BOL: Related items

Genome Workbench 2.10.7

Gudiya Pal — Fri, 01 Jul 2016 12:09:59 -0500

Genome Workbench 2.10.7 is here! New features include added support for local custom BLAST databases and improvements to Tree View.

For the full list of features, improvements and fixes, see the release notes:https://ncbi.nlm.nih.gov/tools/gbench/releasenotes

New Features

BLAST Tool: added support for local custom BLAST databases
Graphical Sequence View: added log scaling option for graph tracks
Generic Table View: new tutorial added

Bug Fixes and Improvements

Project Tree View: Genomic Collections/Assemblies now show accessions, not just names
Tree View: layout updated to better accommodate nodes of different sizes
Table Import Dialog (MacOS): fixed issue with table visibility
Fixed bug where different molecules IDs in GenBank could resolve to the same sequence
Graphical Sequence View: fixed issue where sequence track was not shown for some sequences
Graphical Sequence View: fixed protein coloration methods
Graphical Sequence View: improved rendering of Markers to better indicate boundaries and produce higher quality PDF images
Create Gene Model tool: fixed scenario when gene model tool failed with local sequences
Search View: ORF Finder – fixed incorrect protein lengths
Fixed bug with not opening project file (.gbp) on a click
Fixed issues in GVF import
Fixed BLAST Search tool against NCBI databases not working
Fixed tblastn (protein BLAST) not working in standalone mode
Fixed GTF export failure

Scarpa

Poonam Mahapatra — Wed, 13 Jul 2016 07:59:25 -0500

Scarpa is a stand-alone scaffolding tool for NGS data. It can be used together with virtually any genome assembler and any NGS read mapper that supports SAM format. Other features include support for multiple libraries and an option to estimate insert size distributions from data. Scarpa is available free of charge for academic and commercial use under the GNU General Public License (GPL).

See the user manual or the paper for more information about Scarpa. Click here for the supplementary material.

Address of the bookmark: http://compbio.cs.toronto.edu/hapsembler/scarpa.html

VAGUE:Velvet Assembler Graphical Front End

Jit — Fri, 24 Feb 2017 08:56:49 -0600

VAGUE is a vague acronym for "Velvet Assembler Graphical Front End", which means it is a GUI for the Velvet de novo assembler. The command line version of Velvet can be complicated for beginners to use, but VAGUE makes it clear and simple

More at http://www.vicbioinformatics.com/software.vague.shtml

Address of the bookmark: http://www.vicbioinformatics.com/software.vague.shtml

RepeatModeler

Jit — Thu, 18 Aug 2016 09:57:15 -0500

RepeatModeler is a de-novo repeat family identification and modeling package. At the heart of RepeatModeler are two de-novo repeat finding programs ( RECON and RepeatScout ) which employ complementary computational methods for identifying repeat element boundaries and family relationships from sequence data. RepeatModeler assists in automating the runs of RECON and RepeatScout given a genomic database and uses the output to build, refine and classify consensus models of putative interspersed repeats.

Address of the bookmark: http://www.repeatmasker.org/RepeatModeler.html

TGNet

Shruti Paniwala — Wed, 24 Aug 2016 05:36:36 -0500

Recent technological progress has greatly facilitated de novo genome sequencing. However, de novo assemblies consist in many pieces of contiguous sequence (contigs) arranged in thousands of scaffolds instead of small numbers of chromosomes. Confirming and improving the quality of such assemblies is critical for subsequent analysis.

Visualization and quality assessment of de novo genome assemblies

Citation

This software is fully described in the paper:
Riba-Grognuz, Keller, Falquet, Xenarios & Wurm (2011) Visualization and quality assessment of de novo genome assemblies.

In brief, our scripts create Cytoscape files to visualize transcript evidence that suggests adjacency between scaffolds and contigs.

