In this task, you are given an abstract of article. Your task is to generate title for this article. Preferred titles are under thirty words.

Expression quantitative trait loci (eQTL) mapping aims to determine genomic regions that regulate gene transcription. Expression QTL is used to study the regulatory structure of normal tissues and to search for genetic factors in complex diseases such as cancer, diabetes, and cystic fibrosis. A modern eQTL dataset contains millions of SNPs and thousands of transcripts measured for hundreds of samples. This makes the analysis computationally complex as it involves independent testing for association for every transcript-SNP pair. The heavy computational burden makes eQTL analysis less popular, often forces analysts to restrict their attention to just a subset of transcripts and SNPs. As larger genotype and gene expression datasets become available, the demand for fast tools for eQTL analysis increases. We present a new method for fast eQTL analysis via linear models, called Matrix eQTL. Matrix eQTL can model and test for association using both linear regression and ANOVA models. The models can include covariates to account for such factors as population structure, gender, and clinical variables. It also supports testing of heteroscedastic models and models with correlated errors. In our experiment on large datasets Matrix eQTL was thousands of times faster than the existing popular software for QTL/eQTL analysis. Matrix eQTL is implemented as both Matlab and R packages and thus can easily be run on Windows, Mac OS, and Linux systems. The software is freely available at the following address: http://www.bios.unc.edu/research/genomic_software/Matrix_eQTL
Matrix eQTL: Ultra fast eQTL analysis via large matrix operations

Salmonella enterica serovar Typhimurium (S. Typhimurium) is a facultative intracellular pathogen that causes disease in a variety of hosts. S. Typhimurium actively invade host cells and typically reside within a membrane-bound compartment called the Salmonella-containing vacuole (SCV). The bacteria modify the fate of the SCV using two independent type III secretion systems (TTSS). TTSS are known to damage eukaryotic cell membranes and S. Typhimurium has been suggested to damage the SCV using its Salmonella pathogenicity island (SPI)-1 encoded TTSS. Here we show that this damage gives rise to an intracellular bacterial population targeted by the autophagy system during in vitro infection. Approximately 20% of intracellular S. Typhimurium colocalized with the autophagy marker GFP-LC3 at 1 h postinfection. Autophagy of S. Typhimurium was dependent upon the SPI-1 TTSS and bacterial protein synthesis. Bacteria targeted by the autophagy system were often associated with ubiquitinated proteins, indicating their exposure to the cytosol. Surprisingly, these bacteria also colocalized with SCV markers. Autophagy-deficient (atg5-/-) cells were more permissive for intracellular growth by S. Typhimurium than normal cells, allowing increased bacterial growth in the cytosol. We propose a model in which the host autophagy system targets bacteria in SCVs damaged by the SPI-1 TTSS. This serves to retain intracellular S. Typhimurium within vacuoles early after infection to protect the cytosol from bacterial colonization. Our findings support a role for autophagy in innate immunity and demonstrate that Salmonella infection is a powerful model to study the autophagy process.
Autophagy controls Salmonella infection in response to damage to the Salmonella-containing vacuole.

OBJECTIVE Funnel plots (plots of effect estimates against sample size) may be useful to detect bias in meta-analyses that were later contradicted by large trials. We examined whether a simple test of asymmetry of funnel plots predicts discordance of results when meta-analyses are compared to large trials, and we assessed the prevalence of bias in published meta-analyses.
DESIGN Medline search to identify pairs consisting of a meta-analysis and a single large trial (concordance of results was assumed if effects were in the same direction and the meta-analytic estimate was within 30% of the trial); analysis of funnel plots from 37 meta-analyses identified from a hand search of four leading general medicine journals 1993-6 and 38 meta-analyses from the second 1996 issue of the Cochrane Database of Systematic Reviews.
MAIN OUTCOME MEASURE Degree of funnel plot asymmetry as measured by the intercept from regression of standard normal deviates against precision.
RESULTS In the eight pairs of meta-analysis and large trial that were identified (five from cardiovascular medicine, one from diabetic medicine, one from geriatric medicine, one from perinatal medicine) there were four concordant and four discordant pairs. In all cases discordance was due to meta-analyses showing larger effects. Funnel plot asymmetry was present in three out of four discordant pairs but in none of concordant pairs. In 14 (38%) journal meta-analyses and 5 (13%) Cochrane reviews, funnel plot asymmetry indicated that there was bias.
CONCLUSIONS A simple analysis of funnel plots provides a useful test for the likely presence of bias in meta-analyses, but as the capacity to detect bias will be limited when meta-analyses are based on a limited number of small trials the results from such analyses should be treated with considerable caution.
Bias in meta-analysis detected by a simple, graphical test.