MOTIVATION: Achieving a near complete understanding of how the genome of an individual affects the phenotypes of that individual requires deciphering the order of variations along homologous chromosomes in species with diploid genomes. However, true diploid assembly of long-range haplotypes remains challenging. RESULTS: To address this, we have developed Haplotype-resolved Assembly for Synthetic long reads using a Trio-binning strategy, or HAST, which uses parental information to classify reads into maternal or paternal. Once sorted, these reads are used to independently de novo assemble the parent-specific haplotypes. We applied HAST to cobarcoded second-generation sequencing data from an Asian individual, resulting in a haplotype assembly covering 94.7% of the reference genome with a scaffold N50 longer than 11 Mb. The high haplotyping precision (∼99.7%) and recall (∼95.9%) represents a substantial improvement over the commonly used tool for assembling cobarcoded reads (Supernova), and is comparable to a trio-binning-based third generation long-read-based assembly method (TrioCanu) but with a significantly higher single-base accuracy [up to 99.99997% (Q65)]. This makes HAST a superior tool for accurate haplotyping and future haplotype-based studies. AVAILABILITY AND IMPLEMENTATION: The code of the analysis is available at https://github.com/BGI-Qingdao/HAST. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: The adaptive immune response intrinsically depends on hypervariable human leukocyte antigen (HLA) genes. Concomitantly, correct HLA phenotyping is crucial for successful donor-patient matching in organ transplantation. The cost and technical limitations of current laboratory techniques, together with advances in next-generation sequencing (NGS) methodologies, have increased the need for precise computational typing methods. RESULTS: We tested two widespread HLA typing methods using high quality full genome sequencing data from 150 individuals in 50 family trios from the Genome Denmark project. First, we computed descendant accuracies assessing the agreement in the inheritance of alleles from parents to offspring. Second, we compared the locus-specific homozygosity rates as well as the allele frequencies; and we compared those to the observed values in related populations. We provide guidelines for testing the accuracy of HLA typing methods by comparing family information, which is independent of the availability of curated alleles. CONCLUSIONS: Although current computational methods for HLA typing generally provide satisfactory results, our benchmark - using data with ultra-high sequencing depth - demonstrates the incompleteness of current reference databases, and highlights the importance of providing genomic databases addressing current sequencing standards, a problem yet to be resolved before benefiting fully from personalised medicine approaches HLA phenotyping is essential.

BACKGROUND: Short-read aligners have recently gained a lot of speed by exploiting the massive parallelism of GPU. An uprising alterative to GPU is Intel MIC; supercomputers like Tianhe-2, currently top of TOP500, is built with 48,000 MIC boards to offer ~55 PFLOPS. The CPU-like architecture of MIC allows CPU-based software to be parallelized easily; however, the performance is often inferior to GPU counterparts as an MIC card contains only ~60 cores (while a GPU card typically has over a thousand cores). RESULTS: To better utilize MIC-enabled computers for NGS data analysis, we developed a new short-read aligner MICA that is optimized in view of MIC's limitation and the extra parallelism inside each MIC core. By utilizing the 512-bit vector units in the MIC and implementing a new seeding strategy, experiments on aligning 150 bp paired-end reads show that MICA using one MIC card is 4.9 times faster than BWA-MEM (using 6 cores of a top-end CPU), and slightly faster than SOAP3-dp (using a GPU). Furthermore, MICA's simplicity allows very efficient scale-up when multiple MIC cards are used in a node (3 cards give a 14.1-fold speedup over BWA-MEM). SUMMARY: MICA can be readily used by MIC-enabled supercomputers for production purpose. We have tested MICA on Tianhe-2 with 90 WGS samples (17.47 Tera-bases), which can be aligned in an hour using 400 nodes. MICA has impressive performance even though MIC is only in its initial stage of development. AVAILABILITY AND IMPLEMENTATION: MICA's source code is freely available at http://sourceforge.net/projects/mica-aligner under GPL v3. SUPPLEMENTARY INFORMATION: Supplementary information is available as "Additional File 1". Datasets are available at www.bio8.cs.hku.hk/dataset/mica.

