Compression of FASTQ and SAM Format Sequencing Data

Storage and transmission of the data produced by modern DNA sequencing instruments has become a major concern, which prompted the Pistoia Alliance to pose the SequenceSqueeze contest for compression of FASTQ files. We present several compression entries from the competition, Fastqz and Samcomp/Fqzcomp, including the winning entry. These are compared against existing algorithms for both reference based compression (CRAM, Goby) and non-reference based compression (DSRC, BAM) and other recently published competition entries (Quip, SCALCE). The tools are shown to be the new Pareto frontier for FASTQ compression, offering state of the art ratios at affordable CPU costs. All programs are freely available on SourceForge. Fastqz: https://sourceforge.net/projects/fastqz/, fqzcomp: https://sourceforge.net/projects/fqzcomp/, and samcomp: https://sourceforge.net/projects/samcomp/.     

PHYSICO2: an UNIX based standalone procedure for computation of physicochemical,window-dependent and substitution based evolutionary properties of protein sequences along with automated block preparation tool,version 2

AvailabilityPHYSICO2: is freely available at http://sourceforge.net/projects/physico2/ along with its documentation at https://sourceforge.net/projects/physico2/files/Documentation.pdf/download for all users.     

ADSBET2: Automated Determination of Salt-Bridge Energy-Terms version 2

AvailabilityADSBET2 is freely available at http://sourceforge.net/projects/ADSBET2/ for all users.     

SBION2: Analyses of Salt Bridges from Multiple Structure Files,Version 2

AvailabilitySBION2 is freely available at http://sourceforge.net/projects/sbion2/ for academic users     

A Scalable and Accurate Targeted Gene Assembly Tool (SAT-Assembler) for Next-Generation Sequencing Data

Gene assembly, which recovers gene segments from short reads, is an important step in functional analysis of next-generation sequencing data. Lacking quality reference genomes, de novo assembly is commonly used for RNA-Seq data of non-model organisms and metagenomic data. However, heterogeneous sequence coverage caused by heterogeneous expression or species abundance, similarity between isoforms or homologous genes, and large data size all pose challenges to de novo assembly. As a result, existing assembly tools tend to output fragmented contigs or chimeric contigs, or have high memory footprint. In this work, we introduce a targeted gene assembly program SAT-Assembler, which aims to recover gene families of particular interest to biologists. It addresses the above challenges by conducting family-specific homology search, homology-guided overlap graph construction, and careful graph traversal. It can be applied to both RNA-Seq and metagenomic data. Our experimental results on an Arabidopsis RNA-Seq data set and two metagenomic data sets show that SAT-Assembler has smaller memory usage, comparable or better gene coverage, and lower chimera rate for assembling a set of genes from one or multiple pathways compared with other assembly tools. Moreover, the family-specific design and rapid homology search allow SAT-Assembler to be naturally compatible with parallel computing platforms. The source code of SAT-Assembler is available at https://sourceforge.net/projects/sat-assembler/. The data sets and experimental settings can be found in supplementary material.     

CPAG: software for leveraging pleiotropy in GWAS to reveal similarity between human traits links plasma fatty acids and intestinal inflammation

Meta-analyses of genome-wide association studies (GWAS) have demonstrated that the same genetic variants can be associated with multiple diseases and other complex traits. We present software called CPAG (Cross-Phenotype Analysis of GWAS) to look for similarities between 700 traits, build trees with informative clusters, and highlight underlying pathways. Clusters are consistent with pre-defined groups and literature-based validation but also reveal novel connections. We report similarity between plasma palmitoleic acid and Crohn''s disease and find that specific fatty acids exacerbate enterocolitis in zebrafish. CPAG will become increasingly powerful as more genetic variants are uncovered, leading to a deeper understanding of complex traits. CPAG is freely available at www.sourceforge.net/projects/CPAG/.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0722-1) contains supplementary material, which is available to authorized users.     

morFeus: a web-based program to detect remotely conserved orthologs using symmetrical best hits and orthology network scoring

Background

Searching the orthologs of a given protein or DNA sequence is one of the most important and most commonly used Bioinformatics methods in Biology. Programs like BLAST or the orthology search engine Inparanoid can be used to find orthologs when the similarity between two sequences is sufficiently high. They however fail when the level of conservation is low. The detection of remotely conserved proteins oftentimes involves sophisticated manual intervention that is difficult to automate.

