Integrative Multi-omics Module Network Inference with Lemon-Tree

Module network inference is an established statistical method to reconstruct co-expression modules and their upstream regulatory programs from integrated multi-omics datasets measuring the activity levels of various cellular components across different individuals, experimental conditions or time points of a dynamic process. We have developed Lemon-Tree, an open-source, platform-independent, modular, extensible software package implementing state-of-the-art ensemble methods for module network inference. We benchmarked Lemon-Tree using large-scale tumor datasets and showed that Lemon-Tree algorithms compare favorably with state-of-the-art module network inference software. We also analyzed a large dataset of somatic copy-number alterations and gene expression levels measured in glioblastoma samples from The Cancer Genome Atlas and found that Lemon-Tree correctly identifies known glioblastoma oncogenes and tumor suppressors as master regulators in the inferred module network. Novel candidate driver genes predicted by Lemon-Tree were validated using tumor pathway and survival analyses. Lemon-Tree is available from http://lemon-tree.googlecode.com under the GNU General Public License version 2.0.

This is a PLOS Computational Biology Software Article

     

Accurate human microsatellite genotypes from high-throughput resequencing data using informed error profiles

Repetitive sequences are biologically and clinically important because they can influence traits and disease, but repeats are challenging to analyse using short-read sequencing technology. We present a tool for genotyping microsatellite repeats called RepeatSeq, which uses Bayesian model selection guided by an empirically derived error model that incorporates sequence and read properties. Next, we apply RepeatSeq to high-coverage genomes from the 1000 Genomes Project to evaluate performance and accuracy. The software uses common formats, such as VCF, for compatibility with existing genome analysis pipelines. Source code and binaries are available at http://github.com/adaptivegenome/repeatseq.     

ClonalFrameML: Efficient Inference of Recombination in Whole Bacterial Genomes

Recombination is an important evolutionary force in bacteria, but it remains challenging to reconstruct the imports that occurred in the ancestry of a genomic sample. Here we present ClonalFrameML, which uses maximum likelihood inference to simultaneously detect recombination in bacterial genomes and account for it in phylogenetic reconstruction. ClonalFrameML can analyse hundreds of genomes in a matter of hours, and we demonstrate its usefulness on simulated and real datasets. We find evidence for recombination hotspots associated with mobile elements in Clostridium difficile ST6 and a previously undescribed 310kb chromosomal replacement in Staphylococcus aureus ST582. ClonalFrameML is freely available at http://clonalframeml.googlecode.com/.     

Sequence Maneuverer: tool for sequence extraction from genomes

The availability of genomic sequences of many organisms has opened new challenges in many aspects particularly in terms of genome analysis. Sequence extraction is a vital step and many tools have been developed to solve this issue. These tools are available publically but have limitations with reference to the sequence extraction, length of the sequence to be extracted, organism specificity and lack of user friendly interface. We have developed a java based software package having three modules which can be used independently or sequentially. The tool efficiently extracts sequences from large datasets with few simple steps. It can efficiently extract multiple sequences of any desired length from a genome of any organism. The results are crosschecked by published data.

Availability

URL 1: http://ww3.comsats.edu.pk/bio/ResearchProjects.aspxURL 2: http://ww3.comsats.edu.pk/bio/SequenceManeuverer.aspx     

CREST – Classification Resources for Environmental Sequence Tags

Sequencing of taxonomic or phylogenetic markers is becoming a fast and efficient method for studying environmental microbial communities. This has resulted in a steadily growing collection of marker sequences, most notably of the small-subunit (SSU) ribosomal RNA gene, and an increased understanding of microbial phylogeny, diversity and community composition patterns. However, to utilize these large datasets together with new sequencing technologies, a reliable and flexible system for taxonomic classification is critical. We developed CREST (Classification Resources for Environmental Sequence Tags), a set of resources and tools for generating and utilizing custom taxonomies and reference datasets for classification of environmental sequences. CREST uses an alignment-based classification method with the lowest common ancestor algorithm. It also uses explicit rank similarity criteria to reduce false positives and identify novel taxa. We implemented this method in a web server, a command line tool and the graphical user interfaced program MEGAN. Further, we provide the SSU rRNA reference database and taxonomy SilvaMod, derived from the publicly available SILVA SSURef, for classification of sequences from bacteria, archaea and eukaryotes. Using cross-validation and environmental datasets, we compared the performance of CREST and SilvaMod to the RDP Classifier. We also utilized Greengenes as a reference database, both with CREST and the RDP Classifier. These analyses indicate that CREST performs better than alignment-free methods with higher recall rate (sensitivity) as well as precision, and with the ability to accurately identify most sequences from novel taxa. Classification using SilvaMod performed better than with Greengenes, particularly when applied to environmental sequences. CREST is freely available under a GNU General Public License (v3) from http://apps.cbu.uib.no/crest and http://lcaclassifier.googlecode.com.     

