String matching problems in bioinformatics are typically for finding exact substring matches between a query and a reference text. Previous formulations often focus on maximum exact matches (MEMs). However, multiple occurrences of substrings of the query in the text that are long enough but not maximal may not be captured by MEMs. Such long matches can be informative, especially when the text is a collection of similar sequences such as genomes. In this paper, we describe a new type of match between a pattern and a text that aren't necessarily maximal in the query, but still contain useful matching information: locally maximal exact matches (LEMs). There are usually a large amount of LEMs, so we only consider those above some length threshold ℒ. These are referred to as long LEMs. The purpose of long LEMs is to capture substring matches between a query and a text that are not necessarily maximal in the pattern but still long enough to be important. Therefore efficient long LEMs finding algorithms are desired for these datasets. However, these datasets are too large to query on traditional string indexes. Fortunately, these datasets are very repetitive. Recently, compressed string indexes that take advantage of the redundancy in the data but retain efficient querying capability have been proposed as a solution. We therefore give an efficient algorithm for computing all the long LEMs of a query and a text in a BWT runs compressed string index. We describe an O(m+occ) expected time algorithm that relies on an O(r) words space string index for outputting all long LEMs of a pattern with respect to a text given the matching statistics of the pattern with respect to the text. Here m is the length of the query, occ is the number of long LEMs outputted, and r is the number of runs in the BWT of the text. The O(r) space string index we describe relies on an adaptation of the move data structure by Nishimoto and Tabei. We are able to support LCP[i] queries in constant time given SA[i]. In other words, we answer PLCP[i] queries in constant time. These PLCP queries enable the efficient long LEM query. Long LEMs may provide useful similarity information between a pattern and a text that MEMs may ignore. This information is particularly useful in pangenome and biobank scale haplotype panel contexts.

MOTIVATION: The availability of large genotyped cohorts brings new opportunities for revealing the high-resolution genetic structure of admixed populations via local ancestry inference (LAI), the process of identifying the ancestry of each segment of an individual haplotype. Though current methods achieve high accuracy in standard cases, LAI is still challenging when reference populations are more similar (e.g. intra-continental), when the number of reference populations is too numerous, or when the admixture events are deep in time, all of which are increasingly unavoidable in large biobanks. RESULTS: In this work, we present Recomb-Mix, a new LAI method which integrates elements from the site-based Li and Stephens model and introduces a new graph collapsing techniques to simplify counting paths with the same ancestry label readout. Through comprehensive benchmarking on various simulated datasets, we show that Recomb-Mix is more accurate than existing methods in diverse sets of scenarios while being competitive in terms of resource efficiency. The scalability and robustness of Recomb-Mix are also demonstrated with real-world datasets. We expect that Recomb-Mix will be a useful method for advancing genetics studies of admixed populations. AVAILABILITY AND IMPLEMENTATION: The implementation of Recomb-Mix is available at https://github.com/ucfcbb/Recomb-Mix.

MOTIVATION: The 3D structures of RNA play a critical role in understanding their functionalities. There exist several computational methods to study RNA 3D structures by identifying structural motifs and categorizing them into several motif families based on their structures. Although the number of such motif families is not limited, a few of them are well-studied. Out of these structural motif families, there exist several families that are visually similar or very close in structure, even with different base interactions. Alternatively, some motif families share a set of base interactions but maintain variation in their 3D formations. These similarities among different motif families, if known, can provide a better insight into the RNA 3D structural motifs as well as their characteristic functions in cell biology. RESULTS: In this work, we proposed a method, RNAMotifComp, that analyzes the instances of well-known structural motif families and establishes a relational graph among them. We also have designed a method to visualize the relational graph where the families are shown as nodes and their similarity information is represented as edges. We validated our discovered correlations of the motif families using RNAMotifContrast. Additionally, we used a basic Naïve Bayes classifier to show the importance of RNAMotifComp. The relational analysis explains the functional analogies of divergent motif families and illustrates the situations where the motifs of disparate families are predicted to be of the same family. AVAILABILITY AND IMPLEMENTATION: Source code publicly available at https://github.com/ucfcbb/RNAMotifFamilySimilarity.

