| 11. |
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| 12. |
- Ali, Raja Hashim, et al.
(författare)
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A graph-based approach for improving the homologyinference in multiple sequence alignments
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Multiple sequence alignment (MSA) is ubiquitous in evolutionary studies and other areas ofbioinformatics. In nearly all cases MSAs are taken to be a known and xed quantity on which toperform downstream analysis despite extensive evidence that MSA accuracy and uncertainty aectsresults. Mistakes in the MSA are known to cause a wide range of problems for downstream evolutionaryinference, ranging from false inference of positive selection to long branch attraction artifacts. The mostpopular approach to dealing with this problem is to remove (lter) specic columns in the MSA thatare thought to be prone to error, either through proximity to gaps or through some scoring function.Although popular, this approach has had mixed success and several studies have even suggested thatltering might be detrimental to phylogenetic studies. Here we present a dierent approach to dealingwith MSA accuracy and uncertainty through a graph-based approach implemented in the freely availablesoftware Divvier. The aim of Divvier is to identify clusters of characters that have strong statisticalevidence of shared homology, based on the output of a pair hidden Markov model. These clusters canthen be used to either lter characters out the MSA, through a process we call partial ltering, or torepresent each of the clusters in a new column, through a process we call divvying up. We validateour approach through its performance on real and simulated benchmarks, nding Divvier substantiallyoutperforms all other ltering software for treating MSAs by retaining more true positive homology callsand removing more false positive homology calls. We also nd that Divvier, in contrast to other lteringtools, can alleviate long branch attraction artifacts induced by MSA and reduces the variation in treeestimates caused by MSA uncertainty.
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| 13. |
- Ali, Raja Hashim, et al.
(författare)
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Identifying Clusters of High Confidence Homologies in Multiple Sequence Alignments
- 2019
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Ingår i: Molecular biology and evolution. - : OXFORD UNIV PRESS. - 0737-4038 .- 1537-1719. ; 36:10, s. 2340-2351
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Tidskriftsartikel (refereegranskat)abstract
- Multiple sequence alignment (MSA) is ubiquitous in evolution and bioinformatics. MSAs are usually taken to be a known and fixed quantity on which to perform downstream analysis despite extensive evidence that MSA accuracy and uncertainty affect results. These errors are known to cause a wide range of problems for downstream evolutionary inference, ranging from false inference of positive selection to long branch attraction artifacts. The most popular approach to dealing with this problem is to remove (filter) specific columns in the MSA that are thought to be prone to error. Although popular, this approach has had mixed success and several studies have even suggested that filtering might be detrimental to phylogenetic studies. We present a graph-based clustering method to address MSA uncertainty and error in the software Divvier (available at https://github.com/simonwhelan/Divvier), which uses a probabilistic model to identify clusters of characters that have strong statistical evidence of shared homology. These clusters can then be used to either filter characters from the MSA (partial filtering) or represent each of the clusters in a new column (divvying). We validate Divvier through its performance on real and simulated benchmarks, finding Divvier substantially outperforms existing filtering software by retaining more true pairwise homologies calls and removing more false positive pairwise homologies. We also find that Divvier, in contrast to other filtering tools, can alleviate long branch attraction artifacts induced by MSA and reduces the variation in tree estimates caused by MSA uncertainty.
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| 14. |
- Allen, James E., et al.
(författare)
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Assessing the State of Substitution Models Describing Noncoding RNA Evolution
- 2014
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Ingår i: Genome Biology and Evolution. - : Oxford University Press (OUP). - 1759-6653. ; 6:1, s. 65-75
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Tidskriftsartikel (refereegranskat)abstract
- Phylogenetic inference is widely used to investigate the relationships between homologous sequences. RNA molecules have played a key role in these studies because they are present throughout life and tend to evolve slowly. Phylogenetic inference has been shown to be dependent on the substitution model used. A wide range of models have been developed to describe RNA evolution, either with 16 states describing all possible canonical base pairs or with 7 states where the 10 mismatched nucleotides are reduced to a single state. Formal model selection has become a standard practice for choosing an inferential model and works well for comparing models of a specific type, such as comparisons within nucleotide models or within amino acid models. Model selection cannot function across different sized state spaces because the likelihoods are conditioned on different data. Here, we introduce statistical state-space projection methods that allow the direct comparison of likelihoods between nucleotide models and 7-state and 16-state RNA models. To demonstrate the general applicability of our new methods, we extract 287 RNA families from genomic alignments and perform model selection. We find that in 281/287 families, RNA models are selected in preference to nucleotide models, with simple 7-state RNA models selected for more conserved families with shorter stems and more complex 16-state RNA models selected for more divergent families with longer stems. Other factors, such as the function of the RNA molecule or the GC-content, have limited impact on model selection. Our models and model selection methods are freely available in the open-source software.