Results

Here, we introduce morFeus, a search program to find remotely conserved orthologs. Based on relaxed sequence similarity searches, morFeus selects sequences based on the similarity of their alignments to the query, tests for orthology by iterative reciprocal BLAST searches and calculates a network score for the resulting network of orthologs that is a measure of orthology independent of the E-value. Detecting remotely conserved orthologs of a protein using morFeus thus requires no manual intervention. We demonstrate the performance of morFeus by comparing it to state-of-the-art orthology resources and methods. We provide an example of remotely conserved orthologs, which were experimentally shown to be functionally equivalent in the respective organisms and therefore meet the criteria of the orthology-function conjecture.

Conclusions

Based on our results, we conclude that morFeus is a powerful and specific search method for detecting remotely conserved orthologs. morFeus is freely available at http://bio.biochem.mpg.de/morfeus/. Its source code is available from Sourceforge.net (https://sourceforge.net/p/morfeus/).

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-263) contains supplementary material, which is available to authorized users.     

MutAid: Sanger and NGS Based Integrated Pipeline for Mutation Identification,Validation and Annotation in Human Molecular Genetics

Traditional Sanger sequencing as well as Next-Generation Sequencing have been used for the identification of disease causing mutations in human molecular research. The majority of currently available tools are developed for research and explorative purposes and often do not provide a complete, efficient, one-stop solution. As the focus of currently developed tools is mainly on NGS data analysis, no integrative solution for the analysis of Sanger data is provided and consequently a one-stop solution to analyze reads from both sequencing platforms is not available. We have therefore developed a new pipeline called MutAid to analyze and interpret raw sequencing data produced by Sanger or several NGS sequencing platforms. It performs format conversion, base calling, quality trimming, filtering, read mapping, variant calling, variant annotation and analysis of Sanger and NGS data under a single platform. It is capable of analyzing reads from multiple patients in a single run to create a list of potential disease causing base substitutions as well as insertions and deletions. MutAid has been developed for expert and non-expert users and supports four sequencing platforms including Sanger, Illumina, 454 and Ion Torrent. Furthermore, for NGS data analysis, five read mappers including BWA, TMAP, Bowtie, Bowtie2 and GSNAP and four variant callers including GATK-HaplotypeCaller, SAMTOOLS, Freebayes and VarScan2 pipelines are supported. MutAid is freely available at https://sourceforge.net/projects/mutaid.     

iPiG: Integrating Peptide Spectrum Matches into Genome Browser Visualizations

Proteogenomic approaches have gained increasing popularity, however it is still difficult to integrate mass spectrometry identifications with genomic data due to differing data formats. To address this difficulty, we introduce iPiG as a tool for the integration of peptide identifications from mass spectrometry experiments into existing genome browser visualizations. Thereby, the concurrent analysis of proteomic and genomic data is simplified and proteomic results can directly be compared to genomic data. iPiG is freely available from https://sourceforge.net/projects/ipig/. It is implemented in Java and can be run as a stand-alone tool with a graphical user-interface or integrated into existing workflows. Supplementary data are available at PLOS ONE online.     

Allele-specific copy-number discovery from whole-genome and whole-exome sequencing

Copy-number variants (CNVs) are a major form of genetic variation and a risk factor for various human diseases, so it is crucial to accurately detect and characterize them. It is conceivable that allele-specific reads from high-throughput sequencing data could be leveraged to both enhance CNV detection and produce allele-specific copy number (ASCN) calls. Although statistical methods have been developed to detect CNVs using whole-genome sequence (WGS) and/or whole-exome sequence (WES) data, information from allele-specific read counts has not yet been adequately exploited. In this paper, we develop an integrated method, called AS-GENSENG, which incorporates allele-specific read counts in CNV detection and estimates ASCN using either WGS or WES data. To evaluate the performance of AS-GENSENG, we conducted extensive simulations, generated empirical data using existing WGS and WES data sets and validated predicted CNVs using an independent methodology. We conclude that AS-GENSENG not only predicts accurate ASCN calls but also improves the accuracy of total copy number calls, owing to its unique ability to exploit information from both total and allele-specific read counts while accounting for various experimental biases in sequence data. Our novel, user-friendly and computationally efficient method and a complete analytic protocol is freely available at https://sourceforge.net/projects/asgenseng/.     