MOTIVATION: The positional Burrows-Wheeler transform (PBWT) has led to tremendous strides in haplotype matching on biobank-scale data. For genetic genealogical search, PBWT-based methods have optimized the asymptotic runtime of finding long matches between a query haplotype and a predefined panel of haplotypes. However, to enable fast query searches, the full-sized panel and PBWT data structures must be kept in memory, preventing existing algorithms from scaling up to modern biobank panels consisting of millions of haplotypes. In this work, we propose a space-efficient variation of PBWT named Syllable-PBWT, which divides every haplotype into syllables, builds the PBWT positional prefix arrays on the compressed syllabic panel, and leverages the polynomial rolling hash function for positional substring comparison. With the Syllable-PBWT data structures, we then present a long match query algorithm named Syllable-Query. RESULTS: Compared to the most time- and space-efficient previously published solution to the long match query problem, Syllable-Query reduced the memory use by a factor of over 100 on both the UK Biobank genotype data and the 1000 Genomes Project sequence data. Surprisingly, the smaller size of our syllabic data structures allows for more efficient iteration and CPU cache usage, granting Syllable-Query even faster runtime than existing solutions. AVAILABILITY AND IMPLEMENTATION: https://github.com/ZhiGroup/Syllable-PBWT. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: Due to the rapid growth of the genetic database size, genealogical search, a process of inferring familial relatedness by identifying DNA matches, has become a viable approach to help individuals finding missing family members or law enforcement agencies locating suspects. A fast and accurate method is needed to search an out-of-database individual against millions of individuals. Most existing approaches only offer all-versus-all within panel match. Some prototype algorithms offer one-versus-all query from out-of-panel individual, but they do not tolerate errors. RESULTS: A new method, random projection-based identity-by-descent (IBD) detection (RaPID) query, is introduced to make fast genealogical search possible. RaPID-Query identifies IBD segments between a query haplotype and a panel of haplotypes. By integrating matches over multiple PBWT indexes, RaPID-Query manages to locate IBD segments quickly with a given cutoff length while allowing mismatched sites. A single query against all UK biobank autosomal chromosomes was completed within 2.76 seconds on average, with the minimum length 7 cM and 700 markers. RaPID-Query achieved a 0.016 false negative rate and a 0.012 false positive rate simultaneously on a chromosome 20 sequencing panel having 86 265 sites. This is comparable to the state-of-the-art IBD detection method TPBWT(out-of-sample) and Hap-IBD. The high-quality IBD segments yielded by RaPID-Query were able to distinguish up to fourth degree of the familial relatedness for a given individual pair, and the area under the receiver operating characteristic curve values are at least 97.28%. AVAILABILITY AND IMPLEMENTATION: The RaPID-Query program is available at https://github.com/ucfcbb/RaPID-Query.

Efficient haplotype matching search is of great interest when large genotyped cohorts are becoming available. Positional Burrows-Wheeler Transform (PBWT) enables efficient searching for blocks of haplotype matches. However, existing efficient PBWT algorithms sweep across the haplotype panel from left to right, capturing all exact matches. As a result, PBWT does not account for mismatches. It is also not easy to investigate the patterns of changes between the matching blocks. Here, we present an extension to PBWT, called bi-directional PBWT that allows the information about the blocks of matches to be present at both sides of each site. We also present a set of algorithms to efficiently merge the matching blocks or examine the patterns of changes on both sides of each site. The time complexity of the algorithms to find and merge matching blocks using bi-directional PBWT is linear to the input size. Using real data from the UK Biobank, we demonstrate the run time and memory efficiency of our algorithms. More importantly, our algorithms can identify more blocks by enabling tolerance of mismatches. Moreover, by using mutual information (MI) between the forward and the reverse PBWT matching block sets as a measure of haplotype consistency, we found the MI derived from European samples in the 1000 Genomes Project is highly correlated (Spearman correlation r=0.87) with the deCODE recombination map.

