Tandem mass spectrometry data quality assessment by self-convolution

<p>Abstract</p> <p>Background</p> <p>Many algorithms have been developed for deciphering the tandem mass spectrometry (MS) data sets. They can be essentially clustered into two classes. The first performs searches on theoretical mass spectrum database, while the second based itself on <it>de novo </it>sequencing from raw mass spectrometry data. It was noted that the quality of mass spectra affects significantly the protein identification processes in both instances. This prompted the authors to explore ways to measure the quality of MS data sets before subjecting them to the protein identification algorithms, thus allowing for more meaningful searches and increased confidence level of proteins identified.</p> <p>Results</p> <p>The proposed method measures the qualities of MS data sets based on the symmetric property of b- and y-ion peaks present in a MS spectrum. Self-convolution on MS data and its time-reversal copy was employed. Due to the symmetric nature of b-ions and y-ions peaks, the self-convolution result of a good spectrum would produce a highest mid point intensity peak. To reduce processing time, self-convolution was achieved using Fast Fourier Transform and its inverse transform, followed by the removal of the "DC" (Direct Current) component and the normalisation of the data set. The quality score was defined as the ratio of the intensity at the mid point to the remaining peaks of the convolution result. The method was validated using both theoretical mass spectra, with various permutations, and several real MS data sets. The results were encouraging, revealing a high percentage of positive prediction rates for spectra with good quality scores.</p> <p>Conclusion</p> <p>We have demonstrated in this work a method for determining the quality of tandem MS data set. By pre-determining the quality of tandem MS data before subjecting them to protein identification algorithms, spurious protein predictions due to poor tandem MS data are avoided, giving scientists greater confidence in the predicted results. We conclude that the algorithm performs well and could potentially be used as a pre-processing for all mass spectrometry based protein identification tools.</p

A proteomics approach to decipher the molecular nature of planarian stem cells

Background In recent years, planaria have emerged as an important model system for research into stem cells and regeneration. Attention is focused on their unique stem cells, the neoblasts, which can differentiate into any cell type present in the adult organism. Sequencing of the Schmidtea mediterranea genome and some expressed sequence tag projects have generated extensive data on the genetic profile of these cells. However, little information is available on their protein dynamics. Results We developed a proteomic strategy to identify neoblast-specific proteins. Here we describe the method and discuss the results in comparison to the genomic high-throughput analyses carried out in planaria and to proteomic studies using other stem cell systems. We also show functional data for some of the candidate genes selected in our proteomic approach. Conclusions We have developed an accurate and reliable mass-spectra-based proteomics approach to complement previous genomic studies and to further achieve a more accurate understanding and description of the molecular and cellular processes related to the neoblasts

Low-mass and sub-stellar eclipsing binaries in stellar clusters

We highlight the importance of eclipsing double-line binaries in our understanding on star formation and evolution. We review the recent discoveries of low-mass and sub-stellar eclipsing binaries belonging to star-forming regions, open clusters, and globular clusters identified by ground-based surveys and space missions with high-resolution spectroscopic follow-up. These discoveries provide benchmark systems with known distances, metallicities, and ages to calibrate masses and radii predicted by state-of-the-art evolutionary models to a few percent. We report their density and discuss current limitations on the accuracy of the physical parameters. We discuss future opportunities and highlight future guidelines to fill gaps in age and metallicity to improve further our knowledge of low-mass stars and brown dwarfs.Comment: 30 pages, 5 figures, no table. Review pape

The California-Kepler Survey. V. Peas in a Pod: Planets in a Kepler Multi-planet System Are Similar in Size and Regularly Spaced

