BOL: Related items

Consed--A Finishing Package (BAM File Viewer, Assembly Editor, Autofinish, Autoreport, Autoedit, and Align Reads To Reference Sequence)

Neel — Fri, 07 Feb 2020 07:16:22 -0600

Supports Illumina, 454, other Next-Gen and Sanger Reads and allows mixtures of these read types
Consed includes BamScape which can view bam files with unlimited numbers of reads. BamScape can bring up consed to edit reads and the reference sequence in targeted regions.
Consed is compatible with Newbler, Cross_match, Phrap, MIRA, Velvet and PCAP output.
Quickly takes the user to each variant site for viewing (also available as an automated report)
Overview of assembly can help detect and fix misassemblies
Editing time reduced by the program's ability to pin-point problem areas
Editing is guided by error probabilities

Address of the bookmark: http://www.phrap.org/consed/consed.html

Genobuntu: A software package containing more than 70 software and packages oriented towards NGS and genome assembly

BioStar — Tue, 11 Dec 2018 05:15:57 -0600

Genobuntu is a software package containing more than 70 software and packages oriented towards NGS. In its current version, Genobuntu supports pre assembly tools, genome assemblers as well as post assembly tools.

Commonly used biological software and example script files for different assembly pipelines have also been provided, where the example script files can be updated to suit one’s experimental needs. Genobuntu attempts to reduce the amount of time and energy needed to build software workstations and it can also act as a good teaching source for a class room setting.

https://sourceforge.net/projects/genobuntu/

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

OMTools: a software package for visualizing and processing optical mapping data

BioJoker — Fri, 29 Mar 2019 01:21:54 -0500

OMTools, an efficient and intuitive data processing and visualization suite to handle and explore large-scale optical mapping profiles. OMTools includes modules for visualization (OMView), data processing and simulation. These modules together form an accessible and convenient pipeline for optical mapping analyses.

https://github.com/TF-Chan-Lab/OMTools

Address of the bookmark: https://github.com/TF-Chan-Lab/OMTools

SOAP2 : Short Oligonucleotide Analysis Package 2

Poonam Mahapatra — Wed, 23 May 2018 10:09:22 -0500

SOAPaligner/soap2 is a member of the SOAP (Short Oligonucleotide Analysis Package). It is an updated version of SOAP software for short oligonucleotide alignment. The new program features in super fast and accurate alignment for huge amounts of short reads generated by Illumina/Solexa Genome Analyzer. Compared to soap v1, it is one order of magnitude faster. It require only 2 minutes aligning one million single-end reads onto the human reference genome. Another remarkable improvement of SOAPaligner is that it now supports a wide range of the read length. SOAPaligner benefitted in time and space efficiency by a revolution in the basic data structures and algorithms used.The core algorithms and the indexing data structures (2way-BWT) are developed by the algorithms research group of the Department of Computer Science, the University of Hong Kong (T.W. Lam, Alan Tam, Simon Wong, Edward Wu and S.M. Yiu).

Address of the bookmark: http://soap.genomics.org.cn/soapaligner.html

RAVEN: a software suite for Matlab that allows for semi-automated reconstruction of genome-scale models

Jit — Wed, 24 Oct 2018 22:38:05 -0500

The RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks) Toolbox 2 is a software suite for Matlab that allows for semi-automated reconstruction of genome-scale models (GEMs). It makes use of published models and/or KEGG, MetaCyc databases, coupled with extensive gap-filling and quality control features. The software suite also contains methods for visualizing simulation results and omics data, as well as a range of methods for performing simulations and analyzing the results. The software is a useful tool for system-wide data analysis in a metabolic context and for streamlined reconstruction of metabolic networks based on protein homology.

Address of the bookmark: https://github.com/SysBioChalmers/RAVEN

DeepVariant : an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.

Jit — Sat, 25 Jan 2020 13:28:09 -0600

DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.

DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data. DeepVariant relies on Nucleus, a library of Python and C++ code for reading and writing data in common genomics file formats (like SAM and VCF) designed for painless integration with the TensorFlow machine learning framework.

https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html

https://www.biorxiv.org/content/10.1101/092890v6

Address of the bookmark: https://github.com/google/deepvariant

Juicebox: Visualization and analysis software for Hi-C data

Jit — Fri, 21 Feb 2020 00:33:38 -0600

Juicebox is visualization software for Hi-C data. This distribution includes the source code for Juicebox, Juicer Tools, and Assembly Tools. Download Juicebox here, or use Juicebox on the web. Detailed documentation is available on the wiki. Instructions below pertain primarily to usage of command line tools and the Juicebox jar files.

Juicebox can now be used to visualize and interactively (re)assemble genomes. Check out the Juicebox Assembly Tools Module website https://aidenlab.org/assembly for more details on how to use Juicebox for assembly.

GUI at https://aidenlab.org/juicebox/

Address of the bookmark: https://github.com/aidenlab/Juicebox

EAGER

Jit — Sat, 10 Dec 2016 18:07:23 -0600

The automated reconstruction of genome sequences in ancient genome analysis is a multifaceted process.

EAGER encompasses both state-of-the-art tools for each step as well as new complementary tools tailored for ancient DNA data within a single integrated solution in an easily accessible format.

https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0918-z

Address of the bookmark: https://github.com/apeltzer/EAGER-GUI

RNA-seq Analysis Workshop Course Materials

Jit — Tue, 03 Jul 2018 08:14:14 -0500

RNAseq can be roughly divided into two "types": Reference genome-based - an assembled genome exists for a species for which an RNAseq experiment is performed. It allows reads to be aligned against the reference genome and significantly improves our ability to reconstruct transcripts. This category would obviously include humans and most model organisms but excludes the majority of truly biologically intereting species (e.g., Hyacinth macaw); Reference genome-free - no genome assembly for the species of interest is available. In this case one would need to assemble the reads into transcripts using de novo approaches. This type of RNAseq is as much of an art as well as science because assembly is heavily parameter-dependent and difficult to do well. In this lesson we will focus on the Reference genome-based type of RNA seq. http://chagall.med.cornell.edu/RNASEQcourse/

Address of the bookmark: http://chagall.med.cornell.edu/RNASEQcourse/

GWASpro: A High-Performance Genome-Wide Association Analysis Server

Rahul Nayak — Fri, 07 Dec 2018 08:04:57 -0600

GWASpro supports building complex design matrices, by which complex experimental designs that may include replications, treatments, locations and times, can be accounted for in the linear mixed model (LMM). GWASpro is optimized to handle GWAS data that may consist of up to 10 million markers and 10,000 samples from replicable lines or hybrids. GWASpro provides an interface that significantly reduces the learning curve for new GWAS investigators.

Address of the bookmark: https://bioinfo.noble.org/GWASPRO/