Abstract Motivation Durbin’s positional Burrows–Wheeler transform (PBWT) is a scalable data structure for haplotype matching. It has been successfully applied to identical by descent (IBD) segment identification and genotype imputation. Once the PBWT of a haplotype panel is constructed, it supports efficient retrieval of all shared long segments among all individuals (long matches) and efficient query between an external haplotype and the panel. However, the standard PBWT is an array-based static data structure and does not support dynamic updates of the panel. Results Here, we generalize the static PBWT to a dynamic data structure, d-PBWT, where the reverse prefix sorting at each position is stored with linked lists. We also developed efficient algorithms for insertion and deletion of individual haplotypes. In addition, we verified that d-PBWT can support all algorithms of PBWT. In doing so, we systematically investigated variations of set maximal match and long match query algorithms: while they all have average case time complexity independent of database size, they have different worst case complexities and dependencies on additional data structures. Availabilityand implementation The benchmarking code is available at genome.ucf.edu/d-PBWT. Supplementary information Supplementary data are available at Bioinformatics online.

The ability to reverse engineer a hardware netlist in order to detect malicious logic has become an important problem in recent years. Much work has been done on algorithmically identifying structure and state in circuits; the first step of which is to separate control signals from data signals. The most current tools rely on topological comparisons of logic in order to identify signals which are uniquely structured in the netlist, as these signals are likely control signals. However, topological comparisons become less effective when a netlist has been resynthesized and optimized. We present a new tool, RELIC-FUN, based on netlist slicing and functional comparison of logic. Experimental results show that depending on netlist size, optimization, and control logic density, the proposed algorithm can be more accurate, and faster, than existing topological algorithms in many cases.

Assuring the quality and the trustworthiness of third party resources has been a hard problem to tackle. Researchers have shown that analyzing Integrated Circuits (IC), without the aid of golden models, is challenging. In this paper we discuss a toolset, NETA, designed to aid IP users in assuring the confidentiality, integrity, and accessibility of their IC or third party IP core. The discussed toolset gives access to a slew of gate-level analysis tools, many of which are heuristic-based, for the purposes of extracting high-level circuit design information. NETA majorly comprises the following tools: RELIC, REBUS, REPCA, REFSM, and REPATH.

MOTIVATION: With the wide availability of whole-genome genotype data, there is an increasing need for conducting genetic genealogical searches efficiently. Computationally, this task amounts to identifying shared DNA segments between a query individual and a very large panel containing millions of haplotypes. The celebrated Positional Burrows-Wheeler Transform (PBWT) data structure is a pre-computed index of the panel that enables constant time matching at each position between one haplotype and an arbitrarily large panel. However, the existing algorithm (Durbin's Algorithm 5) can only identify set-maximal matches, the longest matches ending at any location in a panel, while in real genealogical search scenarios, multiple 'good enough' matches are desired. RESULTS: In this work, we developed two algorithmic extensions of Durbin's Algorithm 5, that can find all L-long matches, matches longer than or equal to a given length L, between a query and a panel. In the first algorithm, PBWT-Query, we introduce 'virtual insertion' of the query into the PBWT matrix of the panel, and then scanning up and down for the PBWT match blocks with length greater than L. In our second algorithm, L-PBWT-Query, we further speed up PBWT-Query by introducing additional data structures that allow us to avoid iterating through blocks of incomplete matches. The efficiency of PBWT-Query and L-PBWT-Query is demonstrated using the simulated data and the UK Biobank data. Our results show that our proposed algorithms can detect related individuals for a given query efficiently in very large cohorts which enables a fast on-line query search. AVAILABILITY AND IMPLEMENTATION: genome.ucf.edu/pbwt-query. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: Recent advances in whole-genome sequencing and SNP array technology have led to the generation of a large amount of genotype data. Large volumes of genotype data will require faster and more efficient methods for storing and searching the data. Positional Burrows-Wheeler Transform (PBWT) provides an appropriate data structure for bi-allelic data. With the increasing sample sizes, more multi-allelic sites are expected to be observed. Hence, there is a necessity to handle multi-allelic genotype data. RESULTS: In this paper, we introduce a multi-allelic version of the Positional Burrows-Wheeler Transform (mPBWT) based on the bi-allelic version for compression and searching. The time-complexity for constructing the data structure and searching within a panel containing t-allelic sites increases by a factor of t. CONCLUSION: Considering the small value for the possible alleles t, the time increase for the multi-allelic PBWT will be negligible and comparable to the bi-allelic version of PBWT.