We have established precise planet radii, semimajor axes, incident stellar fluxes, and stellar masses for 909 planets in 355 multi-planet systems discovered by Kepler. In this sample, we find that planets within a single multi-planet system have correlated sizes: each planet is more likely to be the size of its neighbor than a size drawn at random from the distribution of observed planet sizes. In systems with three or more planets, the planets tend to have a regular spacing: the orbital period ratios of adjacent pairs of planets are correlated. Furthermore, the orbital period ratios are smaller in systems with smaller planets, suggesting that the patterns in planet sizes and spacing are linked through formation and/or subsequent orbital dynamics. Yet, we find that essentially no planets have orbital period ratios smaller than 1.2, regardless of planet size. Using empirical mass-radius relationships, we estimate the mutual Hill separations of planet pairs. We find that 93% of the planet pairs are at least 10 mutual Hill radii apart, and that a spacing of ∼20 mutual Hill radii is most common. We also find that when comparing planet sizes, the outer planet is larger in 65% ± 0.4% of cases, and the typical ratio of the outer to inner planet size is positively correlated with the temperature difference between the planets. This could be the result of photo-evaporation

The California-Kepler Survey. III. A Gap in the Radius Distribution of Small Planets

The size of a planet is an observable property directly connected to the physics of its formation and evolution. We used precise radius measurements from the California-Kepler Survey to study the size distribution of 2025 Kepler planets in fine detail. We detect a factor of ≥2 deficit in the occurrence rate distribution at 1.5-2.0 R⊕. This gap splits the population of close-in (P &lt; 100 days) small planets into two size regimes: Rp &lt; 1.5⊕ and RP = 2.0-3.0R⊕, with few planets in between. Planets in these two regimes have nearly the same intrinsic frequency based on occurrence measurements that account for planet detection efficiencies. The paucity of planets between 1.5 and 2.0 R⊕ supports the emerging picture that close-in planets smaller than Neptune are composed of rocky cores measuring 1.5 R⊕ or smaller with varying amounts of low-density gas that determine their total sizes

The California-Kepler Survey. II. Precise Physical Properties of 2025 Kepler Planets and Their Host Stars

We present stellar and planetary properties for 1305 Kepler Objects of Interest hosting 2025 planet candidates observed as part of the California-Kepler Survey. We combine spectroscopic constraints, presented in Paper I, with stellar interior modeling to estimate stellar masses, radii, and ages. Stellar radii are typically constrained to 11%, compared to 40% when only photometric constraints are used. Stellar masses are constrained to 4%, and ages are constrained to 30%. We verify the integrity of the stellar parameters through comparisons with asteroseismic studies and Gaia parallaxes. We also recompute planetary radii for 2025 planet candidates. Because knowledge of planetary radii is often limited by uncertainties in stellar size, we improve the uncertainties in planet radii from typically 42% to 12%. We also leverage improved knowledge of stellar effective temperature to recompute incident stellar fluxes for the planets, now precise to 21%, compared to a factor of two when derived from photometry

The California-Kepler Survey. I. High-resolution Spectroscopy of 1305 Stars Hosting Kepler Transiting Planets

The California-Kepler Survey (CKS) is an observational program developed to improve our knowledge of the properties of stars found to host transiting planets by NASA's Kepler Mission. The improvement stems from new high-resolution optical spectra obtained using HIRES at the W. M. Keck Observatory. The CKS stellar sample comprises 1305 stars classified as Kepler objects of interest, hosting a total of 2075 transiting planets. The primary sample is magnitude-limited (Kp &lt; 14.2) and contains 960 stars with 1385 planets. The sample was extended to include some fainter stars that host multiple planets, ultra-short period planets, or habitable zone planets. The spectroscopic parameters were determined with two different codes, one based on template matching and the other on direct spectral synthesis using radiative transfer. We demonstrate a precision of 60 K in Teff, 0.10 dex in log g, 0.04 dex in [Fe/H], and 1.0km s-1 in V sin i. In this paper, we describe the CKS project and present a uniform catalog of spectroscopic parameters. Subsequent papers in this series present catalogs of derived stellar properties such as mass, radius, and age; revised planet properties; and statistical explorations of the ensemble. CKS is the largest survey to determine the properties of Kepler stars using a uniform set of high-resolution, high signal-to-noise ratio spectra. The HIRES spectra are available to the community for independent analyses