Evaluation of Algorithm Performance in ChIP-Seq Peak Detection

Next-generation DNA sequencing coupled with chromatin immunoprecipitation (ChIP-seq) is revolutionizing our ability to interrogate whole genome protein-DNA interactions. Identification of protein binding sites from ChIP-seq data has required novel computational tools, distinct from those used for the analysis of ChIP-Chip experiments. The growing popularity of ChIP-seq spurred the development of many different analytical programs (at last count, we noted 31 open source methods), each with some purported advantage. Given that the literature is dense and empirical benchmarking challenging, selecting an appropriate method for ChIP-seq analysis has become a daunting task. Herein we compare the performance of eleven different peak calling programs on common empirical, transcription factor datasets and measure their sensitivity, accuracy and usability. Our analysis provides an unbiased critical assessment of available technologies, and should assist researchers in choosing a suitable tool for handling ChIP-seq data

A Monte Carlo-based framework enhances the discovery and interpretation of regulatory sequence motifs

Abstract Background Discovery of functionally significant short, statistically overrepresented subsequence patterns (motifs) in a set of sequences is a challenging problem in bioinformatics. Oftentimes, not all sequences in the set contain a motif. These non-motif-containing sequences complicate the algorithmic discovery of motifs. Filtering the non-motif-containing sequences from the larger set of sequences while simultaneously determining the identity of the motif is, therefore, desirable and a non-trivial problem in motif discovery research. Results We describe MotifCatcher, a framework that extends the sensitivity of existing motif-finding tools by employing random sampling to effectively remove non-motif-containing sequences from the motif search. We developed two implementations of our algorithm; each built around a commonly used motif-finding tool, and applied our algorithm to three diverse chromatin immunoprecipitation (ChIP) data sets. In each case, the motif finder with the MotifCatcher extension demonstrated improved sensitivity over the motif finder alone. Our approach organizes candidate functionally significant discovered motifs into a tree, which allowed us to make additional insights. In all cases, we were able to support our findings with experimental work from the literature. Conclusions Our framework demonstrates that additional processing at the sequence entry level can significantly improve the performance of existing motif-finding tools. For each biological data set tested, we were able to propose novel biological hypotheses supported by experimental work from the literature. Specifically, in Escherichia coli, we suggested binding site motifs for 6 non-traditional LexA protein binding sites; in Saccharomyces cerevisiae, we hypothesize 2 disparate mechanisms for novel binding sites of the Cse4p protein; and in Halobacterium sp. NRC-1, we discoverd subtle differences in a general transcription factor (GTF) binding site motif across several data sets. We suggest that small differences in our discovered motif could confer specificity for one or more homologous GTF proteins. We offer a free implementation of the MotifCatcher software package at http://www.bme.ucdavis.edu/facciotti/resources_data/software/ .http://deepblue.lib.umich.edu/bitstream/2027.42/112965/1/12859_2012_Article_5570.pd

Limits on the Peculiar Velocities of Two Distant Clusters Using the Kinematic Sunyaev-Zel'dovich Effect

We report millimeter-wavelength observations of the Sunyaev-Zel'dovich (S-Z) effect in two distant galaxy clusters. A relativistically correct analysis of the S-Z data is combined with the results of X-ray observations to determine the radial peculiar velocities v_r of the clusters. We observed Abell 2163 (z=.201) in three mm-wavelength bands centered at 2.1, 1.4, and 1.1 mm. We report a significant detection of the thermal component of the S-Z effect seen as both a decrement in the brightness of the CMB at 2.1 mm, and as an increment at 1.1 mm. Including uncertainties due to the calibration of the instrument, distribution and temperature of the IC gas, and astrophysical confusion, a simultaneous fit to the data in all three bands gives v_r=+490 +1370/-880 km/s at 68% confidence. We observed Abell 1689 (z=.181) in the 2.1 and 1.4 mm bands. Including the same detailed accounting of uncertainty, a simultaneous fit to the data in both bands gives v_r=+170 +815/-630 km/s. The limits on the peculiar velocities of A2163 and A1689 correspond to deviations from the uniform Hubble flow of <= 2-3%.Comment: 21 pages, 13 postscript figures, LaTeX(aaspptwo.sty), ApJ(in press

