BOL: Related items

Graph Genome Suite

Jit — Fri, 28 Oct 2016 07:59:54 -0500

Seven Bridges is the biomedical data analysis company accelerating breakthroughs in genomics research for cancer, drug development and precision medicine. We build self-improving systems to analyze millions of genomes, including the Graph Genome Suite — the most advanced population genomics tools in the world.

Address of the bookmark: https://www.sbgenomics.com/graph/

MitoZ: a toolkit for animal mitochondrial genome assembly, annotation and visualization

Jit — Fri, 24 Jan 2020 04:09:15 -0600

MitoZ is a Python3-based toolkit which aims to automatically filter pair-end raw data (fastq files), assemble genome, search for mitogenome sequences from the genome assembly result, annotate mitogenome (genbank file as result), and mitogenome visualization. MitoZ is available from https://github.com/linzhi2013/MitoZ.

https://academic.oup.com/nar/article/47/11/e63/5377471

Address of the bookmark: https://github.com/linzhi2013/MitoZ

LINKS

Jit — Fri, 04 Nov 2016 06:19:01 -0500

LINKS is a genomics application for scaffolding genome assemblies with long reads, such as those produced by Oxford Nanopore Technologies Ltd. It can be used to scaffold high-quality draft genome assemblies with any long sequences (eg. ONT reads, PacBio reads, another draft genomes, etc)

Paper at https://gigascience.biomedcentral.com/articles/10.1186/s13742-015-0076-3

Address of the bookmark: https://github.com/warrenlr/LINKS/

Professor (all levels) in Bioinformatics and Computational Biology

Tue, 22 Nov 2016 05:43:38 -0600

King Abdullah University of Science and Technology (KAUST) (kaust.edu.sa) is seeking a highly motivated and skilled faculty member for the Bioinformatics track whose research focuses on development of methods and tools for Bioinformatics and Computational Biology.
KAUST is an international, graduate-level research university dedicated to advancing science and technology through interdisciplinary research, education, and innovation. Located on the shores of the Red Sea in Saudi Arabia, KAUST offers superb research facilities, generous assured research funding, and internationally competitive salaries, attracting top international faculty, scientists, engineers, and students to conduct fundamental and goal-oriented research to address the world’s pressing scientific and technological challenges in the areas of food, water, energy, and the environment.
The successful applicant is expected to develop world-leading research in domain of bioinformatics/computational biology with focus on development of novel computational approaches for efficient and accurate methods of analyzing biological phenomena at molecular level. The faculty member will be part of the Computational Bioscience Research Center (CBRC) within the Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division. The position will remain open until filled.

Requirements:

PhD or equivalent in a Computer Science, Mathematics or Engineering discipline. Candidates should be well-established within the research field relevant to the position grade. They should demonstrate original research and experience at the highest international level.

Responsibilities and tasks:

Research competence in the following areas is preferred:
Analysis of next generation sequencing (NGS) and other ‘omics’ data (e.g. CAGE, ChIP-Seq, DHS, RNA-Seq, Ribo-Seq, proteomic, metabolic and NMR spectra, etc.).
Signaling, regulatory and metabolic pathways analysis.
Development of tools (web-based and standalone) suited for efficient computational biology/bioinformatics.

Visit cemse.kaust.edu.sa to apply.

EXCAVATOR2tool

Bulbul — Wed, 30 Nov 2016 04:09:19 -0600

EXCAVATOR2 is a collection of bash, R and Fortran scripts and codes that analyses Whole Exome Sequencing (WES) data to identify CNVs. EXCAVATOR2 enhances the identification of all genomic CNVs, both overlapping and non-overlapping targeted exons by integrating the analysis of In-targets and Off- targets reads. Specifically, it improves the precision of calling CNVs overlapping targeted exons from WES data and enlarges the spectrum of detectable CNVs to off-target events.
EXCAVATOR2 can be effectively employed for the identification of CNVs in small as well as large-scale re-sequencing population and cancer studies. Lastly, it’s of particular interest that all WES experiments can be re-analysed using our method with the beneficial effect to identify novelCNVs in extra-exonic regions by having the full-genome CN profile.

Address of the bookmark: https://sourceforge.net/projects/excavator2tool/

Structural variation: the hidden genomic treasure

Jit — Sat, 10 Dec 2016 16:19:09 -0600

Genome re-sequencing projects have revealed substantial amounts of genetic variation between individuals extending beyond single nucleotide polymorphisms (SNPs) and short indels. Structural Variations (SVs) and Copy Number Variations (CNVs) are a major source of genomic variation. However, compared to SNPs, accurate detection, genotyping and understanding of CNVs is lagging behind due to much greater analytical challenges related to SV/CNV detection and analysis. In our lab we analyse SVs/CNVs using high-throughput sequencing and different analytical approaches. The most‐studied structural variants are copy number variations (CNVs) which can be generated by several different mechanisms including non‐allelic homologous recombination, non‐homologous end‐joining and deoxyribonucleic acid (DNA) replication‐related fork stalling and template switching. CNVs are closely related to segmental duplications (SDs): SDs can stimulate the formation of CNVs and themselves started out as CNVs, but became fixed in a species. Structural variation can be neutral but has also influenced our phenotypic evolution, for example our susceptibility to disease and our ability to digest certain types of food. Our understanding of the extent of structural variation is increasing rapidly, but it will be much more difficult to understand its phenotypic consequences.