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| 15. |
- Backes, Claudia, et al.
(författare)
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Production and processing of graphene and related materials
- 2020
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Ingår i: 2D Materials. - : IOP Publishing. - 2053-1583. ; 7:2
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Tidskriftsartikel (refereegranskat)abstract
- We present an overview of the main techniques for production and processing of graphene and related materials (GRMs), as well as the key characterization procedures. We adopt a 'hands-on' approach, providing practical details and procedures as derived from literature as well as from the authors' experience, in order to enable the reader to reproduce the results. Section I is devoted to 'bottom up' approaches, whereby individual constituents are pieced together into more complex structures. We consider graphene nanoribbons (GNRs) produced either by solution processing or by on-surface synthesis in ultra high vacuum (UHV), as well carbon nanomembranes (CNM). Production of a variety of GNRs with tailored band gaps and edge shapes is now possible. CNMs can be tuned in terms of porosity, crystallinity and electronic behaviour. Section II covers 'top down' techniques. These rely on breaking down of a layered precursor, in the graphene case usually natural crystals like graphite or artificially synthesized materials, such as highly oriented pyrolythic graphite, monolayers or few layers (FL) flakes. The main focus of this section is on various exfoliation techniques in a liquid media, either intercalation or liquid phase exfoliation (LPE). The choice of precursor, exfoliation method, medium as well as the control of parameters such as time or temperature are crucial. A definite choice of parameters and conditions yields a particular material with specific properties that makes it more suitable for a targeted application. We cover protocols for the graphitic precursors to graphene oxide (GO). This is an important material for a range of applications in biomedicine, energy storage, nanocomposites, etc. Hummers' and modified Hummers' methods are used to make GO that subsequently can be reduced to obtain reduced graphene oxide (RGO) with a variety of strategies. GO flakes are also employed to prepare three-dimensional (3d) low density structures, such as sponges, foams, hydro- or aerogels. The assembly of flakes into 3d structures can provide improved mechanical properties. Aerogels with a highly open structure, with interconnected hierarchical pores, can enhance the accessibility to the whole surface area, as relevant for a number of applications, such as energy storage. The main recipes to yield graphite intercalation compounds (GICs) are also discussed. GICs are suitable precursors for covalent functionalization of graphene, but can also be used for the synthesis of uncharged graphene in solution. Degradation of the molecules intercalated in GICs can be triggered by high temperature treatment or microwave irradiation, creating a gas pressure surge in graphite and exfoliation. Electrochemical exfoliation by applying a voltage in an electrolyte to a graphite electrode can be tuned by varying precursors, electrolytes and potential. Graphite electrodes can be either negatively or positively intercalated to obtain GICs that are subsequently exfoliated. We also discuss the materials that can be amenable to exfoliation, by employing a theoretical data-mining approach. The exfoliation of LMs usually results in a heterogeneous dispersion of flakes with different lateral size and thickness. This is a critical bottleneck for applications, and hinders the full exploitation of GRMs produced by solution processing. The establishment of procedures to control the morphological properties of exfoliated GRMs, which also need to be industrially scalable, is one of the key needs. Section III deals with the processing of flakes. (Ultra)centrifugation techniques have thus far been the most investigated to sort GRMs following ultrasonication, shear mixing, ball milling, microfluidization, and wet-jet milling. It allows sorting by size and thickness. Inks formulated from GRM dispersions can be printed using a number of processes, from inkjet to screen printing. Each technique has specific rheological requirements, as well as geometrical constraints. The solvent choice is critical, not only for the GRM stability, but also in terms of optimizing printing on different substrates, such as glass, Si, plastic, paper, etc, all with different surface energies. Chemical modifications of such substrates is also a key step. Sections IV-VII are devoted to the growth of GRMs on various substrates and their processing after growth to place them on the surface of choice for specific applications. The substrate for graphene growth is a key determinant of the nature and quality of the resultant film. The lattice mismatch between graphene and substrate influences the resulting crystallinity. Growth on insulators, such as SiO2, typically results in films with small crystallites, whereas growth on the close-packed surfaces of metals yields highly crystalline films. Section IV outlines the growth of graphene on SiC substrates. This satisfies the requirements for electronic applications, with well-defined graphene-substrate interface, low trapped impurities and no need for transfer. It also allows graphene structures and devices to be measured directly on the growth substrate. The flatness of the substrate results in graphene with minimal strain and ripples on large areas, allowing spectroscopies and surface science to be performed. We also discuss the surface engineering by intercalation of the resulting graphene, its integration with Si-wafers and the production of nanostructures with the desired shape, with no need for patterning. Section V deals with chemical vapour deposition (CVD) onto various transition metals and on insulators. Growth on Ni results in graphitized