MOTIVATION: The Full-text index in Minute space (FM-index) is a memory-efficient data structure widely used in bioinformatics for solving the fundamental pattern-matching task of searching for short patterns within a long reference. With the demand for short query patterns, the k-ordered concept has been proposed for FM-indexes. However, few construction algorithms in the state of the art fully exploit this idea to achieve significant speedups in the pan-genome era. RESULTS: We introduce the k-ordered Induced Suffix Sorting (kISS) for efficient construction and utilization of k-ordered FM-indexes. We present an algorithmic workflow for building k-ordered suffix arrays, incorporating two novel strategies to improve time and memory efficiency. We also demonstrate the compatibility of integrating k-ordered FM-indexes with locate operations in FMtree. Experiments show that kISS can improve the construction time, and the generated k-ordered suffix array can also be applied to FMtree without any additional in computation or memory usage. AVAILABILITY: https://github.com/jhhung/kISS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Since the 90s, keyword-based search engines have been the only option for people to locate relevant web content through a simple query comprising one to a few keywords. These engines, whether free or paid, retained users' search queries and preferences, often to deliver targeted ads. Additionally, user-uploaded articles for plagiarism detection can further be stored as part of service providers' expanding databases for profit. Essentially, users could not search without exposing their queries to these providers. We present a new solution here: a method for searching the internet using a full article as a query without disclosing the content. Our Sapiens Aperio Veritas Engine (S.A.V.E.) uses an encoding scheme and an FM-index search, borrowed from next-generation human genome sequencing. Each word in a user's query is transformed into one of 12 "amino acids" to create a pseudo-biological sequence (PBS) on the user's device. Plagiarism checks are done by users submitting their locally created PBSs to our cloud service. This detects identical content in our database, which includes all English and Chinese Wikipedia articles and Open Access journals up to April 2021. PBSs, longer than 12 "amino acids", show accurate results with less than 0.8% false positives. Performance-wise, S.A.V.E. runs at a similar genome-mapping speed as Bowtie and is >5 orders faster than BLAST. With both standard and private modes, S.A.V.E. offers a revolutionary, privacy-first search and plagiarism check system. We believe this sets an exciting precedent for future search engines prioritizing user confidentiality. S.A.V.E. can be accessed at https://dyn.life.nthu.edu.tw/SAVE/.

MOTIVATION: Cross-sample comparisons or large-scale meta-analyses based on the next generation sequencing (NGS) involve replicable and universal data preprocessing, including removing adapter fragments in contaminated reads (i.e. adapter trimming). While modern adapter trimmers require users to provide candidate adapter sequences for each sample, which are sometimes unavailable or falsely documented in the repositories (such as GEO or SRA), large-scale meta-analyses are therefore jeopardized by suboptimal adapter trimming. RESULTS: Here we introduce a set of fast and accurate adapter detection and trimming algorithms that entail no a priori adapter sequences. These algorithms were implemented in modern C++ with SIMD and multithreading to accelerate its speed. Our experiments and benchmarks show that the implementation (i.e. EARRINGS), without being given any hint of adapter sequences, can reach comparable accuracy and higher throughput than that of existing adapter trimmers. EARRINGS is particularly useful in meta-analyses of a large batch of datasets and can be incorporated in any sequence analysis pipelines in all scales. AVAILABILITY AND IMPLEMENTATION: EARRINGS is open-source software and is available at https://github.com/jhhung/EARRINGS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A reconfigurable wrapper provides the flexibility for a core test to utilize different bandwidths of test access mechanism (TAM) at different test time points. By using reconfigurable wrappers, the lower bound of total test application time can be achieved. However, since reconfigurable wrappers attempt to utilize TAM bandwidth as fully as possible, they often consume a lot of routing resources. In advanced technology nodes, routability has become a critical and difficult issue. In this paper, based on reconfigurable wrappers, we present the first work that studies the correlation between grid-based TAM wire routing and test scheduling. Our objective is to derive a feasible grid-based TAM wire routing solution with the minimum total test application time. Compared with previous works, the main advantage of our approach is that it can resolve the grid-based TAM wire routing congestion problem during test scheduling. Benchmark data show that our approach can effectively and efficiently minimize the total test application time under grid-based routing congestion constraints.