Virmid: accurate detection of somatic mutations with sample impurity inference

Detection of somatic variation using sequence from disease-control matched data sets is a critical first step. In many cases including cancer, however, it is hard to isolate pure disease tissue, and the impurity hinders accurate mutation analysis by disrupting overall allele frequencies. Here, we propose a new method, Virmid, that explicitly determines the level of impurity in the sample, and uses it for improved detection of somatic variation. Extensive tests on simulated and real sequencing data from breast cancer and hemimegalencephaly demonstrate the power of our model. A software implementation of our method is available at http://sourceforge.net/projects/virmid/.     

LymAnalyzer: a tool for comprehensive analysis of next generation sequencing data of T cell receptors and immunoglobulins

The adaptive immune system includes populations of B and T cells capable of binding foreign epitopes via antigen specific receptors, called immunoglobulin (IG) for B cells and the T cell receptor (TCR) for T cells. In order to provide protection from a wide range of pathogens, these cells display highly diverse repertoires of IGs and TCRs. This is achieved through combinatorial rearrangement of multiple gene segments in addition, for B cells, to somatic hypermutation. Deep sequencing technologies have revolutionized analysis of the diversity of these repertoires; however, accurate TCR/IG diversity profiling requires specialist bioinformatics tools. Here we present LymAnalzyer, a software package that significantly improves the completeness and accuracy of TCR/IG profiling from deep sequence data and includes procedures to identify novel alleles of gene segments. On real and simulated data sets LymAnalyzer produces highly accurate and complete results. Although, to date we have applied it to TCR/IG data from human and mouse, it can be applied to data from any species for which an appropriate database of reference genes is available. Implemented in Java, it includes both a command line version and a graphical user interface and is freely available at https://sourceforge.net/projects/lymanalyzer/.     

AutoAssemblyD: a graphical user interface system for several genome assemblers

Next-generation sequencing technologies have increased the amount of biological data generated. Thus, bioinformatics has become important because new methods and algorithms are necessary to manipulate and process such data. However, certain challenges have emerged, such as genome assembly using short reads and high-throughput platforms. In this context, several algorithms have been developed, such as Velvet, Abyss, Euler-SR, Mira, Edna, Maq, SHRiMP, Newbler, ALLPATHS, Bowtie and BWA. However, most such assemblers do not have a graphical interface, which makes their use difficult for users without computing experience given the complexity of the assembler syntax. Thus, to make the operation of such assemblers accessible to users without a computing background, we developed AutoAssemblyD, which is a graphical tool for genome assembly submission and remote management by multiple assemblers through XML templates.

Availability

AssemblyD is freely available at https://sourceforge.net/projects/autoassemblyd. It requires Sun jdk 6 or higher.     

FineSplice,enhanced splice junction detection and quantification: a novel pipeline based on the assessment of diverse RNA-Seq alignment solutions

Alternative splicing is the main mechanism governing protein diversity. The recent developments in RNA-Seq technology have enabled the study of the global impact and regulation of this biological process. However, the lack of standardized protocols constitutes a major bottleneck in the analysis of alternative splicing. This is particularly important for the identification of exon–exon junctions, which is a critical step in any analysis workflow. Here we performed a systematic benchmarking of alignment tools to dissect the impact of design and method on the mapping, detection and quantification of splice junctions from multi-exon reads. Accordingly, we devised a novel pipeline based on TopHat2 combined with a splice junction detection algorithm, which we have named FineSplice. FineSplice allows effective elimination of spurious junction hits arising from artefactual alignments, achieving up to 99% precision in both real and simulated data sets and yielding superior F₁ scores under most tested conditions. The proposed strategy conjugates an efficient mapping solution with a semi-supervised anomaly detection scheme to filter out false positives and allows reliable estimation of expressed junctions from the alignment output. Ultimately this provides more accurate information to identify meaningful splicing patterns. FineSplice is freely available at https://sourceforge.net/p/finesplice/.     