polycrystalline films. While the thickness of these films can be optimized by controlling the deposition parameters, such as the type of hydrocarbon precursor and temperature, it is difficult to attain single layer graphene (SLG) across large areas, owing to the simultaneous nucleation/growth and solution/precipitation mechanisms. The differing characteristics of polycrystalline Ni films facilitate the growth of graphitic layers at different rates, resulting in regions with differing numbers of graphitic layers. High-quality films can be grown on Cu. Cu is available in a variety of shapes and forms, such as foils, bulks, foams, thin films on other materials and powders, making it attractive for industrial production of large area graphene films. The push to use CVD graphene in applications has also triggered a research line for the direct growth on insulators. The quality of the resulting films is lower than possible to date on metals, but enough, in terms of transmittance and resistivity, for many applications as described in section V. Transfer technologies are the focus of section VI. CVD synthesis of graphene on metals and bottom up molecular approaches require SLG to be transferred to the final target substrates. To have technological impact, the advances in production of high-quality large-area CVD graphene must be commensurate with those on transfer and placement on the final substrates. This is a prerequisite for most applications, such as touch panels, anticorrosion coatings, transparent electrodes and gas sensors etc. New strategies have improved the transferred graphene quality, making CVD graphene a feasible option for CMOS foundries. Methods based on complete etching of the metal substrate in suitable etchants, typically iron chloride, ammonium persulfate, or hydrogen chloride although reliable, are time- and resource-consuming, with damage to graphene and production of metal and etchant residues. Electrochemical delamination in a low-concentration aqueous solution is an alternative. In this case metallic substrates can be reused. Dry transfer is less detrimental for the SLG quality, enabling a deterministic transfer. There is a large range of layered materials (LMs) beyond graphite. Only few of them have been already exfoliated and fully characterized. Section VII deals with the growth of some of these materials. Amongst them, h-BN, transition metal tri- and di-chalcogenides are of paramount importance. The growth of h-BN is at present considered essential for the development of graphene in (opto) electronic applications, as h-BN is ideal as capping layer or substrate. The interesting optical and electronic properties of TMDs also require the development of scalable methods for their production. Large scale growth using chemical/physical vapour deposition or thermal assisted conversion has been thus far limited to a small set, such as h-BN or some TMDs. Heterostructures could also be directly grown. Section VIII discusses advances in GRM functionalization. A broad range of organic molecules can be anchored to the sp(2) basal plane by reductive functionalization. Negatively charged graphene can be prepared in liquid phase (e.g. via intercalation chemistry or electrochemically) and can react with electrophiles. This can be achieved both in dispersion or on substrate. The functional groups of GO can be further derivatized. Graphene can also be noncovalently functionalized, in particular with polycyclic aromatic hydrocarbons that assemble on the sp(2) carbon network by pi-pi stacking. In the liquid phase, this can enhance the colloidal stability of SLG/FLG. Approaches to achieve noncovalent on-substrate functionalization are also discussed, which can chemically dope graphene. Research efforts to derivatize CNMs are also summarized, as well as novel routes to selectively address defect sites. In dispersion, edges are the most dominant defects and can be covalently modified. This enhances colloidal stability without modifying the graphene basal plane. Basal plane point defects can also be modified, passivated and healed in ultra-high vacuum. The decoration of graphene with metal nanoparticles (NPs) has also received considerable attention, as it allows to exploit synergistic effects between NPs and graphene. Decoration can be either achieved chemically or in the gas phase. All LMs,
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| 16. |
- Birney, Ewan, et al.
(författare)
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Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project
- 2007
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 447:7146, s. 799-816
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Tidskriftsartikel (refereegranskat)abstract
- We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view of chromatin structure has emerged, including its inter-relationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded new mechanistic and evolutionary insights concerning the functional landscape of the human genome. Together, these studies are defining a path for pursuit of a more comprehensive characterization of human genome function.
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| 17. |
- Blanton, Michael R., et al.
(författare)
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Sloan Digital Sky Survey IV : Mapping the Milky Way, Nearby Galaxies, and the Distant Universe
- 2017
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Ingår i: Astronomical Journal. - : IOP Publishing Ltd. - 0004-6256 .- 1538-3881. ; 154:1
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Tidskriftsartikel (refereegranskat)abstract
- We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and. high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median z similar to 0.03). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between z similar to 0.6 and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs. and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the. Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July.