The urgent requests to protection integrated circuits (IC) and hardware intellectual properties (IP) have led to the development of various logic obfuscation methods. While most existing solutions focus on the combinational logic or sequential logic with full scan-chains, in this paper, we will revisit the security of sequential logic obfuscation within circuits where full scan-chains are not available or accessible. We will first introduce attack methods to compromise obfuscated sequential circuits leveraging newly developed netlist analysis tools. We will then propose systematic solutions and provide guidelines in developing resilient sequential logic obfuscation schemes.

In a modern IC design flow, from specification development to chip fabrication, various security threats are emergent. Of particular concern are modifications made to third-party IP cores and commercial off-the-shelf (COTS) chips where no golden models are available for comparisons. Toward this direction, we develop a tool, named Reverse Engineering Finite State Machine (REFSM), that helps end-users reconstruct a high-level description of the control logic from a flattened netlist. We demonstrate that REFSM effectively recovers circuit control logic from netlists with varying degrees of complexity. Experimental results also showed that the developed tool can easily identify malicious logic from a flattened (or even obfuscated) netlist. If combined with chip level reverse engineering techniques, the developed REFSM tool can help detect the insertion of hardware Trojans in fabricated circuits.

The heavy reliance on third-party resources, including third-party IP cores and fabrication foundries, has triggered the security concerns that design backdoors and/or hardware Trojans may be inserted into fabricated chips. While existing reverse engineering tools can help recover netlist from fabricated chips, there is a lack of efficient tools to further analyze the netlist for malicious logic detection and full functionality recovery. While it is relatively easy to identify the functional modules from the netlist using pattern matching methods, the main obstacle is to isolate control logic registers and reverseengineering the control logic. Upon this request, we proposed a topology-based computational method for register categorization. Through this proposed algorithm, we can differentiate data registers from control logic registers such that the control logic can be separated from the datapath. Experimental results showed that the suggested method was capable of identifying control logic registers in circuits with various complexities ranging from the RS232 core to the 8051 microprocessor.

The WebSTAR3D web server is a user-friendly online interface for the alignment of RNA 3D structures. The website takes as input two files, each of which can be in either PDB or mmCIF format, containing the desired structures to align, via a PDB code or user upload. In return, the user is presented with a visualization of the aligned structures in Jmol or JSmol, along with the corresponding sequence alignment, and the option to download the nucleotide mapping of the structures and a PDB file containing the aligned, superimposed structures. AVAILABILITY AND IMPLEMENTATION: The WebSTAR3D is available at http://rna.ucf.edu/WebSTAR3D CONTACT: [email protected].

Identification of non-coding RNAs (ncRNAs) has been significantly enhanced due to the rapid advancement in sequencing technologies. On the other hand, semantic annotation of ncRNA data lag behind their identification, and there is a great need to effectively integrate discovery from relevant communities. To this end, the Non-Coding RNA Ontology (NCRO) is being developed to provide a precisely defined ncRNA controlled vocabulary, which can fill a specific and highly needed niche in unification of ncRNA biology.

To address the concern that a complete detection scheme for effective hardware Trojan identification is lacking, we have designed an RTL security metric in order to evaluate the quality of IP cores (with the same or similar functionality) and counter Trojan attacks at the pre-fabrication stages of the IP design flow. The proposed security metric is constructed on top of two criteria, from which a quantitative security value can be assigned to the target circuit: 1) Distribution of controllability; 2) Existence of rare events. The proposed metric, called FIGHT, is an automated tool whereby malicious modifications to ICs and/or the vulnerability of the IP core can be identified, by monitoring both internal node controllability and the corresponding control value distribution plotted as a histogram. Experimentation on an RS232 module was performed to demonstrate our dual security criteria and proved security degradation to the IP module upon hardware Trojan insertion.