DNA-COMPACT: DNA COMpression Based on a Pattern-Aware Contextual Modeling Technique

Genome data are becoming increasingly important for modern medicine. As the rate of increase in DNA sequencing outstrips the rate of increase in disk storage capacity, the storage and data transferring of large genome data are becoming important concerns for biomedical researchers. We propose a two-pass lossless genome compression algorithm, which highlights the synthesis of complementary contextual models, to improve the compression performance. The proposed framework could handle genome compression with and without reference sequences, and demonstrated performance advantages over best existing algorithms. The method for reference-free compression led to bit rates of 1.720 and 1.838 bits per base for bacteria and yeast, which were approximately 3.7% and 2.6% better than the state-of-the-art algorithms. Regarding performance with reference, we tested on the first Korean personal genome sequence data set, and our proposed method demonstrated a 189-fold compression rate, reducing the raw file size from 2986.8 MB to 15.8 MB at a comparable decompression cost with existing algorithms. DNAcompact is freely available at https://sourceforge.net/projects/dnacompact/for research purpose.     

ArrayPlex: distributed,interactive and programmatic access to genome sequence,annotation, ontology,and analytical toolsets

ArrayPlex is a software package that centrally provides a large number of flexible toolsets useful for functional genomics, including microarray data storage, quality assessments, data visualization, gene annotation retrieval, statistical tests, genomic sequence retrieval and motif analysis. It uses a client-server architecture based on open source components, provides graphical, command-line, and programmatic access to all needed resources, and is extensible by virtue of a documented application programming interface. ArrayPlex is available at http://sourceforge.net/projects/arrayplex/.     

qpure: A Tool to Estimate Tumor Cellularity from Genome-Wide Single-Nucleotide Polymorphism Profiles

Tumour cellularity, the relative proportion of tumour and normal cells in a sample, affects the sensitivity of mutation detection, copy number analysis, cancer gene expression and methylation profiling. Tumour cellularity is traditionally estimated by pathological review of sectioned specimens; however this method is both subjective and prone to error due to heterogeneity within lesions and cellularity differences between the sample viewed during pathological review and tissue used for research purposes. In this paper we describe a statistical model to estimate tumour cellularity from SNP array profiles of paired tumour and normal samples using shifts in SNP allele frequency at regions of loss of heterozygosity (LOH) in the tumour. We also provide qpure, a software implementation of the method. Our experiments showed that there is a medium correlation 0.42 (-value = 0.0001) between tumor cellularity estimated by qpure and pathology review. Interestingly there is a high correlation 0.87 (-value 2.2e-16) between cellularity estimates by qpure and deep Ion Torrent sequencing of known somatic KRAS mutations; and a weaker correlation 0.32 (-value = 0.004) between IonTorrent sequencing and pathology review. This suggests that qpure may be a more accurate predictor of tumour cellularity than pathology review. qpure can be downloaded from https://sourceforge.net/projects/qpure/.     

Metagenomic Profiling of Known and Unknown Microbes with MicrobeGPS

Microbial community profiling identifies and quantifies organisms in metagenomic sequencing data using either reference based or unsupervised approaches. However, current reference based profiling methods only report the presence and abundance of single reference genomes that are available in databases. Since only a small fraction of environmental genomes is represented in genomic databases, these approaches entail the risk of false identifications and often suggest a higher precision than justified by the data. Therefore, we developed MicrobeGPS, a novel metagenomic profiling approach that overcomes these limitations. MicrobeGPS is the first method that identifies microbiota in the sample and estimates their genomic distances to known reference genomes. With this strategy, MicrobeGPS identifies organisms down to the strain level and highlights possibly inaccurate identifications when the correct reference genome is missing. We demonstrate on three metagenomic datasets with different origin that our approach successfully avoids misleading interpretation of results and additionally provides more accurate results than current profiling methods. Our results indicate that MicrobeGPS can enable reference based taxonomic profiling of complex and less characterized microbial communities. MicrobeGPS is open source and available from https://sourceforge.net/projects/microbegps/ as source code and binary distribution for Windows and Linux operating systems.