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| 18. |
- Bogusz, Marcin
(författare)
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Evolutionary Approaches to Sequence Alignment
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Molecular evolutionary biology allows us to look into the past by analyzing sequences of amino acids or nucleotides. These analyses can be very complex, often involving advanced statistical models of sequence evolution to construct phylogenetic trees, study the patterns of natural selection and perform a number of other evolutionary studies. In many cases, these evolutionary studies require a prerequisite of multiple sequence alignment (MSA) - a technique, which aims at grouping the characters that share a common ancestor, or homology, into columns. This information regarding shared homology is needed by statistical models to describe the process of substitutions in order to perform evolutionary inference. Sequence alignment, however, is difficult and MSAs often contain whole regions of wrongly aligned characters, which impact downstream analyses.In this thesis I use two broad groups of approaches to avoid errors in the alignment. The first group addresses the analysis methods without sequence alignment by explicitly modelling the processes of substitutions, and insertions and deletions (indels) between pairs of sequences using pair hidden Markov models. I describe an accurate tree inference method that uses a neighbor joining clustering approach to construct a tree from a matrix of model-based evolutionary distances.Next, I develop a pairwise method of modelling how natural selection acts on substitutions and indels. I further show the relationship between the constraints acting on these two evolutionary forces to show that natural selection affects them in a similar way.The second group of approaches deals with errors in existing alignments. I use a statistical model-based approach to evaluate the quality of multiple sequence alignments.First, I provide a graph-based tool for removing wrongly aligned pairs of residues by splitting them apart. This approach tends to produce better results when compared to standard column-based filtering.Second, I provide a way to compare MSAs using a probabilistic framework. I propose new ways of scoring of sequence alignments and show that popular methods produce similar results.The overall purpose of this work is to facilitate more accurate evolutionary analyses by addressing the problem of sequence alignment in a statistically rigorous manner.
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| 19. |
- Bogusz, Marcin, et al.
(författare)
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Examining sequence alignments using a model-based approach
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Multiple sequence alignment (MSA) is a commonly performed procedure required for a number of evolutionary and comparative analyses. The common two-step process of sequence alignment followed by statistical phylogenetic inference depends on MSA quality. MSA is computationally difficult and as a result in many cases sequence alignments contain regions of spurious homologies. These errors in the alignment affect downstream results, so choosing an accurate MSA is critical. Researchers often face the problem of choosing an aligner out of many multiple sequence alignment methods (MSAMs). This choice is often based on the results of benchmarks with various popular methods claiming high accuracy scores. These methods compete to obtain the highest scores in the commonly used sum-of-pairs benchmark—which accounts for a fraction of the true homologies recovered—ignoring the fraction of introduced false positive homologies. Furthermore, these benchmarks do not account for the fact that some homologies are more difficult to recover than the others. We take a probabilistic model-based approach to examine the quality of pairwise homologies returned by four popular MSAMs. We use pair-hidden Markov models to break down alignment columns into pairs and obtain distributions of pairwise posterior scores for these aligners. Basing our results on a structural benchmark and a simulation study, we find that MSAMs appear to return a sample from a confidence set defined by high posterior probabilities. Furthermore, we find that the reference alignment contains low pairwise posterior portions of pairwise homologies which cannot be expected to be recovered by any MSAM. Finally, we look at several possible test statistics, with and without the need for reference alignments, and ultimately suggest using positive predictive value (PPV) and mean posterior probability for MSA evaluation.
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| 20. |
- Bogusz, Marcin, et al.
(författare)
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Phylogenetic Tree Estimation With and Without Alignment : New Distance Methods and Benchmarking
- 2017
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Ingår i: Systematic Biology. - : Oxford University Press (OUP). - 1063-5157 .- 1076-836X. ; 66:2, s. 218-231
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Tidskriftsartikel (refereegranskat)abstract
- Phylogenetic tree inference is a critical component of many systematic and evolutionary studies. The majority of these studies are based on the two-step process of multiple sequence alignment followed by tree inference, despite persistent evidence that the alignment step can lead to biased results. Here we present a two-part study that first presents PaHMM-Tree, a novel neighbor joining-based method that estimates pairwise distances without assuming a single alignment. We then use simulations to benchmark its performance against a wide-range of other phylogenetic tree inference methods, including the first comparison of alignment-free distance-based methods against more conventional tree estimation methods. Our new method for calculating pairwise distances based on statistical alignment provides distance estimates that are as accurate as those obtained using standard methods based on the true alignment. Pairwise distance estimates based on the two-step process tend to be substantially less accurate. This improved performance carries through to tree inference, where PaHMM-Tree provides more accurate tree estimates than all of the pairwise distance methods assessed. For close to moderately divergent sequence data we find that the two-step methods using statistical inference, where information from all sequences is included in the estimation procedure, tend to perform better than PaHMM-Tree, particularly full statistical alignment, which simultaneously estimates both the tree and the alignment. For deep divergences we find the alignment step becomes so prone to error that our distance-based PaHMM-Tree outperforms all other methods of tree inference. Finally, we find that the accuracy of alignment-free methods tends to decline faster than standard two-step methods in the presence of alignment uncertainty, and identify no conditions where alignment-free methods are equal to or more accurate than standard phylogenetic methods even in the presence of substantial alignment error.
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