UNLABELLED: Single nucleotide variations (SNVs) located within a reading frame can result in single amino acid polymorphisms (SAPs), leading to alteration of the corresponding amino acid sequence as well as function of a protein. Accurate detection of SAPs is an important issue in proteomic analysis at the experimental and bioinformatic level. Herein, we present sapFinder, an R software package, for detection of the variant peptides based on tandem mass spectrometry (MS/MS)-based proteomics data. This package automates the construction of variation-associated databases from public SNV repositories or sample-specific next-generation sequencing (NGS) data and the identification of SAPs through database searching, post-processing and generation of HTML-based report with visualized interface. AVAILABILITY AND IMPLEMENTATION: sapFinder is implemented as a Bioconductor package in R. The package and the vignette can be downloaded at http://bioconductor.org/packages/devel/bioc/html/sapFinder.html and are provided under a GPL-2 license.

MOTIVATION: Transcriptome sequencing has long been the favored method for quickly and inexpensively obtaining a large number of gene sequences from an organism with no reference genome. Owing to the rapid increase in throughputs and decrease in costs of next- generation sequencing, RNA-Seq in particular has become the method of choice. However, the very short reads (e.g. 2 × 90 bp paired ends) from next generation sequencing makes de novo assembly to recover complete or full-length transcript sequences an algorithmic challenge. RESULTS: Here, we present SOAPdenovo-Trans, a de novo transcriptome assembler designed specifically for RNA-Seq. We evaluated its performance on transcriptome datasets from rice and mouse. Using as our benchmarks the known transcripts from these well-annotated genomes (sequenced a decade ago), we assessed how SOAPdenovo-Trans and two other popular transcriptome assemblers handled such practical issues as alternative splicing and variable expression levels. Our conclusion is that SOAPdenovo-Trans provides higher contiguity, lower redundancy and faster execution. AVAILABILITY AND IMPLEMENTATION: Source code and user manual are available at http://sourceforge.net/projects/soapdenovotrans/.

MOTIVATION: RNA-Seq provides a powerful approach to carry out ab initio investigation of fusion transcripts representing critical translocation and post-transcriptional events that recode hereditary information. Most of the existing computational fusion detection tools are challenged by the issues of accuracy and how to handle multiple mappings. RESULTS: We present a novel tool SOAPfusion for fusion discovery with paired-end RNA-Seq reads. SOAPfusion is accurate and efficient for fusion discovery with high sensitivity (≥93%), low false-positive rate (≤1.36%), even the coverage is as low as 10×, highlighting its ability to detect fusions efficiently at low sequencing cost. From real data of Universal Human Reference RNA (UHRR) samples, SOAPfusion detected 7 novel fusion genes, more than other existing tools and all genes have been validated through reverse transcription-polymerase chain reaction followed by Sanger sequencing. SOAPfusion thus proves to be an effective method with precise applicability in search of fusion transcripts, which is advantageous to accelerate pathological and therapeutic cancer studies.

MOTIVATION: Despite the prevalence of copy number variation (CNV) in the human genome, only a handful of confirmed associations have been reported between common CNVs and complex disease. This may be partially attributed to the difficulty in accurately genotyping CNVs in large cohorts using array-based technologies. Exome sequencing is now widely being applied to case-control cohorts and presents an exciting opportunity to look for common CNVs associated with disease. RESULTS: We developed ExoCNVTest: an exome sequencing analysis pipeline to identify disease-associated CNVs and to generate absolute copy number genotypes at putatively associated loci. Our method re-discovered the LCE3B_LCE3C CNV association with psoriasis (P-value = 5 × 10e-6) while controlling inflation of test statistics (λ < 1). ExoCNVTest-derived absolute CNV genotypes were 97.4% concordant with PCR-derived genotypes at this locus. AVAILABILITY AND IMPLEMENTATION: ExoCNVTest has been implemented in Java and R and is freely available from www1.imperial.ac.uk/medicine/people/l.coin/. CONTACT: [email protected] or [email protected].

