BOL: Related items

CGView - Circular Genome Viewer

Jit — Mon, 19 Sep 2016 07:52:26 -0500

GView is a Java package used to display and navigate bacterial genomes. GView is useful for producing high-quality genome maps for use in publications and websites, or as a visualization tool in a sequence annotation pipeline. Users can interact with the genome using a powerful pan-and-zoom interface, or GView can write static images of a genome to a file. GView can draw a genome using either circular or linear layouts. For examples of some of the images GView can produce, see the Image Gallery. GView is a re-write of CGView, a circular genome viewer written by Paul Stothard. The goal of GView is to provide greater user interaction, and more flexibility in how the genome map is rendered. To aid with easily configuring the display of a genome, a style editor has been included to provide an intuitive, user-friendly graphical user interface for customizing genome maps. Styling attributes such as colours or fonts for the various map elements can be adjusted in real time. Customized styles can be saved for later use or for application to other genome maps using GView's custom file format.

Address of the bookmark: http://wishart.biology.ualberta.ca/cgview/

BLAST Ring Image Generator (BRIG)

Anjana — Fri, 30 Sep 2016 09:18:50 -0500

BRIG is a free cross-platform (Windows/Mac/Unix) application that can display circular comparisons between a large number of genomes, with a focus on handling genome assembly data. The application is available at: http://sourceforge.net/projects/brig

If you have any questions or comments, post them on one of the trackers on BRIG’s SourceForge page: http://sourceforge.net/tracker/?group_id=328245.

Features:

Images show similarity between a central reference sequence and other sequences as concentric rings.
BRIG will perform all BLAST comparisons and file parsing automatically via a simple GUI.
Contig boundaries and read coverage can be displayed for draft genomes; customized graphs and annotations can be displayed.
Using a user-defined set of genes as input, BRIG can display gene presence, absence, truncation or sequence variation in a set of complete genomes, draft genomes or even raw, unassembled sequence data.
BRIG also accepts SAM-formatted read-mapping files enabling genomic regions present in unassembled sequence data from multiple samples to be compared simultaneously

Address of the bookmark: http://brig.sourceforge.net/

Nemo – A stochastic, individual-base, genetically explicit simulation platform

Jit — Sat, 01 Oct 2016 14:45:02 -0500

A recombination map has been added for all multi-locus traits. The map positions (chromosomal) for neutral markers (e.g. SNPs) and loci under selection (QTLs, deleterious mutations, DMIs) can now be specified explicitly, or set at random. The map can hold an unlimited number of loci of different types jointly, at any recombination scale (cM or lower). The effects of linkage can thus be finely explored.
A new trait coding for (Bateson-)Dobzhansky-Muller incompatibility loci. Multiple haploid or diploid pairs of incompatible loci can be spread throughout the genome and affect individual fitness.
Multi-type selection: Individual fitness can be jointly determined by different types of loci under selectinon, such as QTLs coding for quantitative traits under spatially variable selection, universally deleterious mutations, and Dobzhansky-Muller incompatibility loci.
An unlimited number of quantitative traits under different forms of selection can be modelled, based on universally pleiotropic loci with several bi- or multi-allelic models.
Spatial and temporal variation of selection on quantitative traits is possible, modelling shifts of environmental conditions over time.
The dispersal matrix describing the movement of individuals among sub-populations can be replaced by a connectivity matrix and a reduced dispersal matrix describing migration only among the connected sub-populations. This offers a substantial gain in computing time and system memory when simulating very large grids.
Input parameters' arguments may be specified in separate files. This is particularly convenient when specifying large matrices.
Many adjustments have been made for refined control of the input of parameters and data output. See updates in the manual.

Address of the bookmark: http://nemo2.sourceforge.net/index.html

BBMap help

Shruti Paniwala — Mon, 10 Oct 2016 06:29:03 -0500

BBMAP • a solution for everything

That content has been reformatted and it is being expanded to include more information.

There are common options for most BBMap suite programs and depending on the file extension the input/output format is automatically chosen/set.

Using BBMap

Mapping Nanopore reads

BBMap.sh has a length cap of 6kbp. Reads longer than this will be broken into 6kbp pieces and mapped independently.

More at https://www.biostarhandbook.com/tools/bbmap/bbmap-help.html

Address of the bookmark: https://www.biostarhandbook.com/tools/bbmap/bbmap-help.html

Ribbon !!

