Step In Sequence Analysis Research Articles

Seismic 3D full-horizon tracking based on a knowledge graph to represent the stratigraphic sequence relationship

Seismic 3D full-horizon tracking is a fundamental and crucial step in sequence analysis and reservoir modeling. Existing automatic full-horizon tracking approaches lack effective methods for representing the stratigraphic sequence relationships in seismic data. However, the inability to represent the stratigraphic sequence relationships fully and accurately makes it challenging to address discontinuous areas affected by faults and unconformities. To address this issue, we develop a knowledge graph representing the stratigraphic sequence relationship, which enables the simultaneous extraction of all horizon surfaces once the stratigraphic distribution of the seismic data is obtained. This method first generates horizon patches and calculates the fault attributes, followed by the construction of an initial knowledge graph that characterizes the overall distribution of horizon patches and faults. The initial knowledge graph comprises nodes and edges. The nodes represent horizon patches, and their attributes cover the geographical location information of the patches and faults. Simultaneously, the edges represent the relationship between the horizon patches, including the stratigraphic sequence relationship, and their attributes illustrate the potential for connecting these patches. Furthermore, we introduce a multilayer knowledge graph based on the point-set topology to fuse the nodes. This allows for the continuous merging of the horizon patches to obtain horizon surfaces across discontinuities with the constraints of fault attributes and stratigraphic sequence relationships in 3D space. Synthetic and field examples demonstrate that our approach can effectively represent stratigraphic sequence relationships and accurately track horizons located in discontinuous areas with faults and unconformities.

Identity: rapid alignment-free prediction of sequence alignment identity scores using self-supervised general linear models.

Pairwise global alignment is a fundamental step in sequence analysis. Optimal alignment algorithms are quadratic—slow especially on long sequences. In many applications that involve large sequence datasets, all what is needed is calculating the identity scores (percentage of identical nucleotides in an optimal alignment—including gaps—of two sequences); there is no need for visualizing how every two sequences are aligned. For these applications, we propose Identity, which produces global identity scores for a large number of pairs of DNA sequences using alignment-free methods and self-supervised general linear models. For the first time, the new tool can predict pairwise identity scores in linear time and space. On two large-scale sequence databases, Identity provided the best compromise between sensitivity and precision while being faster than BLAST, Mash, MUMmer4 and USEARCH by 2–80 times. Identity was the best performing tool when searching for low-identity matches. While constructing phylogenetic trees from about 6000 transcripts, the tree due to the scores reported by Identity was the closest to the reference tree (in contrast to andi, FSWM and Mash). Identity is capable of producing pairwise identity scores of millions-of-nucleotides-long bacterial genomes; this task cannot be accomplished by any global-alignment-based tool. Availability: https://github.com/BioinformaticsToolsmith/Identity.

Analysis of genomic rearrangements by using the Burrows-Wheeler transform of short-read data.

BackgroundThe potential utility of the Burrows-Wheeler transform (BWT) of a large amount of short-read data ("reads") has not been fully studied. The BWT basically serves as a lossless dictionary of reads, unlike the heuristic and lossy reads-to-genome mapping results conventionally obtained in the first step of sequence analysis. Thus, it is naturally expected to lead to development of sensitive methods for analysis of short-read data. Recently, one of the most active areas of research in sequence analysis is sensitive detection of rare genomic rearrangements from whole-genome sequencing (WGS) data of heterogeneous cancer samples. The application the BWT of reads to the analysis of genomic rearrangements is addressed in this study.ResultsA new method for sensitive detection of genomic rearrangements by using the BWT of reads in the following three steps is proposed: first, breakpoint regions, which contain breakpoints and are joined together by rearrangement, are predicted from the distribution of so-called discordant pairs by using a kind of the conjugate gradient method; second, reads partially matching the breakpoint regions are collected from the BWT of reads; and third, breakpoints are detected as branching points among the collected reads, and their precise positions are determined. The method was experimentally implemented, and its performance (i.e., sensitivity and specificity) was evaluated by using simulated data with known artificial rearrangements. It was applied to publicly available real biological WGS data of cancer patients, and the detection results were compared with published results.ConclusionsServing as a lossless dictionary of reads, the BWT of short reads enables sensitive analysis of genomic rearrangements in heterogeneous cancer-genome samples when used in conjunction with breakpoint-region predictions based on a conjugate gradient method.