Structural variants (SVs) such as deletions, insertions, duplications, inversions and translocations litter genomes and are often associated with gene expression changes and severe phenotypes (ie. genetic diseases in humans). Recent studies on the functional aspects of different types of SVs have unveiled several cases of adaptive evolution. For example, inversions have been associated with ecological adaptations and may facilitate speciation. Due to their prevalent nature, SVs arguably have a large impact on genome evolution and should not be neglected when studying the genetics of adaptation and speciation. SVs were classically defined as chromosomal rearrangements larger than 1kb, but due to a higher resolution of new detection methods, smaller variants (between 50 and 1000 base pairs) can now be accurately assessed. Besides various methods of detection in next generation sequencing data (paired end mapping, split reads, and depth of coverage), array-based approaches have proven to be particularly useful for detecting copy number variations (CNVs). These technologies have enabled researchers to catalog a wide spectrum of SVs in many organisms and infer the effects of selection shaping their evolutionary trajectories.

Structure variation sequencing signature (Source: NatRev Genetics)

Related tools, databases and publications are listed below. If you know any interesing papers, please let us know in comment section:

Key concepts

Structural variation includes balanced variants such as inversions and translocations, and unbalanced ones such as duplications and deletions (copy number variations or CNVs).

Structural variants can arise by several mechanisms, including nonallelic homologous recombination (NAHR), nonhomologous end‐joining (NHEJ) and DNA replication‐based fork stalling and template switching (FoSTeS).

CNV is closely linked to segmental duplication, but is not exactly the same. Segmental duplications can stimulate CNV formation by NAHR, and themselves arise from CNVs that have become fixed.

Segmental duplications did not appear uniformly during the evolution of the Great Ape species, but rather during a burst of activity around the time of the divergence of gorilla from the human/chimpanzee ancestor.

Duplicated genes play a critical role in the evolution of a genome as they act as ‘spare parts’ than can evolve to perform new or more specialized functions.

Effects of structural variation on gene expression can be identified but only a few examples of the consequences for species biology have been documented.

Tools

CNVnatora tool for CNV discovery and genotyping from depth of read mapping.2011a,2011b

AGEa tools that implements an algorithm for optimal alignment of sequences with SVs.2011

BreakSeqa pipeline for annotation, classification and analysis of SVs at single nucleotide resolution.2010

PEMera computational and simulation framework for discovering SVs by paired-end read mapping.2009,2007

GASV https://code.google.com/archive/p/gasv/

PAIROSCOPE http://pairoscope.sourceforge.net/

SVDetect http://svdetect.sourceforge.net/Site/Home.html

BreakPtr, discovery of unbalanced structural variants (copy-number variants) with tiling microarrays Link

R Package https://www.bioconductor.org/help/course-materials/2010/EMBL2010/Practical-4-StructuralVariants.pdf

BreakSeq, structural variant genotyping using split reads Link

CopySeq, genotyping of unbalanced structural variants (copy-number variants) using read-depth Link

DELLY2, integrated structural variant discovery, genotyping and visualization in deep sequencing data Link

PEMer, structural variant discovery in 454 sequencing data by paired-end mapping Link

TIGER, transduction inference in germline genomes using short read data Link

MANTA https://github.com/Illumina/manta

SV-Bay https://github.com/InstitutCurie/SV-Bay

BreakDancer http://breakdancer.sourceforge.net/

Variation Hunter http://compbio.cs.sfu.ca/software-variation-hunter

Lumpy https://github.com/arq5x/lumpy-sv

ForestSV http://sebatlab.ucsd.edu/index.php/software-data

PBSuites for long reads https://sourceforge.net/projects/pb-jelly/

Visualization

The SV visualization tool: http://genomesavant.com/savant/

InGAP-SV (http://ingap.sourceforge.net/) that is nice tools for both detection and visualisation of severals kind of structural variations (Large insertions, translocation, deletion, inversions....)