Toward a sustainable and resilient future

This chapter focuses on the implications of changing climate extremes for development, and considers how disaster risk management and climate change adaptation together can contribute to a sustainable and resilient future. Changes in the frequency, timing, magnitude, and characteristics of extreme events pose challenges to the goals of reducing disaster risk and vulnerability, both in the present and in the future. Enhancing the capacity of social-ecological systems to cope with, adapt to, and shape change is central to building sustainable and resilient development pathways in the face of climate change. The concept for social-ecological systems recognizes the interdependence of social and ecological factors in the generation and management of risk, as well as in the pursuit of sustainable development. Despite 20 years on the policy agenda, sustainable development remains contested and elusive. However, within the context of climate change, it is becoming increasingly clear that the sustainability of humans on the Earth is closely linked to resilient social-ecological systems, which is influenced by social institutions, human agency, and human capabilities

Shape-based peak identification for ChIP-Seq

We present a new algorithm for the identification of bound regions from ChIP-seq experiments. Our method for identifying statistically significant peaks from read coverage is inspired by the notion of persistence in topological data analysis and provides a non-parametric approach that is robust to noise in experiments. Specifically, our method reduces the peak calling problem to the study of tree-based statistics derived from the data. We demonstrate the accuracy of our method on existing datasets, and we show that it can discover previously missed regions and can more clearly discriminate between multiple binding events. The software T-PIC (Tree shape Peak Identification for ChIP-Seq) is available at http://math.berkeley.edu/~vhower/tpic.htmlComment: 12 pages, 6 figure

The Sunyaev-Zel'dovich Infrared Experiment: A Millimeter-wave Receiver for Cluster Cosmology

Measurements of the Sunyaev-Zel'dovich (S-Z) effect towards distant clusters of galaxies can be used to determine the Hubble constant and the radial component of cluster peculiar velocities. Determination of the cluster peculiar velocity requires the separation of the two components of the S-Z effect, which are due to the thermal and bulk velocities of the intracluster plasma. The two components can be separated practically only at millimeter (mm) wavelengths. Measurements of the S-Z effect at mm wavelengths are subject to minimal astrophysical confusion and, therefore, provide an important test of results obtained at longer wavelengths. We describe the instrument used to make the first significant detections of the S-Z effect at millimeter wavelengths. This instrument employs new filter, detector, and readout technologies to produce sensitive measurements of differential sky brightness stable on long time scales. These advances allow drift scan observations which achieve high sensitivity while minimizing common sources of systematic error.Comment: 19 pages, 15 postscript figures, LaTeX(aaspptwo.sty), ApJ(in press

Microscale sulfur cycling in the phototrophic pink berry consortia of the Sippewissett Salt Marsh

Microbial metabolism is the engine that drives global biogeochemical cycles, yet many key transformations are carried out by microbial consortia over short spatiotemporal scales that elude detection by traditional analytical approaches. We investigate syntrophic sulfur cycling in the ‘pink berry’ consortia of the Sippewissett Salt Marsh through an integrative study at the microbial scale. The pink berries are macroscopic, photosynthetic microbial aggregates composed primarily of two closely associated species: sulfide-oxidizing purple sulfur bacteria (PB-PSB1) and sulfate-reducing bacteria (PB-SRB1). Using metagenomic sequencing and 34S-enriched sulfate stable isotope probing coupled with nanoSIMS, we demonstrate interspecies transfer of reduced sulfur metabolites from PB-SRB1 to PB-PSB1. The pink berries catalyse net sulfide oxidation and maintain internal sulfide concentrations of 0–500 μm. Sulfide within the berries, captured on silver wires and analysed using secondary ion mass spectrometer, increased in abundance towards the berry interior, while δ34S-sulfide decreased from 6‰ to −31‰ from the exterior to interior of the berry. These values correspond to sulfate–sulfide isotopic fractionations (15–53‰) consistent with either sulfate reduction or a mixture of reductive and oxidative metabolisms. Together this combined metagenomic and high-resolution isotopic analysis demonstrates active sulfur cycling at the microscale within well-structured macroscopic consortia consisting of sulfide-oxidizing anoxygenic phototrophs and sulfate-reducing bacteria

TEF, Vol. 1 No. 1

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