CGAP-Align: A High Performance DNA Short Read Alignment Tool

BackgroundNext generation sequencing platforms have greatly reduced sequencing costs, leading to the production of unprecedented amounts of sequence data. BWA is one of the most popular alignment tools due to its relatively high accuracy. However, mapping reads using BWA is still the most time consuming step in sequence analysis. Increasing mapping efficiency would allow the community to better cope with ever expanding volumes of sequence data.ResultsWe designed a new program, CGAP-align, that achieves a performance improvement over BWA without sacrificing recall or precision. This is accomplished through the use of Suffix Tarray, a novel data structure combining elements of Suffix Array and Suffix Tree. We also utilize a tighter lower bound estimation for the number of mismatches in a read, allowing for more effective pruning during inexact mapping. Evaluation of both simulated and real data suggests that CGAP-align consistently outperforms the current version of BWA and can achieve over twice its speed under certain conditions, all while obtaining nearly identical results.ConclusionCGAP-align is a new time efficient read alignment tool that extends and improves BWA. The increase in alignment speed will be of critical assistance to all sequence-based research and medicine. CGAP-align is freely available to the academic community at http://sourceforge.net/p/cgap-align under the GNU General Public License (GPL).

Large Disclosing the Nature of Computational Tools for the Analysis of Next Generation Sequencing Data

Next-generation sequencing (NGS) technologies are rapidly changing the approach to complex genomic studies, opening the way to personalized drugs development and personalized medicine. NGS technologies are characterized by a massive throughput for relatively short-sequences (30-100), and they are currently the most reliable and accurate method for grouping individuals on the basis of their genetic profiles. The first and crucial step in sequence analysis is the conversion of millions of short sequences (reads) into valuable genetic information by their mapping to a known (reference) genome. New computational methods, specifically designed for the type and the amount of data generated by NGS technologies, are replacing earlier widespread genome alignment algorithms which are unable to cope with such massive amount of data. This review provides an overview of the bioinformatics techniques that have been developed for the mapping of NGS data onto a reference genome, with a special focus on polymorphism rate and sequence error detection. The different techniques have been experimented on an appropriately defined dataset, to investigate their relative computational costs and usability, as seen from an user perspective. Since NGS platforms interrogate the genome using either the conventional nucleotide space or the more recent color space, this review does consider techniques both in nucleotide and color space, emphasizing similarities and diversities.

Parallel pairwise statistical significance estimation of local sequence alignment using Message Passing Interface library

SUMMARYHomology detection is a fundamental step in sequence analysis. In the recent years, pairwise statistical significance has emerged as a promising alternative to database statistical significance for homology detection. Although more accurate, currently it is much time consuming because it involves generating tens of hundreds of alignment scores to construct the empirical score distribution. This paper presents a parallel algorithm for pairwise statistical significance estimation, called MPIPairwiseStatSig, implemented in C using MPI library. We further apply the parallelization technique to estimate non‐conservative pairwise statistical significance using standard, sequence‐specific, and position‐specific substitution matrices, which has earlier demonstrated superior sequence comparison accuracy than original pairwise statistical significance. Distributing the most compute‐intensive portions of the pairwise statistical significance estimation procedure across multiple processors has been shown to result in near‐linear speed‐ups for the application. The MPIPairwiseStatSig program for pairwise statistical significance estimation is available for free academic use at www.cs.iastate.edu~ankitag/MPIPairwiseStatSig.html. Copyright © 2011 John Wiley & Sons, Ltd.

Assessment of replicate bias in 454 pyrosequencing and a multi-purpose read-filtering tool

BackgroundRoche 454 pyrosequencing platform is often considered the most versatile of the Next Generation Sequencing technology platforms, permitting the sequencing of large genomes, the analysis of variations or the study of transcriptomes. A recent reported bias leads to the production of multiple reads for a unique DNA fragment in a random manner within a run. This bias has a direct impact on the quality of the measurement of the representation of the fragments using the reads. Other cleaning steps are usually performed on the reads before assembly or alignment.FindingsPyroCleaner is a software module intended to clean 454 pyrosequencing reads in order to ease the assembly process. This program is a free software and is distributed under the terms of the GNU General Public License as published by the Free Software Foundation. It implements several filters using criteria such as read duplication, length, complexity, base-pair quality and number of undetermined bases. It also permits to clean flowgram files (.sff) of paired-end sequences generating on one hand validated paired-ends file and the other hand single read file.ConclusionsRead cleaning has always been an important step in sequence analysis. The pyrocleaner python module is a Swiss knife dedicated to 454 reads cleaning. It includes commonly used filters as well as specialised ones such as duplicated read removal and paired-end read verification.

