Giggle v0.6.3 – Search Engine for large-scale integrated Genome Analysis

Giggle v0.6.3

:: DESCRIPTION

Giggle is a genomics search engine for genomic features and intervals. That is, scalable, multi-file index for fast queries of genomic intervals.

::DEVELOPER

The Quinlan Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

Giggle

:: MORE INFORMATION

Citation:

Nat Methods. 2018 Feb;15(2):123-126. doi: 10.1038/nmeth.4556. Epub 2018 Jan 8.
GIGGLE: a search engine for large-scale integrated genome analysis.
Layer RM, Pedersen BS, DiSera T, Marth GT, Gertz J, Quinlan AR

GenomeTools 1.5.8 – Genome Analysis Software

GenomeTools 1.5.8

:: DESCRIPTION

GenomeTools genome analysis system is a free collection of bioinformatics tools (in the realm of genome informatics) combined into a single binary named gt.

::DEVELOPER

RESEARCH GROUP FOR GENOME INFORMATICS ,Center for Bioinformatics, University of Hamburg

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Mac OsX /Windows with Cygwin

:: DOWNLOAD

GenomeTools ; for Windows

:: MORE INFORMATION

The GenomeTools distribution includes several published software tools:

  • ltrharvest, an efficient and flexible software tool for de novo detection of LTR retrotransposons.
    D. Ellinghaus, S. Kurtz, and U. Willhoeft.
    LTRharvest, a efficient and flexible software for de novo detection of LTR retrotransposons.
    BMC Bioinformatics 2008, 9:18
  • tallymer, a collection of flexible and memory-efficient programs for k-mer counting and indexing of large sequence sets.
    S. Kurtz, A. Narechania, J.C. Stein, and D. Ware.
    A new method to compute K-mer frequencies and its application to annotate large repetitive plant genomes.
    BMC Genomics 2008, 9:517
  • uniquesub, a program for computing minimum unique substrings.
    S. Gräf, F.G.G. Nielsen, S. Kurtz, M.A. Huynen, E. Birney, H. Stunnenberg, and P. Flicek.
    Optimized design and assessment of whole genome tiling arrays.
    Bioinformatics 2007, 23(13):i195–i204
  • AnnotationSketch, a library for drawing genome annotations.
    S. Steinbiss, G. Gremme, C. Schärfer, M. Mader and S. Kurtz.
    AnnotationSketch: a genome annotation drawing library.
    Bioinformatics 2009, 25(4):533–534
  • ltrdigest, a software tool for automated annotation of internal features of LTR retrotransposons.
    S. Steinbiss, U. Willhoeft, G. Gremme and S. Kurtz.
    Fine-grained annotation and classification of de novo predicted LTR retrotransposons.
    Nucleic Acids Research 2009, 37(21):7002–7013
  • MetaGenomeThreader, a software to predict genes, such as PCS’s (predicted coding sequences) in sequences of metagenome projects.
    D.J. Schmitz-Hübsch and S. Kurtz.
    MetaGenomeThreader: A software tool for predicting genes in DNA-sequences of metagenome projects.
    In R. Daniel and W. Streit (Eds.), Metagenomics. Methods in Molecular Biology, 325–338, Humana Press, Totowa, NJ, ISBN 978-1-60761-822-5
  • GtEncseq, a compressed biosequence representation with many features.
    S. Steinbiss and S. Kurtz.
    A New Efficient Data Structure for Storage and Retrieval of Multiple Biosequences.
    IEEE/ACM Transactions on Computational Biology and Bioinformatics 2012, 9(2):345–357
  • Readjoiner, a sequence assembler based on the assembly string graph framework.
    G. Gonnella and S. Kurtz.
    Readjoiner: a fast and memory efficient string graph-based sequence assembler.
    BMC Bioinformatics 2012, 13:82

IonGAP – Integrated Genome Analysis Platform for Ion Torrent Sequence data

IonGAP

:: DESCRIPTION

IonGAP is a publicly available integrated pipeline designed for the assembly and subsequent analysis of Ion Torrent bacterial sequence data. Both its components and their configuration are based on a research process aimed to discover the optimal combination of tools for obtaining good results from single-end reads generated by the Ion Torrent PGM sequencer.

