Simple Runs-Bounded FM-Index Designs Are Fast

Given a string X of length n on alphabet ?, the FM-index data structure allows counting all occurrences of a pattern P of length m in O(m) time via an algorithm called backward search. An important difficulty when searching with an FM-index is to support queries on L, the Burrows-Wheeler transform of X, while L is in compressed form. This problem has been the subject of intense research for 25 years now. Run-length encoding of L is an effective way to reduce index size, in particular when the data being indexed is highly-repetitive, which is the case in many types of modern data, including those arising from versioned document collections and in pangenomics. This paper takes a back-to-basics look at supporting backward search in FM-indexes, exploring and engineering two simple designs. The first divides the BWT string into blocks containing b symbols each and then run-length compresses each block separately, possibly introducing new runs (compared to applying run-length encoding once, to the whole string). Each block stores counts of each symbol that occurs before the block. This method supports the operation rank_c(L, i) (i.e., count the number of times c occurs in the prefix L[1..i]) by first determining the block i/b in which i falls and scanning the block to the appropriate position counting occurrences of c along the way. This partial answer to rank_c(L, i) is then added to the stored count of c symbols before the block to determine the final answer. Our second design has a similar structure, but instead divides the run-length-encoded version of L into blocks containing an equal number of runs. The trick then is to determine the block in which a query falls, which is achieved via a predecessor query over the block starting positions. We show via extensive experiments on a wide range of repetitive text collections that these FM-indexes are not only easy to implement, but also fast and space efficient in practice

Natural quantitative genetic variance in plant growth differs in response to ecologically relevant temperature heterogeneity

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Xilinxin 7-sarjan FPGA-piirien muistiresurssit ja niiden käyttö suunnittelussa

Tiivistelmä. Työssä tutkittiin Xilinxin 7-sarjan FPGA-piirien muistiresursseja ja niiden käyttöä suunnittelussa. Työssä kuvattiin FPGA-piirien perusteet ja niiden käyttökohteet. Ennen Xilinxin muistitekniikoita käytiin läpi tavallisimpien muistien perusperiaatteet ja muistit, jotka olivat käytännöllisimpiä FPGA-piirin kannalta. Sitten tutkittiin kuinka Xilinxin hajautetut ja lohko-RAM-teknologiat toimivat ja kuinka niitä käytetään suunnittelussa Xilinxin toteutuskoodilla sekä RTL-koodilla. Lopuksi tutkittiin Xilinxin 7-sarjan FPGA-piirien muistiresursseja laitetasolla. Työ tehtiin kirjallisuuskatsauksena.Xilinx 7-series FPGAs’ memory resources and their use in design. Abstract. The subject of this bachelor’s thesis was to research Xilinx 7-series FPGAs’ memory resources and their uses in design. FPGAs’ basics and uses were described. The basics of most practical memories were reviewed followed by Xilinx’s 7-series FPGAs’ memory technologies distributed RAM and block RAM. Their basic principals and uses were researched and their uses in design in Xilinx instantiations and RTL code. Lastly 7-series FPGA’s memory resources were researched. The work was done as a literature review

Reciprocal Associations between Burnout and Depression : An 8-Year Longitudinal Study

The purpose of the present four-wave longitudinal study was to examine the differentiation and reciprocal associations between burnout and depression, and their associations with a series of correlates related to employees' physical and psychological health (sleep disturbances, somatic symptoms, self-rated subjective health, and life satisfaction). A total of 542 early career Finnish workers filled out questionnaires four times over a period of 8 years. First, our results supported the superiority of a bifactor exploratory structural equation modeling (bifactor-ESEM) representation of employees' burnout ratings, and the empirical differentiation between burnout and depression ratings over each measurement occasion. These results further revealed moderate cross-sectional associations between burnout and depression, supporting their inter-related character but also their empirical distinctiveness. Second, autoregressive cross-lagged analyses revealed that both constructs presented a moderate level of stability over time and reciprocal associations that generalized to all time intervals considered. Finally, relations between depression and all correlates measures during the last wave of the study were in the expected direction, whereas burnout was found to be more weakly related to only a subset of these correlates. Taken together, these results thus support the distinctiveness of burnout and depression, and the presence of mutually reinforcing relations between them.Peer reviewe

Disentangled long-read de Bruijn graphs via optical maps

Peer reviewe

Succinct dynamic de Bruijn graphs

Motivation: The de Bruijn graph is one of the fundamental data structures for analysis of high throughput sequencing data. In order to be applicable to population-scale studies, it is essential to build and store the graph in a space- and time-efficient manner. In addition, due to the ever-changing nature of population studies, it has become essential to update the graph after construction, e.g. add and remove nodes and edges. Although there has been substantial effort on making the construction and storage of the graph efficient, there is a limited amount of work in building the graph in an efficient and mutable manner. Hence, most space efficient data structures require complete reconstruction of the graph in order to add or remove edges or nodes. Results: In this article, we present DynamicBOSS, a succinct representation of the de Bruijn graph that allows for an unlimited number of additions and deletions of nodes and edges. We compare our method with other competing methods and demonstrate that DynamicBOSS is the only method that supports both addition and deletion and is applicable to very large samples (e.g. greater than 15 billion k-mers). Competing dynamic methods, e.g. FDBG cannot be constructed on large scale datasets, or cannot support both addition and deletion, e.g. BiFrost.Peer reviewe

Longitudinal Trajectories, Social and Individual Antecedents, and Outcomes of Problematic Internet Use Among Late Adolescents

Given the detrimental effects associated with problematic internet use (PIU) and the need to better understand its nature and evolution, the present study examined the development of PIU in a sample of 1,750 adolescents (aged 16–19) from Finland over a 3‐year period. We documented the social (loneliness, perceived maternal and paternal behaviors) and individual (sex) antecedents, as well as the outcome implications (depressive symptoms, substance use, academic achievement) of PIU trajectories. Outcomes also predicted PIU trajectories. Latent curve modeling revealed an initially moderate, and subsequently decreasing trajectory of PIU. PIU was predicted by loneliness, paternal neglect, maternal care, depressive symptoms, and being male. In turn, PIU trajectories predicted increases in depressive symptoms and substance use, but decreases in academic achievement.Given the detrimental effects associated with problematic internet use (PIU) and the need to better understand its nature and evolution, the present study examined the development of PIU in a sample of 1,750 adolescents (aged 16-19) from Finland over a 3-year period. We documented the social (loneliness, perceived maternal and paternal behaviors) and individual (sex) antecedents, as well as the outcome implications (depressive symptoms, substance use, academic achievement) of PIU trajectories. Outcomes also predicted PIU trajectories. Latent curve modeling revealed an initially moderate, and subsequently decreasing trajectory of PIU. PIU was predicted by loneliness, paternal neglect, maternal care, depressive symptoms, and being male. In turn, PIU trajectories predicted increases in depressive symptoms and substance use, but decreases in academic achievement.Peer reviewe