BACKGROUND: Estimation of allele frequency is of fundamental importance in population genetic analyses and in association mapping. In most studies using next-generation sequencing, a cost effective approach is to use medium or low-coverage data (e.g., < 15X). However, SNP calling and allele frequency estimation in such studies is associated with substantial statistical uncertainty because of varying coverage and high error rates. RESULTS: We evaluate a new maximum likelihood method for estimating allele frequencies in low and medium coverage next-generation sequencing data. The method is based on integrating over uncertainty in the data for each individual rather than first calling genotypes. This method can be applied to directly test for associations in case/control studies. We use simulations to compare the likelihood method to methods based on genotype calling, and show that the likelihood method outperforms the genotype calling methods in terms of: (1) accuracy of allele frequency estimation, (2) accuracy of the estimation of the distribution of allele frequencies across neutrally evolving sites, and (3) statistical power in association mapping studies. Using real re-sequencing data from 200 individuals obtained from an exon-capture experiment, we show that the patterns observed in the simulations are also found in real data. CONCLUSIONS: Overall, our results suggest that association mapping and estimation of allele frequencies should not be based on genotype calling in low to medium coverage data. Furthermore, if genotype calling methods are used, it is usually better not to filter genotypes based on the call confidence score.

SUMMARY: SOAP2 is a significantly improved version of the short oligonucleotide alignment program that both reduces computer memory usage and increases alignment speed at an unprecedented rate. We used a Burrows Wheeler Transformation (BWT) compression index to substitute the seed strategy for indexing the reference sequence in the main memory. We tested it on the whole human genome and found that this new algorithm reduced memory usage from 14.7 to 5.4 GB and improved alignment speed by 20-30 times. SOAP2 is compatible with both single- and paired-end reads. Additionally, this tool now supports multiple text and compressed file formats. A consensus builder has also been developed for consensus assembly and SNP detection from alignment of short reads on a reference genome. AVAILABILITY: http://soap.genomics.org.cn.

SUMMARY: We have developed a program SOAP for efficient gapped and ungapped alignment of short oligonucleotides onto reference sequences. The program is designed to handle the huge amounts of short reads generated by parallel sequencing using the new generation Illumina-Solexa sequencing technology. SOAP is compatible with numerous applications, including single-read or pair-end resequencing, small RNA discovery and mRNA tag sequence mapping. SOAP is a command-driven program, which supports multi-threaded parallel computing, and has a batch module for multiple query sets. AVAILABILITY: http://soap.genomics.org.cn.

BACKGROUND: The main two sorts of automatic gene annotation frameworks are ab initio and alignment-based, the latter splitting into two sub-groups. The first group is used for intra-species alignments, among which are successful ones with high specificity and speed. The other group contains more sensitive methods which are usually applied in aligning inter-species sequences. RESULTS: Here we present a new algorithm called CAT (for Cross-species Alignment Tool). It is designed to align mRNA sequences to mammalian-sized genomes. CAT is implemented using C scripts and is freely available on the web at http://xat.sourceforge.net/. CONCLUSIONS: Examined from different angles, CAT outperforms other extant alignment tools. Tested against all available mouse-human and zebrafish-human orthologs, we demonstrate that CAT combines the specificity and speed of the best intra-species algorithms, like BLAT and sim4, with the sensitivity of the best inter-species tools, like GeneWise.

We describe an algorithm, ReAS, to recover ancestral sequences for transposable elements (TEs) from the unassembled reads of a whole genome shotgun. The main assumptions are that these TEs must exist at high copy numbers across the genome and must not be so old that they are no longer recognizable in comparison to their ancestral sequences. Tested on the japonica rice genome, ReAS was able to reconstruct all of the high copy sequences in the Repbase repository of known TEs, and increase the effectiveness of RepeatMasker in identifying TEs from genome sequences.