Software requirements

BLAT (tested with Standalone BLAT v. 32×1). Source Binaries .
Cytoscape (tested with versions 2.7.0, 2.8.2)
a UNIX machine (tested on Mac OS X 10.6 and CentOS 4.6)

Address of the bookmark: https://github.com/ksanao/TGNet

Useful Bioinformatics Tools

Poonam Mahapatra — Mon, 29 Aug 2016 04:08:12 -0500

Collections of few handy tools for bioinformatician

http://molbiol-tools.ca/Convert.htm

Address of the bookmark: http://molbiol-tools.ca/Convert.htm

BRAKER: pipeline for fully automated prediction of protein coding genes with GeneMark-ES/ET and AUGUSTUS in novel eukaryotic genomes

Jit — Thu, 01 Sep 2016 08:02:59 -0500

Gene finding in eukaryotic genomes is notoriously difficult to automate. The task is to design a work flow with a minimal set of tools that would reach state-of-the-art performance across a wide range of species. GeneMark-ET is a gene prediction tool that incorporates RNA-Seq data into unsupervised training and subsequently generates ab initio gene predictions. AUGUSTUS is a gene finder that usually requires supervised training and uses information from RNA-Seq reads in the prediction step. Complementary strengths of GeneMark-ET and AUGUSTUS provided motivation for designing a new combined tool for automatic gene prediction.

http://www.ncbi.nlm.nih.gov/pubmed/26559507

Address of the bookmark: http://bioinf.uni-greifswald.de/bioinf/braker/

NGS Tutorial

Jit — Mon, 05 Sep 2016 09:50:46 -0500

These tutorials are written for hundreds of bioinformaticians trying to cope with large volume of next-generation sequencing (NGS) data. NGS technologies brought a dramatic shift in the world of sequencing. Merely five years back, genome sequencing of higher eukaryotes used to be very expensive endeavor. To get a genome of interest sequenced, hundreds of scientists had to raise funds together by writing a joint white-paper and petitioning to various government agencies. The tasks of sequencing and assembly were handled by dedicated sequencing facilities, of which only a few existed around the globe. Naturally, the capacities at those sequencing facilities were significantly constrained from high volume of requests

Address of the bookmark: http://www.homolog.us/Tutorials/index.php

GAGE : Genome Assembly Gold-standard Evaluation

Jit — Wed, 07 Sep 2016 07:35:49 -0500

GAGE is an evaluation of the very latest large-scale genome assembly algorithms. We have organized this "bake-off" as an attempt to produce a realistic assessment of genome assembly software in a rapidly changing field of next-generation sequencing. The main results of GAGE have now been published in the journal Genome Research: GAGE: A critical evaluation of genome assemblies and assembly algorithms.

http://genome.cshlp.org/content/early/2012/01/12/gr.131383.111

Address of the bookmark: http://gage.cbcb.umd.edu/index.html

PHYMMBL

Jit — Mon, 10 Oct 2016 08:56:34 -0500

Metagenomics sequencing projects collect samples of DNA from uncharacterized environments that may contain hundreds or even thousands of species. One of the main challenges in analyzing a metagenome is phylogenetic classification of raw sequence reads into groups representing the same or similar species. Such classification is a useful prerequisite for genome assembly and for analysis of the biological diversity present in a sample. The newest sequencing technologies have simultaneously made metagenomics easier, by making the sequencing process faster, and more difficult, by producing shorter read lengths than previous technologies. Methods for classifying sequences as short as 100 base pairs (bp) have until now been relatively inaccurate, requiring metagenomics projects to use older, long-read technologies. Phymm, a new classification approach for metagenomics data which uses interpolated Markov models (IMMs) to taxonomically classify DNA sequences, can accurately classify reads as short as 100 bp. Its accuracy for short reads represents a significant leap forward over previous composition-based classification methods. PhymmBL (rhymes with "thimble"), the hybrid classifier included in this distribution which combines analysis from both Phymm and BLAST, produces even higher accuracy.

Address of the bookmark: http://www.cbcb.umd.edu/software/phymm/