MOTIVATION: The Full-text index in Minute space (FM-index) derived from the Burrows-Wheeler transform (BWT) is broadly used for fast string matching in large genomes or a huge set of sequencing reads. Several graphic processing unit (GPU) accelerated aligners based on the FM-index have been proposed recently; however, the construction of the index is still handled by central processing unit (CPU), only parallelized in data level (e.g. by performing blockwise suffix sorting in GPU), or not scalable for large genomes. RESULTS: To fulfill the need for a more practical, hardware-parallelizable indexing and matching approach, we herein propose sBWT based on a BWT variant (i.e. Schindler transform) that can be built with highly simplified hardware-acceleration-friendly algorithms and still suffices accurate and fast string matching in repetitive references. In our tests, the implementation achieves significant speedups in indexing and searching compared with other BWT-based tools and can be applied to a variety of domains. AVAILABILITY AND IMPLEMENTATION: sBWT is implemented in C ++ with CPU-only and GPU-accelerated versions. sBWT is open-source software and is available at http://jhhung.github.io/sBWT/Supplementary information: Supplementary data are available at Bioinformatics online. CONTACT: [email protected] or [email protected] (also [email protected]).

BACKGROUND: In modern paired-end sequencing protocols short DNA fragments lead to adapter-appended reads. Current paired-end adapter removal approaches trim adapter by scanning the fragment of adapter on the 3' end of the reads, which are not competent in some applications. RESULTS: Here, we propose a fast and highly accurate adapter-trimming algorithm, PEAT, designed specifically for paired-end sequencing. PEAT requires no a priori adaptor sequence, which is convenient for large-scale meta-analyses. We assessed the performance of PEAT with many adapter trimmers in both simulated and real life paired-end sequencing libraries. The importance of adapter trimming was exemplified by the influence of the downstream analyses on RNA-seq, ChIP-seq and MNase-seq. Several useful guidelines of applying adapter trimmers with aligners were suggested. CONCLUSIONS: PEAT can be easily included in the routine paired-end sequencing pipeline. The executable binaries and the standalone C++ source code package of PEAT are freely available online.

A central goal of biology is understanding and describing the molecular basis of plasticity: the sets of genes that are combinatorially selected by exogenous and endogenous environmental changes, and the relations among the genes. The most viable current approach to this problem consists of determining whether sets of genes are connected by some common theme, e.g. genes from the same pathway are overrepresented among those whose differential expression in response to a perturbation is most pronounced. There are many approaches to this problem, and the results they produce show a fair amount of dispersion, but they all fall within a common framework consisting of a few basic components. We critically review these components, suggest best practices for carrying out each step, and propose a voting method for meeting the challenge of assessing different methods on a large number of experimental data sets in the absence of a gold standard.

The cost and time to develop a drug continues to be a major barrier to widespread distribution of medication. Although the genomic revolution appears to have had little impact on this problem, and might even have exacerbated it because of the flood of additional and usually ineffective leads, the emergence of high throughput resources promises the possibility of rapid, reliable and systematic identification of approved drugs for originally unintended uses. In this paper we develop and apply a method for identifying such repositioned drug candidates against breast cancer, myelogenous leukemia and prostate cancer by looking for inverse correlations between the most perturbed gene expression levels in human cancer tissue and the most perturbed expression levels induced by bioactive compounds. The method uses variable gene signatures to identify bioactive compounds that modulate a given disease. This is in contrast to previous methods that use small and fixed signatures. This strategy is based on the observation that diseases stem from failed/modified cellular functions, irrespective of the particular genes that contribute to the function, i.e., this strategy targets the functional signatures for a given cancer. This function-based strategy broadens the search space for the effective drugs with an impressive hit rate. Among the 79, 94 and 88 candidate drugs for breast cancer, myelogenous leukemia and prostate cancer, 32%, 13% and 17% respectively are either FDA-approved/in-clinical-trial drugs, or drugs with suggestive literature evidences, with an FDR of 0.01. These findings indicate that the method presented here could lead to a substantial increase in efficiency in drug discovery and development, and has potential application for the personalized medicine.

In this paper, we present an efficient approach to make functional change by using spare cells efficiently. The proposed approach includes two main steps (1) technology remapping and (2) spare cell selection. In technology remapping step, resource constraints will be considered to find a set of proper cells for remapping with examining resources exhaustively. In spare cell selection, we regard this problem as a question of resource allocation, the goal is to simultaneously select the suitable spare cells to achieve the functional changes and minimize the wirelength increases. We modify the matching algorithm to solve the spare cell selection with the goal of minimizing the increase in wire length, and use two wiring cost estimate methods to improve the wiring cost measurement of accuracy. Experimental results based on nine industry benchmarks show that there is 1% bias between the wiring cost our approach estimated and the actual wiring cost.

In this paper, the content-based retrieval with audio examples based on MP3 digital music archive for one singer is considered. In our proposed method, the Sub-Band Coefficients (SBC) in a MP3 frame is used for feature extraction. Both Quantization-Tree indexing (QT) approach and the Melody-Line Tracking (MLT) approach are proposed for indexing MP3 objects. Finally, a two-stage comparison method is used to measure the similarity between MP3 objects. We also employ the measurement of the similarity between query sample and database items for a singer. Evaluations on a content-based MP3 retrieval system are performed. Experimental results show that our proposed approach can achieve good performance and high accuracy.