BACKGROUND: Recent advances in RNA structure probing technologies, including the ones based on high-throughput sequencing, have improved the accuracy of thermodynamic folding with quantitative nucleotide-resolution structural information. RESULTS: In this paper, we present a novel approach, ProbeAlign, to incorporate the reactivities from high-throughput RNA structure probing into ncRNA homology search for functional annotation. To reduce the overhead of structure alignment on large-scale data, the specific pairing patterns in the query sequences are ignored. On the other hand, the partial structural information of the target sequences embedded in probing data is retrieved to guide the alignment. Thus the structure alignment problem is transformed into a sequence alignment problem with additional reactivity information. The benchmark results show that the prediction accuracy of ProbeAlign outperforms filter-based CMsearch with high computational efficiency. The application of ProbeAlign to the FragSeq data, which is based on genome-wide structure probing, has demonstrated its capability to search ncRNAs in a large-scale dataset from high-throughput sequencing. CONCLUSIONS: By incorporating high-throughput sequencing-based structure probing information, ProbeAlign can improve the accuracy and efficiency of ncRNA homology search. It is a promising tool for ncRNA functional annotation on genome-wide datasets. AVAILABILITY: The source code of ProbeAlign is available at http://genome.ucf.edu/ProbeAlign.

BACKGROUND: RNAalifold, a popular computational method for RNA consensus structure prediction, incorporates covarying mutations into a thermodynamic model to fold the aligned RNA sequences. When quantifying covariance, it evaluates conserved signals of two aligned columns with base-pairing rules. This scoring scheme performs better than some other approaches, such as mutual information. However it ignores the phylogenetic history of the aligned sequences, which is an important criterion to evaluate the level of sequence covariance. RESULTS: In this article, in order to improve the accuracy of consensus structure folding, we propose a novel approach named PhyloRNAalifold. It incorporates the number of covarying mutations on the phylogenetic tree of the aligned sequences into the covariance scoring of RNAalifold. The benchmarking results show that the new scoring scheme of PhyloRNAalifold can improve the consensus structure detection of RNAalifold. CONCLUSION: Incorporating additional phylogenetic information of aligned sequences into the covariance scoring of RNAalifold can improve its performance of consensus structures folding. This improvement is correlated with alignment characteristics, such as pair-wise identity and the number of sequences in the alignment.

BACKGROUND: Current advances of the next-generation sequencing technology have revealed a large number of un-annotated RNA transcripts. Comparative study of the RNA structurome is an important approach to assess their biological functionalities. Due to the large sizes and abundance of the RNA transcripts, an efficient and accurate RNA structure-structure alignment algorithm is in urgent need to facilitate the comparative study. Despite the importance of the RNA secondary structure alignment problem, there are no computational tools available that provide high computational efficiency and accuracy. In this case, designing and implementing such an efficient and accurate RNA secondary structure alignment algorithm is highly desirable. RESULTS: In this work, through incorporating the sparse dynamic programming technique, we implemented an algorithm that has an O(n3) expected time complexity, where n is the average number of base pairs in the RNA structures. This complexity, which can be shown assuming the polymer-zeta property, is confirmed by our experiments. The resulting new RNA secondary structure alignment tool is called ERA. Benchmark results indicate that ERA can significantly speedup RNA structure-structure alignments compared to other state-of-the-art RNA alignment tools, while maintaining high alignment accuracy. CONCLUSIONS: Using the sparse dynamic programming technique, we are able to develop a new RNA secondary structure alignment tool that is both efficient and accurate. We anticipate that the new alignment algorithm ERA will significantly promote comparative RNA structure studies. The program, ERA, is freely available at http://genome.ucf.edu/ERA.