Inapproximability of maximal strip recovery

In comparative genomics, the first step of sequence analysis is usually to decompose two or more genomes into syntenic blocks that are segments of homologous chromosomes. For the reliable recovery of syntenic blocks, noise and ambiguities in the genomic maps need to be removed first. Maximal Strip Recovery (MSR) is an optimization problem proposed by Zheng, Zhu, and Sankoff for reliably recovering syntenic blocks from genomic maps in the midst of noise and ambiguities. Given d genomic maps as sequences of gene markers, the objective of MSR- d is to find d subsequences, one subsequence of each genomic map, such that the total length of syntenic blocks in these subsequences is maximized. For any constant d ≥ 2 , a polynomial-time 2 d -approximation for MSR- d was previously known. In this paper, we show that for any d ≥ 2 , MSR- d is APX-hard, even for the most basic version of the problem in which all gene markers are distinct and appear in positive orientation in each genomic map. Moreover, we provide the first explicit lower bounds on approximating MSR- d for all d ≥ 2 . In particular, we show that MSR- d is NP-hard to approximate within Ω ( d / log d ) . From the other direction, we show that the previous 2 d -approximation for MSR- d can be optimized into a polynomial-time algorithm even if d is not a constant but is part of the input. We then extend our inapproximability results to several related problems including CMSR- d , δ -gap-MSR- d , and δ -gap-CMSR- d .

Analysis of SNPs and other genomic variations using gel-based chips.

Application of microarrays for the analysis of point mutations and SNPs in genomic DNAs is currently under intensive development. Various technologies are being investigated, employing enzymatic, chemical, and physical tools [for review, see Tillib and Mirzabekov, 2001]. Our current approach is based on the use of IMAGE chips (immobilized microarrays of gel elements) consisting of an array of gel pads attached to a hydrophobic glass surface. The gel pads range in size from picoliters to nanoliters and are used for immobilization of oligonucleotide probes, as well as miniature test tubes for chemical or enzymatic reactions with tethered compounds. Nucleic acids are hybridized, fractionated, modified, and subjected to enzymatic reactions inside the pads. All steps of sequence analysis (PCR-amplification, activation or release of primers and products, DNA extension, hybridization, and reading of the results) can be performed within the same pad. A flexible and inexpensive technology platform enables one to monitor processes in the arrays in both real time and steady-state. Identification of SNPs, microsequencing, and other specific tasks are easily performed. In particular, stacking interactions with short oligonucleotides enhance the capability of high-throughput screening. The IMAGE chips can be analyzed using a variety of equipment, from a dedicated multi-color fluorescent microscope or MALDI-spectrometer to an inexpensive portable analyzer suitable for field conditions. Customized gel-based chips were successfully used for screening of SNPs in a broad range of biologically meaningful genes.

An algorithm to analyse the hydrolysis pathway of peptides and proteins by sequence analyses of unfractionated digestion mixtures.

We have designed and implemented on a personal computer a program for identifying and quantifying the fragments present in a peptide mixture obtained by hydrolysing a polypeptide of known sequence using digesting agents. The qualitative data utilized by the main algorithm consist of the target sequence of the intact molecule and the amino acid residues identified at each step of the automatic sequence analysis of the unfractionated digestion mixture. In this way, the sequence of each fragment present in the mixture is quickly reconstructed. Furthermore, if the quantitative data of the amino acid residues identified at each step of the sequence analysis are utilized, the program will correlate the sequence of each fragment to its amount. We furnish an example of the application intended for the rapid identification and characterization of the extracellular proteinases produced by a basidiomycete fungus, utilizing the bovine insulin beta-chain as target substrate. A variety of uses for the method are discussed.

Determination of base ratios on sub-microgram quantities of RNA

1. Introduction The determination of base compositions of ribo- nucleic acids is an important step in sequence analysis. As RNAs are often not available in milligram quan- tities for the determination of base compositions using spectrophotometric procedures [l-6] , more sensitive radioactive labelling methods have been developed. The procedures of Sanger et al. [7] can be used directly for base composition analysis of RNA uniformly labelled with 32P to a high specific activity. But not all RNAs can be so labelled in vivo, and 32P also has an inconveniently short half-life. The Ran- deraths [8,9] .developed a method using sodium boro- [3H]hydride to reduce periodate-oxidised nucleosides to stable tritiated nucleoside tri-alcohols. Tritium has a low energy of radiation so it is difficult to detect by autoradiography, especially when picomole quantities of tritiated nucleoside tri-alcohols are analysed. We previously described a simple, sensitive proce- dure for chemically labelling RNA and its derivatives which uses p-hydrazinobenzene-[35S]sulphonic acid (35S-p-HBSA) as the radioactive labelling reagent [lo] We now wish to describe routine labelling procedure for determining base compositions of RNA and ribo- oligonucleotides. The procedure is simple and very sensitive requiring only 0.5 pg of the polymer for at least a triplicate determination. 2. Materials and methods 2.1.