Alignment-free Genomic Analysis via a Big Data Spark Platform

Motivation: Alignment-free distance and similarity functions (AF functions, for short) are a well established alternative to two and multiple sequence alignments for many genomic, metagenomic and epigenomic tasks. Due to data-intensive applications, the computation of AF functions is a Big Data problem, with the recent Literature indicating that the development of fast and scalable algorithms computing AF functions is a high-priority task. Somewhat surprisingly, despite the increasing popularity of Big Data technologies in Computational Biology, the development of a Big Data platform for those tasks has not been pursued, possibly due to its complexity. Results: We fill this important gap by introducing FADE, the first extensible, efficient and scalable Spark platform for Alignment-free genomic analysis. It supports natively eighteen of the best performing AF functions coming out of a recent hallmark benchmarking study. FADE development and potential impact comprises novel aspects of interest. Namely, (a) a considerable effort of distributed algorithms, the most tangible result being a much faster execution time of reference methods like MASH and FSWM; (b) a software design that makes FADE user-friendly and easily extendable by Spark non-specialists; (c) its ability to support data- and compute-intensive tasks. About this, we provide a novel and much needed analysis of how informative and robust AF functions are, in terms of the statistical significance of their output. Our findings naturally extend the ones of the highly regarded benchmarking study, since the functions that can really be used are reduced to a handful of the eighteen included in FADE

A vanishing theorem

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Preliminaries

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Complementary distributions and Pontrjagin classes

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222Rn daughters influence on scaler mode of the ARGO-YBJ detector

The ARGO-YBJ experiment is a full coverage air shower array; its lowest energy threshold is reached using the "scaler mode technique". Working in this mode, the signals generated by any particle hitting each cluster are put in coincidence every 150 ns and read by four independent scaler channels, giving the counting rates of multiplicity \geq1, \geq2, \geq3 and \geq4 (C1, C2, C3 and C4, respectively). The study of these counting rates pointed out a different behaviour of C1 respect to C2, C3 and C4, suggesting that C1 is detecting not only cosmic rays. This work shows that the radon (222Rn) gamma emitter daughters present in the ARGO-YBJ building air are contributing to C1 counts at the level of 1 Hz each Bq/m3 of radon. The uncertainty about this contribution is great, because of the high variability of 222Rn concentration and the building ventilation. The radon monitoring will allow the C1 correction improving the sensitivity of the ARGO-YBJ experiment at its lowest energy threshold.Comment: 4 pages, 3 figures, Proceedings of the 32nd International Cosmic Ray Conference (ICRC

Using Hypervideo to support undergraduate students' reflection on work practices: a qualitative study

Abstract According to several exploratory studies, the HyperVideo seems to be particularly useful in highlighting the existing connections between the school-based and the work-based contexts, between authentic work situations and theoretical underpinnings. This tool and its features, in particular, the video annotation, seems to constitute an instrument which facilitates the students' reflection on work-practices. Even though several researchers have already studied the efficacy of HyperVideo, studies concerning the qualitative differences between a reflection process activated with or without its use are still missing. Therefore, the present contribution is focused on the reflective processes activated by two groups of students engaged in a higher education course while they carry out a reflective activity on work practices using the HyperVideo or not. The aim is to investigate wether the HyperVideo can be useful for students to foster the connection between theoretical concepts and work practices. Through multi-step qualitative analysis which combined Thematic Qualitative Text Analysis and Grounded Theory, a sample of reflective reports drafted by a group of students who employed HiperVideo to make a video-interview on a work-practice and to reflect on it (Group A) was compared with a sample of reflective reports drafted by a group who did not use it to complete the same task (Group B). The results emerging from the comparison of the coding frequencies between the two groups show that HyperVideo can support the reflective processes of students, better connecting theory and professional practice

FASTA/Q data compressors for MapReduce-Hadoop genomics: space and time savings made easy

Background Storage of genomic data is a major cost for the Life Sciences, effectively addressed via specialized data compression methods. For the same reasons of abundance in data production, the use of Big Data technologies is seen as the future for genomic data storage and processing, with MapReduce-Hadoop as leaders. Somewhat surprisingly, none of the specialized FASTA/Q compressors is available within Hadoop. Indeed, their deployment there is not exactly immediate. Such a State of the Art is problematic. Results We provide major advances in two different directions. Methodologically, we propose two general methods, with the corresponding software, that make very easy to deploy a specialized FASTA/Q compressor within MapReduce-Hadoop for processing files stored on the distributed Hadoop File System, with very little knowledge of Hadoop. Practically, we provide evidence that the deployment of those specialized compressors within Hadoop, not available so far, results in better space savings, and even in better execution times over compressed data, with respect to the use of generic compressors available in Hadoop, in particular for FASTQ files. Finally, we observe that these results hold also for the Apache Spark framework, when used to process FASTA/Q files stored on the Hadoop File System. Conclusions Our Methods and the corresponding software substantially contribute to achieve space and time savings for the storage and processing of FASTA/Q files in Hadoop and Spark. Being our approach general, it is very likely that it can be applied also to FASTA/Q compression methods that will appear in the future

Effect of inborn pancreatic islet deficit in the Munich Wister Frömter rat

The total mass of pancreatic islet cells is a critical factor in glucose metabolic control. The aim of the present study was to investigate whether in the Munich Wistar Frömter (MWF) rat, beside a reduction in the number of nephrons, there are also alterations in the number of pancreatic islets and of β cell mass. We also examined glucose metabolism, both in normal conditions and following intravenous glucose injection. The number of islets per pancreas, estimated by morphometrical analysis, was significantly lower in MWF rats than in Wistar rats (3,501±1,285 vs. 7,259±2,330 islet/rat, respectively). Also the mean number of islets per gram of body weight was significantly lower in MWF rats than in Wistar rats (18±7 in MWF rats vs. 28±10 islets/g bw in Wistar rats). Morphometric analysis of β cell mass showed an average of 77.1±7% islet cells staining for insulin in MWF rats and 83.9±2.1% in the control Wistar rats. Despite the lower number of islets and β cells, MWF and Wistar rats had comparable fasting blood glucose levels but significant differences in blood glucose following an intraperitoneal glucose tolerance test. In summary, pancreatic islets of MWF and Wistar rats showed a marked difference in morphometrical characteristics. While this difference is not associated with blood glucose levels, glucose metabolism after IPGTT between MWF and Wistar rats is significantly different. These data suggest that an inborn deficit in β cell mass of about 60% is responsible for altered glucose metabolism and could favor the development of diabetes