Allele-specific Pyrosequencing verified 17 of them, including three novel imprinted genes. The known and novel imprinted genes all are found in proximity to previously reported differentially methylated regions (DMRs). Ten genes known to be imprinted in placenta had sufficient expression levels to attain a read depth that provided statistical power to detect imprinting, and yet all were consistent with non-imprinting in our transcript count data for neonatal brain. Three closely linked and reciprocally imprinted gene pairs were also discovered, and their pattern of expression suggests transcriptional interference. Despite the coverage of more than 5000 genes, this scan only identified three novel imprinted refseq genes in neonatal brain, suggesting that this tissue is nearly exhaustively characterized. This approach has the potential to yield an complete catalog of imprinted genes after application to multiple tissues and developmental stages, shedding light on the mechanism, bioinformatic prediction, and evolution of imprinted genes and diseases associated with genomic imprinting

Genome remodelling in a basal-like breast cancer metastasis and xenograft

Massively parallel DNA sequencing technologies provide an unprecedented ability to screen entire genomes for genetic changes associated with tumor progression. Here we describe the genomic analyses of four DNA samples from an African-American patient with basal-like breast cancer: peripheral blood, the primary tumor, a brain metastasis, and a xenograft derived from the primary tumor. The metastasis contained two de novo mutations and a large deletion not present in the primary tumor, and was significantly enriched for 20 shared mutations. The xenograft retained all primary tumor mutations, and displayed a mutation enrichment pattern that paralleled the metastasis (16 of 20 genes). Two overlapping large deletions, encompassing CTNNA1, were present in all three tumor samples. The differential mutation frequencies and structural variation patterns in metastasis and xenograft compared to the primary tumor suggest that secondary tumors may arise from a minority of cells within the primary

A novel approach of homozygous haplotype sharing identifies candidate genes in autism spectrum disorder

Autism spectrum disorder (ASD) is a highly heritable disorder of complex and heterogeneous aetiology. It is primarily characterized by altered cognitive ability including impaired language and communication skills and fundamental deficits in social reciprocity. Despite some notable successes in neuropsychiatric genetics, overall, the high heritability of ASD (~90%) remains poorly explained by common genetic risk variants. However, recent studies suggest that rare genomic variation, in particular copy number variation, may account for a significant proportion of the genetic basis of ASD. We present a large scale analysis to identify candidate genes which may contain low-frequency recessive variation contributing to ASD while taking into account the potential contribution of population differences to the genetic heterogeneity of ASD. Our strategy, homozygous haplotype (HH) mapping, aims to detect homozygous segments of identical haplotype structure that are shared at a higher frequency amongst ASD patients compared to parental controls. The analysis was performed on 1,402 Autism Genome Project trios genotyped for 1 million single nucleotide polymorphisms (SNPs). We identified 25 known and 1,218 novel ASD candidate genes in the discovery analysis including CADM2, ABHD14A, CHRFAM7A, GRIK2, GRM3, EPHA3, FGF10, KCND2, PDZK1, IMMP2L and FOXP2. Furthermore, 10 of the previously reported ASD genes and 300 of the novel candidates identified in the discovery analysis were replicated in an independent sample of 1,182 trios. Our results demonstrate that regions of HH are significantly enriched for previously reported ASD candidate genes and the observed association is independent of gene size (odds ratio 2.10). Our findings highlight the applicability of HH mapping in complex disorders such as ASD and offer an alternative approach to the analysis of genome-wide association data