Skip the alignment: degenerate, multiplex primer and probe design using K-mer matching instead of alignments

PriMux is a new software package for selecting multiplex compatible, degenerate primers and probes to detect diverse targets such as viruses. It requires no multiple sequence alignment, instead applying k-mer algorithms, hence it scales well for large target sets and saves user effort from curating sequences into alignable groups. PriMux has the capability to predict degenerate primers as well as probes suitable for TaqMan or other primer/probe triplet assay formats, or simply probes for microarray or other single-oligo assay formats. PriMux employs suffix array methods for efficient calculations on oligos 10-∼100 nt in length. TaqMan® primers and probes for each segment of Rift Valley fever virus were designed using PriMux, and lab testing comparing signatures designed using PriMux versus those designed using traditional methods demonstrated equivalent or better sensitivity for the PriMux-designed signatures compared to traditional signatures. In addition, we used PriMux to design TaqMan® primers and probes for unalignable or poorly alignable groups of targets: that is, all segments of Rift Valley fever virus analyzed as a single target set of 198 sequences, or all 2863 Dengue virus genomes for all four serotypes available at the time of our analysis. The PriMux software is available as open source from http://sourceforge.net/projects/PriMux.     

Inference of Population Splits and Mixtures from Genome-Wide Allele Frequency Data

Many aspects of the historical relationships between populations in a species are reflected in genetic data. Inferring these relationships from genetic data, however, remains a challenging task. In this paper, we present a statistical model for inferring the patterns of population splits and mixtures in multiple populations. In our model, the sampled populations in a species are related to their common ancestor through a graph of ancestral populations. Using genome-wide allele frequency data and a Gaussian approximation to genetic drift, we infer the structure of this graph. We applied this method to a set of 55 human populations and a set of 82 dog breeds and wild canids. In both species, we show that a simple bifurcating tree does not fully describe the data; in contrast, we infer many migration events. While some of the migration events that we find have been detected previously, many have not. For example, in the human data, we infer that Cambodians trace approximately 16% of their ancestry to a population ancestral to other extant East Asian populations. In the dog data, we infer that both the boxer and basenji trace a considerable fraction of their ancestry (9% and 25%, respectively) to wolves subsequent to domestication and that East Asian toy breeds (the Shih Tzu and the Pekingese) result from admixture between modern toy breeds and “ancient” Asian breeds. Software implementing the model described here, called TreeMix, is available at http://treemix.googlecode.com.     

An enigmatic satellite

McLaughlin and Chadwick describe an X-linked tandem repeat that is transcribed, conserved and defies X inactivation. Is it selfish, functional or just an oddity?See research article: http://genomebiology.com/2011/12/4/R37     

HaploSearch: a tool for haplotype-sequence two-way transformation

Comparison of available mitochondrial DNA data is some times hindered by the data presentation format. HaploSearch is a simple tool for transforming DNA sequences into haplotype data and vice versa, speeding up the manipulation of large datasets. Although designed for mitochondrial DNA, HaploSearch could be used with any kind of DNA type. HaploSearch program, detailed software instructions and example files are freely available on the web http://www.haplosite.com/haplosearch/.     

SNUFER: A software for localization and presentation of single nucleotide polymorphisms using a Clustal multiple sequence alignment output file

SNUFER is a software for the automatic localization and generation of tables used for the presentation of single nucleotide polymorphisms (SNPs). After input of a fasta file containing the sequences to be analyzed, a multiple sequence alignment is generated using ClustalW ran inside SNUFER. The ClustalW output file is then used to generate a table which displays the SNPs detected in the aligned sequences and their degree of similarity. This table can be exported to Microsoft Word, Microsoft Excel or as a single text file, permitting further editing for publication. The software was written using Delphi 7 for programming and FireBird 2.0 for sequence database management. It is freely available for noncommercial use and can be downloaded from http://www.heranza.com.br/bioinformatica2.htm.     