Tools table: http://www.nature.com/nbt/journal/v29/n8/fig_tab/nbt.1904_T2.html

Variation Viewer https://www.ncbi.nlm.nih.gov/variation/view/

Papers

http://www.nature.com/nmeth/journal/v9/n2/full/nmeth.1858.html

http://journal.frontiersin.org/researchtopic/1412/structural-variations-in-genomes-ecological-and-evolutionary-implications

http://www.mi.fu-berlin.de/wiki/pub/ABI/GenomicsLecture10Materials/structural-variation.pdf

http://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-015-1479-3

https://www.ncbi.nlm.nih.gov/dbvar/content/overview/

http://www.nature.com/subjects/structural-variation

https://eichlerlab.gs.washington.edu/news/NatMeth_Feb2012.pdf

https://www.ncbi.nlm.nih.gov/pubmed/19477992 ***

https://www.ncbi.nlm.nih.gov/pubmed/22452995

http://biorxiv.org/content/early/2016/09/06/073833

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4479793/

http://www.nature.com/articles/srep18501

http://www.genetics.org/content/202/1/351

http://www.cs.cmu.edu/~sssykim/teaching/s13/slides/Lecture_SVI.pdf

https://www.omicsonline.org/open-access/structural-variation-detection-from-next-generation-sequencing-2469-9853-S1-007.php?aid=69055

http://schatzlab.cshl.edu/presentations/2016/2016.01.12.PAG.Structural%20Variations.pdf

YAHA

Jit — Fri, 20 Jan 2017 05:38:05 -0600

YAHA, a fast and flexible hash-based aligner. YAHA is as fast and accurate as BWA-SW at finding the single best alignment per query and is dramatically faster and more sensitive than both SSAHA2 and MegaBLAST at finding all possible alignments. Unlike other aligners that report all, or one, alignment per query, or that use simple heuristics to select alignments, YAHA uses a directed acyclic graph to find the optimal set of alignments that cover a query using a biologically relevant breakpoint penalty. YAHA can also report multiple mappings per defined segment of the query. We show that YAHA detects more breakpoints in less time than BWA-SW across all SV classes, and especially excels at complex SVs comprising multiple breakpoints.

Availability: YAHA is currently supported on 64-bit Linux systems. Binaries and sample data are freely available for download from http://faculty.virginia.edu/irahall/YAHA.

Contact:

http://genome.wustl.edu/people/groups/detail/hall-lab/

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3463118/

REAPR: a universal tool for genome assembly evaluation

Jitendra Prajapati — Wed, 06 Apr 2016 18:26:31 -0500

REAPR is a tool that evaluates the accuracy of a genome assembly using mapped paired end reads, without the use of a reference genome for comparison. It can be used in any stage of an assembly pipeline to automatically break incorrect scaffolds and flag other errors in an assembly for manual inspection. It reports mis-assemblies and other warnings, and produces a new broken assembly based on the error calls.

The software requires as input an assembly in FASTA format and paired reads mapped to the assembly in a BAM file. Mapping information such as the fragment coverage and insert size distribution is analysed to locate mis-assemblies. REAPR works best using mapped read pairs from a large insert library (at least 1000bp). Additionally, if a short insert Illumina library is also available, REAPR can combine this with the large insert library in order to score each base of the assembly.

http://www.sanger.ac.uk/science/tools/reapr

Address of the bookmark: https://genomebiology.biomedcentral.com/articles/10.1186/gb-2013-14-5-r47

J-Circos

Shruti Paniwala — Fri, 17 Feb 2017 09:06:54 -0600

Circos plot tool (J-Circos) that is an interactive visualization tool that can plot Circos figures, as well as being able to dynamically add data to the figure, and providing information for specific data points using mouse hover display and zoom in/out functions. J-Circos uses the Java computer language to enable it to be used on most operating systems (Windows, MacOS, Linux). Users can input data into J-Circos using flat data formats, as well as from the GUI. J-Circos will enable biologists to better study more complex chromosomal interactions and fusion transcripts that are otherwise difficult to visualize from next-generation sequencing data.

Address of the bookmark: http://www.australianprostatecentre.org/research/software/jcircos

CISA: Contig Integrator for Sequence Assembly

Neel — Thu, 15 Dec 2016 05:42:21 -0600

A plethora of algorithmic assemblers have been proposed for the de novo assembly of genomes, however, no individual assembler guarantees the optimal assembly for diverse species. Optimizing various parameters in an assembler is often performed in order to generate the most optimal assembly. However, few efforts have been pursued to take advantage of multiple assemblies to yield an assembly of high accuracy. In this study, we employ various state-of-the-art assemblers to generate different sets of contigs for bacterial genomes. A tool, named CISA, has been developed to integrate the assemblies into a hybrid set of contigs, resulting in assemblies of superior contiguity and accuracy, compared with the assemblies generated by the state-of-the-art assemblers and the hybrid assemblies merged by existing tools. This tool is implemented in Python and requires MUMmer and BLAST+ to be installed on the local machine. The source code of CISA and examples of its use are available at http://sb.nhri.org.tw/CISA/.

Address of the bookmark: http://sb.nhri.org.tw/CISA/en/CISA