BACKGROUND: Accurately predicting low energy barrier folding pathways between conformational secondary structures of an RNA molecule can provide valuable information for understanding its catalytic and regulatory functions. Most existing heuristic algorithms guide the construction of folding pathways by free energies of intermediate structures in the next move during the folding. However due to the size and ruggedness of RNA energy landscape, energy-guided search can become trapped in local optima. RESULTS: In this paper, we propose an algorithm that guides the construction of folding pathways through the formation and destruction of RNA stacks. Guiding the construction of folding pathways by coarse grained movements of RNA stacks can help reduce the search space and make it easier to jump out of local optima. RNAEAPath is able to find lower energy barrier folding pathways between secondary structures of conformational switches and outperforms the existing heuristic algorithms in most test cases. CONCLUSIONS: RNAEAPath provides an alternate approach for predicting low-barrier folding pathways between RNA conformational secondary structures. The source code of RNAEAPath and the test data sets are available at http://genome.ucf.edu/RNAEAPath.

Structure-based RNA multiple alignment is particularly challenging because covarying mutations make sequence information alone insufficient. Existing tools for RNA multiple alignment first generate pairwise RNA structure alignments and then build the multiple alignment using only sequence information. Here we present PMFastR, an algorithm which iteratively uses a sequence-structure alignment procedure to build a structure-based RNA multiple alignment from one sequence with known structure and a database of sequences from the same family. PMFastR also has low memory consumption allowing for the alignment of large sequences such as 16S and 23S rRNA. The algorithm also provides a method to utilize a multicore environment. We present results on benchmark data sets from BRAliBase, which shows PMFastR performs comparably to other state-of-the-art programs. Finally, we regenerate 607 Rfam seed alignments and show that our automated process creates multiple alignments similar to the manually curated Rfam seed alignments. Thus, the techniques presented in this paper allow for the generation of multiple alignments using sequence-structure guidance, while limiting memory consumption. As a result, multiple alignments of long RNA sequences, such as 16S and 23S rRNAs, can easily be generated locally on a personal computer. The software and supplementary data are available at http://genome.ucf.edu/PMFastR.

MOTIVATION: Many RNAs, such as riboswitches, can fold into multiple alternate structures and perform different biological functions. These biologically functional structures usually have low free energies in their local energy landscapes and are very stable such that they cannot easily jump out of the current states and fold into other stable conformations. The conformational space of feasible RNA secondary structures is prohibitively large, and accurate prediction of functional structure conformations is challenging. Because the stability of an RNA secondary structure is determined predominantly by energetically favorable helical regions (stacks), we propose to use configurations of putative stacks to represent RNA secondary structures. By considering a reduced conformational space of local optimal stack configurations instead of all feasible RNA structures, we first present an algorithm for enumerating all possible local optimal stack configurations. In addition, we present a fast heuristic algorithm for approximating energy barriers encountered during folding pathways between each pair of local optimal stack configurations and finding all the stable local optimal structures. RESULTS: Benchmark tests have been conducted on several RNA riboswitches, whose alternate secondary structures have been experimentally verified. The benchmark results show that our method can successfully predict the native 'on' and 'off' secondary structures, and better rank them compared with other state-of-art approaches. AVAILABILITY: The software is freely available and can be downloaded at http://genome.ucf.edu/RNASLOpt. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The discovery of novel noncoding RNAs has been among the most exciting recent developments in biology. It has been hypothesized that there is, in fact, an abundance of functional noncoding RNAs (ncRNAs) with various catalytic and regulatory functions. However, the inherent signal for ncRNA is weaker than the signal for protein coding genes, making these harder to identify. We consider the following problem: Given an RNA sequence with a known secondary structure, efficiently detect all structural homologs in a genomic database by computing the sequence and structure similarity to the query. Our approach, based on structural filters that eliminate a large portion of the database while retaining the true homologs, allows us to search a typical bacterial genome in minutes on a standard PC. The results are two orders of magnitude better than the currently available software for the problem. We applied FastR to the discovery of novel riboswitches, which are a class of RNA domains found in the untranslated regions. They are of interest because they regulate metabolite synthesis by directly binding metabolites. We searched all available eubacterial and archaeal genomes for riboswitches from purine, lysine, thiamin, and riboflavin subfamilies. Our results point to a number of novel candidates for each of these subfamilies and include genomes that were not known to contain riboswitches.