Jit — Fri, 21 Oct 2016 04:54:30 -0500

Visualization has played an extremely important role in the current genomic revolution to inspect and understand variants, expression patterns, evolutionary changes, and a number of other relationships. However, most of the information in read-to-reference or genome-genome alignments is lost for structural variations in the one-dimensional views of most genome browsers showing only reference coordinates. Instead, structural variations captured by long reads or assembled contigs often need more context to understand, including alignments and other genomic information from multiple chromosomes. We have addressed this problem by creating Ribbon (genomeribbon.com) an interactive online visualization tool that displays alignments along both reference and query sequences, along with any associated variant calls in the sample. This way Ribbon shows patterns in alignments of many reads across multiple chromosomes, while allowing detailed inspection of individual reads (Supplementary Note 1). For example, here we show a gene fusion in the SK-BR-3 breast cancer cell line linking the genes CYTH1 and EIF3H. While it has been found in the transcriptome previously, genome sequencing did not identify a direct chromosomal fusion between these two genes. After SMRT sequencing, Ribbon shows that there are indeed long reads that span from one gene to the other, going through not one but two variants, for the first time showing the genomic link between these two genes (Figure 1a). More gene fusions of this cancer cell line are investigated in Supplementary Note 2. Figure 1b shows another complex event in this sample made simple in Ribbon: the translocation of a 4.4 kb sequence deleted from chr19 and inserted into chr16 (Figure 1b). Thus, Ribbon enables understanding of complex variants, and it may also help in the detection of sequencing and sample preparation issues, testing of aligners and variant-callers, and rapid curation of structural variant candidates (Supplementary Note 3). In addition to SAM and BAM files with long, short, or paired-end reads, Ribbon can also load coordinate files from whole genome aligners such as MUMmer. Therefore, Ribbon can be used to test assembly algorithms or inspect the similarity between species. Supplementary Note 4 shows a comparison of gorilla and human genomes using Ribbon, highlighting major structural differences. In conclusion, Ribbon is a powerful interactive web tool for viewing complex genomic alignments.

Script at https://github.com/MariaNattestad/ribbon

Address of the bookmark: http://genomeribbon.com/

Beagle

Jit — Thu, 27 Oct 2016 11:19:00 -0500

Beagle is a software package that performs genotype calling, genotype phasing, imputation of ungenotyped markers, and identity-by-descent segment detection.

Beagle version 4.1 has a more accurate genotype phasing algorithm and a very fast and accurate genotype imputation algorithm. Version 4.1 also has several changes to the command line arguments which are described in the release notes. The "ped" argument has no effect in version 4.1. If your data contains nuclear families and you want to model the parent-offspring relationships when phasing genotypes, please use version 4.0.

If you use Beagle 4.1 in a published analysis, please report the program version and cite the appropriate article.

The citation for Beagle's phasing algorithm is:

S R Browning and B L Browning (2007) Rapid and accurate haplotype phasing and missing data inference for whole genome association studies by use of localized haplotype clustering. Am J Hum Genet 81:1084-1097.doi:10.1086/521987

The citation for Beagle's genotype imputation algorithm is:

B L Browning and S R Browning (2016). Genotype imputation with millions of reference samples. Am J Hum Genet 98:116-126.doi:10.1016/j.ajhg.2015.11.020

The citation for Beagle's IBD detection algorithm is:

B L Browning and S R Browning (2013). Improving the accuracy and efficiency of identity-by-descent detection in population data. Genetics 194(2):459-71.doi:10.1534/genetics.113.150029

Address of the bookmark: http://faculty.washington.edu/browning/beagle/beagle.html

eFORGE.v1.2

Jit — Fri, 28 Oct 2016 09:06:59 -0500

The eFORGE tool provides a method to view the tissue specific regulatory component of a set of EWAS DMPs. eFORGE analysis takes a set of DMPs, such as those hits above genome-wide significance threshold in an EWAS study, and analyses whether there is enrichment for overlap of putative functional elements compared to matched background DMPs. It assesses enrichment on a per cell type basis, since functional elements are differentially active in different cell types, and hence can expose tissue-specific signals of enrichment for the given test DMP set. This can reveal the sites of action underlying the EWAS signal, and provide confirmation of the validity of the EWAS where a tissue-specific mechanism is known or expected for the phenotype. Conversely unknown tissue involvements can also be revealed.

Address of the bookmark: http://eforge.cs.ucl.ac.uk/eFORGE.v1.2/?documentation

ART: Set of Simulation Tools

Jit — Thu, 03 Nov 2016 08:28:25 -0500

ART is a set of simulation tools to generate synthetic next-generation sequencing reads. ART simulates sequencing reads by mimicking real sequencing process with empirical error models or quality profiles summarized from large recalibrated sequencing data. ART can also simulate reads using user own read error model or quality profiles. ART supports simulation of single-end, paired-end/mate-pair reads of three major commercial next-generation sequencing platforms: Illumina's Solexa, Roche's 454 and Applied Biosystems' SOLiD. ART can be used to test or benchmark a variety of method or tools for next-generation sequencing data analysis, including read alignment, de novo assembly, SNP and structure variation discovery. ART was used as a primary tool for the simulation study of the 1000 Genomes Project . ART is implemented in C++ with optimized algorithms and is highly efficient in read simulation. ART outputs reads in the FASTQ format, and alignments in the ALN format. ART can also generate alignments in the SAM alignment or UCSC BED file format. ART can be used together with genome variants simulators (e.g. VarSim) for evaluating variant calling tools or methods.

Address of the bookmark: http://www.niehs.nih.gov/research/resources/software/biostatistics/art/

R Graphs !!

Jit — Fri, 04 Nov 2016 10:48:00 -0500

The blog is a collection of script examples with example data and output plots. R produce excellent quality graphs for data analysis, science and business presentation, publications and other purposes. Self-help codes and examples are provided. Enjoy nice graphs !!

Address of the bookmark: http://rgraphgallery.blogspot.be/

Bioistats PPT

Jit — Tue, 08 Nov 2016 07:09:01 -0600

Basics concepts of Probability: The Study of Randomness

Biostatistics is the application of statistics to a wide range of topics in biology. The science of biostatistics encompasses the design of biological experiments, especially in medicine, pharmacy, agriculture and fishery; the collection, summarization, and analysis of data from those experiments; and the interpretation of, and inference from, the results. A major branch of this is medical biostatistics, which is exclusively concerned with medicine and health.