BOL: Related items

sockeye

Jit — Fri, 17 Feb 2017 08:51:16 -0600

This sockeye software uses the Ensembl database project to import sequence and annotation information from several eukaryotic species. A user can additionally import their own custom sequence and annotation data. Individual annotation objects are displayed in Sockeye by using custom 3D models. Ensembl-derived and imported sequences can be analyzed by using a suite of multiple and pair-wise alignment algorithms. The results of these comparative analyses are also displayed in the 3D environment of Sockeye. By using the Java3D API to visualize genomic data in a 3D environment, we are able to compactly display cross-sequence comparisons. This provides the user with a novel platform for visualizing and comparing genomic feature organization.

Address of the bookmark: http://www.bcgsc.ca/platform/bioinfo/software/sockeye/releases/1.3

Jvarkit : Java utilities for Bioinformatics

Jit — Fri, 08 Jun 2018 09:31:55 -0500

Collection of Java tool kits for bioinformatics works: Jvarkit : Java utilities for Bioinformatics

Address of the bookmark: http://lindenb.github.io/jvarkit/

4DGenome

Jitendra Narayan — Mon, 04 Jul 2016 00:44:55 -0500

Records in 4DGenome are compiled through comprehensive literature curation of experimentally-derived and computationally-predicted interactions. The current release contains 4,433,071 experimentally-derived and 3,605,176 computationally-predicted interactions in 5 organisms. Experimental data cover both high throughput datasets and individiual focused studies.

All interaction data are freely available in a standardized file format. Records can be queried by genomic regions, gene names, organism, and detection technology.

Address of the bookmark: http://4dgenome.research.chop.edu/

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

Pacbio Long Reads Compatible Software and Tools

Archana Malhotra — Wed, 15 Mar 2017 14:19:01 -0500

The following software packages are known to be compatible with PacBio® data, in addition to PacBio's own SMRT® Analysis suite. All packages are believed to be open source or freely available for non-commercial use. See the individual project sites for up-to-date license information. A separate page lists commercial software.

Know of any other open source software for PacBio data? Email us.

Software categories:

Address of the bookmark: https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software

A 3D Map of the Human Genome

Fri, 12 Dec 2014 22:27:55 -0600

Suhas Rao and Miriam Huntley (of the Aiden Lab) describe a 3D map of the human genome at kilobase resolution, revealing the principles of chromatin looping. Guest Origami Folding: Sarah Nyquist. Suhas S.P. Rao*, Miriam H. Huntley*, Neva C. Durand, Elena K. Stamenova, Ivan D. Bochkov, James T. Robinson, Adrian L. Sanborn, Ido Machol, Arina D. Omer, Eric S. Lander, Erez Lieberman Aiden. (2014). A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping. Cell.

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

LAST

Bulbul — Mon, 19 Dec 2016 14:07:53 -0600

LAST can:

Handle big sequence data, e.g:
- Compare two vertebrate genomes
- Align billions of DNA reads to a genome
Indicate the reliability of each aligned column.
Use sequence quality data properly.
Compare DNA to proteins, with frameshifts.
Compare PSSMs to sequences
Calculate the likelihood of chance similarities between random sequences.
Do split and spliced alignment.
Train alignment parameters for unusual kinds of sequence (e.g. nanopore).

Address of the bookmark: http://last.cbrc.jp/

pyScaf

Bulbul — Mon, 19 Dec 2016 14:20:33 -0600

pyScaf orders contigs from genome assemblies utilising several types of information:

paired-end (PE) and/or mate-pair libraries (NGS-based mode)
long reads (NGS-based mode)
synteny to the genome of some related species (reference-based mode)

Scaffolding

In reference-based mode, pyScaf uses synteny to the genome of closely related species in order to order contigs and estimate distances between adjacent contigs.

Contigs are aligned globally (end-to-end) onto reference chromosomes, ignoring:

matches not satisfying cut-offs (--identity and --overlap)
suboptimal matches (only best match of each query to reference is kept)
and removing overlapping matches on reference.

In preliminary tests, pyScaf performed superbly on simulated heterozygous genomes based on C. parapsilosis (13 Mb; CANPA) and A. thaliana (119 Mb; ARATH) chromosomes, reconstructing correctly all chromosomes always for CANPA and nearly always for ARATH (Figures in dropbox, CANPA table, ARATH table).
Runs took ~0.5 min for CANPA on 4 CPUs and ~2 min for ARATH on 16 CPUs.

Important remarks:

Reduce your assembly before (fasta2homozygous.py) as any redundancy will likely break the synteny.
pyScaf works better with contigs than scaffolds, as scaffolds are often affected by mis-assemblies (no de novo assembler / scaffolder is perfect...), which breaks synteny.
pyScaf works very well if divergence between reference genome and assembled contigs is below 20% at nucleotide level.
pyScaf deals with large rearrangements ie. deletions, insertion, inversions, translocations. Note however, this is experimental implementation!
Consider closing gaps after scaffolding.

Address of the bookmark: https://github.com/lpryszcz/pyScaf

GenomeComp

Jit — Fri, 17 Feb 2017 08:38:32 -0600

GenomeComp is a tool for summarizing, parsing and visualizing the genome wide sequence comparison results derived from voluminous BLAST textual output, so as to locate the rearrangements, insertions or deletions of genome segments between species or strains.

It can be easily used to compare, parsing and visualize large genomic sequences, especially closely related genomes such as inter-species or inter-strains. In addition, it can also show other sequence features like repeat sequence distributions in one whole-genome DNA sequence by comparing the genome to itself.

It is a stand-alone graphical user interface (GUI) program which runs on Linux, Unix, Mac OS X (tested on version 10.2.4 only) and Microsoft Windows platforms and is written in Perl/Tk.

Address of the bookmark: http://www.mgc.ac.cn/GenomeComp/