::DEVELOPER

IonGAP team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

IonGAP: integrative bacterial genome analysis for Ion Torrent sequence data.
Baez-Ortega A, Lorenzo-Diaz F, Hernandez M, Gonzalez-Vila CI, Roda-Garcia JL, Colebrook M, Flores C.
Bioinformatics. 2015 May 6. pii: btv283.

G-InforBIO 1.90 – E-Workbench for Comparative Genome Analysis

G-InforBIO 1.90

:: DESCRIPTION

G-InforBIO is an e-Workbench for “databasing”, comparative genome analysis. The G-InforBIO system is a novel tool for genome data management and sequence analysis. The system can import genome data encoded as eXtensible Markup Language documents as formatted text documents, including annotations and sequences, from DNA Data Bank of Japan and GenBank encoded as flat files. The genome database is constructed automatically after importing, and the database can be exported as documents formatted with eXtensible Markup Language or tab-deliminated text. Users can retrieve data from the database by keyword searches, edit annotation data of genes, and process data with G-InforBIO. In addition, information in the G-InforBIO database can be analyzed seamlessly with nine different software programs, including programs for clustering and homology analyses.

::DEVELOPER

WFCC-MIRCEN World Data Centre for Microorganisms

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • Java

:: DOWNLOAD

 G-InforBIO

:: MORE INFORMATION

Citation

Naoto Tanaka, Takashi Abe, Satoru Miyazaki and Hideaki Sugawara,
G-InforBIO: Integrated system for microbial genomics“,
BMC Bioinformatics, 7, 368, (2006).

CloudBioLinux – Genome Analysis for Cloud Computing platforms

CloudBioLinux

:: DESCRIPTION

CloudBioLinux offers genome analysis resources for cloud computing platforms such as Amazon EC2. The software is a build and deployment system which installs a large selection of Bioinformatics and machine learning libraries on a bare virtual machine (VM) image, freshly installed PC, or in the Cloud.

::DEVELOPER

CloudBioLinux Team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 CloudBioLinux

:: MORE INFORMATION

Citation

Curr Protoc Bioinformatics. 2012 Jun;Chapter 11:Unit11.9.
Using cloud computing infrastructure with CloudBioLinux, CloudMan, and Galaxy.
Afgan E, Chapman B, Jadan M, Franke V, Taylor J.

GADIST – Determine Best Distance Metric for Genome Analysis

GADIST

:: DESCRIPTION

GADIST is a software of Computing Generalized-Average Based Distances. Many popular distances used for comparing binary vectors belong to the generalized-average (GA) family of distances (see this paper : Glazko, Gordon and Mushegian. The choice of optimal distance measure in genome-wide data sets. 2005. Bioinformatics for more detail). GADIST.r produces distances with any given value of the crucial lambda parameter, and computes the first four moments of their distributions. This is useful when choosing the appropriate distance measure for genome analysis

::DEVELOPER

Bioinformatics Center and IT Group @ Stowers Institute for Medical Research

:: REQUIREMENTS

:: DOWNLOAD

 GADIST

:: MORE INFORMATION

Citation

Galina Glazko, Alexander Gordon and Arcady Mushegian
The choice of optimal distance measure in genome-wide datasets
Bioinformatics (2005) 21 (Suppl 3): iii3-iii11

GENOME EXPLORER 1.0 – Comparative Genome Analysis

GENOME EXPLORER 1.0

:: DESCRIPTION

Genome Explorer brings together the tools required to build and compare phylogenies from both sequence and gene order data. It also allows hypothesis testing through simultaneous simulation of chromosomal and sequence evolution. It was written specifically to make interaction with the tools easier for users familiar with a windows style environment – the popup windows and wizards that collect data and set parameters to run the programs are all based on a common design and are both logical and intuitive to use. Many of the available tools are independently useful but frequently used as part of more complex analyses. Genome Explorer anticipates both and therefore has a modular design that allows each tool to be run independently, preserving its full range of functionality and leaving the user fully in control of their data. All classes that run bioinformatics programs implement a common interface, all parameter collection panels are derived from a single class and parameters for each program are stored in a customised object.

::DEVELOPER

 DICKS COMPUTATIONAL BIOLOGY GROUP

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

 GENOME EXPLORER 

:: MORE INFORMATION

Citation:

Conn J, Dicks JL and Roberts IN (2002)
Genome Explorer – For Comparative Genome Analysis.
Proceedings of Objects in Bioinformatics and Cheminformatics 2002, Washington DC