PHProteomicDB： A Module for Two-dimensional Gel Electrophoresis Database Creation on Personal Web Sites

PHProteomicDB is a PHP-written module to help researchers in proteomics to share two-dimenslonal gel electrophoresis data using personal web sites. No technical or PHP knowledge is necessary except a few basics about web site management. PHProteomicDB has a user-friendly administration interface to enter and update data. It creates web pages on the fly displaying gel characteristics, gel pictures, and numbered gel spots with their related identifications pointing to their reference pages in protein databanks. The module is freely available at http：//www.huvec.com/index.php3？rub=Download.     

SEWAL: an open-source platform for next-generation sequence analysis and visualization

Next-generation DNA sequencing platforms provide exciting new possibilities for in vitro genetic analysis of functional nucleic acids. However, the size of the resulting data sets presents computational and analytical challenges. We present an open-source software package that employs a locality-sensitive hashing algorithm to enumerate all unique sequences in an entire Illumina sequencing run (∼10⁸ sequences). The algorithm results in quasilinear time processing of entire Illumina lanes (∼10⁷ sequences) on a desktop computer in minutes. To facilitate visual analysis of sequencing data, the software produces three-dimensional scatter plots similar in concept to Sewall Wright and John Maynard Smith’s adaptive or fitness landscape. The software also contains functions that are particularly useful for doped selections such as mutation frequency analysis, information content calculation, multivariate statistical functions (including principal component analysis), sequence distance metrics, sequence searches and sequence comparisons across multiple Illumina data sets. Source code, executable files and links to sample data sets are available at http://www.sourceforge.net/projects/sewal.     

GMATo: A novel tool for the identification and analysis of microsatellites in large genomes

Simple Sequence Repeats (SSR), also called microsatellite, is very useful for genetic marker development and genome application. The increasing whole sequences of more and more large genomes provide sources for SSR mining in silico. However currently existing SSR mining tools can’t process large genomes efficiently and generate no or poor statistics. Genome-wide Microsatellite Analyzing Tool (GMATo) is a novel tool for SSR mining and statistics at genome aspects. It is faster and more accurate than existed tools SSR Locator and MISA. If a DNA sequence was too long, it was chunked to short segments at several Mb followed by motifs generation and searching using Perl powerful pattern match function. Matched loci data from each chunk were then merged to produce final SSR loci information. Only one input file is required which contains raw fasta DNA sequences and output files in tabular format list all SSR loci information and statistical distribution at four classifications. GMATo was programmed in Java and Perl with both graphic and command line interface, either executable alone in platform independent manner with full parameters control. Software GMATo is a powerful tool for complete SSR characterization in genomes at any size.

Availability

The soft GMATo is freely available at http://sourceforge.net/projects/gmato/files/?source=navbar or on contact     

Report on the 2nd Annual Infinium Humanmethylation450 Array Workshop

The Illumina Infinium HumanMethylation450 BeadChip – the successor to their hugely popular HumanMethylation27 BeadChip – is arguably the most prevalent platform for large-scale studies of DNA methylome analysis. After the success of last year’s meeting¹ that discussed initial analysis strategies for this then-new platform, this year’s meeting (held at Queen Mary, University of London) included the presentation of now established pipelines and normalization methods for data analysis, as well as some exciting tools for down-stream analysis. The importance of defining cell composition was a new topic mentioned by most speakers. The epigenome varies between cell types and insuring that methylation differences are related to sample treatment and not a differing cell population is essential. The meeting was attended by 215 computational and bench scientists from 18 countries. There were 11 speakers, a small poster session, and a discussion session. Talks were recorded and are now freely available at http://www.illumina.com/applications/epigenetics/array-based_methylation_analysis/methylation-array-analysis-education.ilmn     

Timber! Felling the loblolly pine genome

Conventional short read sequences derived from haploid DNA were extended into long super-reads enabling assembly of the massive 22 Gbp loblolly pine, Pinus taeda, genome.See related research http://genomebiology.com/2014/15/3/R59     

jmzTab: A Java interface to the mzTab data standard

mzTab is the most recent standard format developed by the Proteomics Standards Initiative. mzTab is a flexible tab‐delimited file that can capture identification and quantification results coming from MS‐based proteomics and metabolomics approaches. We here present an open‐source Java application programming interface for mzTab called jmzTab. The software allows the efficient processing of mzTab files, providing read and write capabilities, and is designed to be embedded in other software packages. The second key feature of the jmzTab model is that it provides a flexible framework to maintain the logical integrity between the metadata and the table‐based sections in the mzTab files. In this article, as two example implementations, we also describe two stand‐alone tools that can be used to validate mzTab files and to convert PRIDE XML files to mzTab. The library is freely available at http://mztab.googlecode.com .