Tag: de novo

Rnnotator 3.5.0 – de novo Transcriptome Assembly pipeline from stranded RNA-Seq reads

Rnnotator 3.5.0

:: DESCRIPTION

Rnnotator is an automated software pipeline that generates transcript models by de novo assembly of RNA-Seq data without the need for a reference genome.

::DEVELOPER

Zhong Wang at U.S. Department of Energy Joint Genome Institute

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Perl
  • BioPerl
  • Blat

:: DOWNLOAD

  Rnnotator

:: MORE INFORMATION

Citation

BMC Genomics. 2010 Nov 24;11:663. doi: 10.1186/1471-2164-11-663.
Rnnotator: an automated de novo transcriptome assembly pipeline from stranded RNA-Seq reads.
Martin J, Bruno VM, Fang Z, Meng X, Blow M, Zhang T, Sherlock G, Snyder M, Wang Z.

RIPSeeker 1.26.0 – de novo RIP Peak Predictions based on HMM.

RIPSeeker 1.26.0

:: DESCRIPTION

RIPSeeker is a free open-source Bioconductor/R package for identifying protein-associated transcripts from RIP-seq experiments.

::DEVELOPER

Yue Li @ The Zhang Lab, University of Toronto

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Weindows/Linux/MacOsX
  • R package
  • BioConductor

:: DOWNLOAD

 RIPSeeker

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2013 Apr;41(8):e94. doi: 10.1093/nar/gkt142. Epub 2013 Feb 28.
RIPSeeker: a statistical package for identifying protein-associated transcripts from RIP-seq experiments.
Li Y1, Zhao DY, Greenblatt JF, Zhang Z.

HHrepID 1.0.0 – de novo Protein Repeat Detection

HHrepID 1.0.0

:: DESCRIPTION

HHrepID is a novel automated procedure for the de novo identification of repeats in protein sequences. It is able to detect the sequence signature of structural repeats in many proteins that have not yet been known to possess internal sequence symmetry, such as TIM barrels and outer membrane beta-barrels. HHrepID uses HMM-HMM comparison to exploit evolutionary information in the form of the multiple sequence alignment of homologs, but in contrast to HHrep, the new method has several novel characteristics: (1) automated generation of a multiple alignment of repeats; (2) utilization of the transitive nature of homology through a novel merging procedure based on the fully probabilistic treatment of alignments; (3) superior alignment quality through an algorithm that maximizes the expected accuracy of an alignment; (4) the ability to identify different repeats within complicated architectures or multiple domains through automatic domain boundary detection, (5) new statistical treatment yielding improved sensitivity.

::DEVELOPER

Söding Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

  HHrepID

:: MORE INFORMATION

Citation

Biegert A, Söding J:
HHrepID: de novo protein repeat identification by probabilistic consistency
Bioinformatics 2008 24(6), 807-814.

MAP 20121108 – A de novo Metagenomic Assembly program for Shotgun DNA reads

MAP 20121108

:: DESCRIPTION

MAP (Metagenomic Assembly program) is a de novo assembly approach and its implementation based on an improved Overlap/Layout/Consensus (OLC) strategy incorporated with several special algorithms.MAP uses the mate pair information, resulting in being more applicable to shotgun DNA reads (recommended as > 200 bp) currently widely-used in metagenome projects. Results of extensive tests on simulated data show that MAP can be superior to both Celera and Phrap for typical longer reads by Sanger sequencing, as well as has an evident advantage over Celera, Newbler, and the newest Genovo, for typical shorter reads by 454 sequencing.

::DEVELOPER

ZhuLab, Peking Uiniversity, Beijing

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

MAP

:: MORE INFORMATION

Citation

Bioinformatics. 2012 Jun 1;28(11):1455-62. Epub 2012 Apr 11.
A de novo metagenomic assembly program for shotgun DNA reads.
Lai B, Ding R, Li Y, Duan L, Zhu H.

DETONATE 1.11 – DE novo TranscriptOme rNa-seq Assembly with or without the Truth Evaluation

DETONATE 1.11

:: DESCRIPTION

DETONATE consists of two component packages, RSEM-EVAL and REF-EVAL. Both packages are mainly intended to be used to evaluate de novo transcriptome assemblies, although REF-EVAL can be used to compare sets of any kinds of genomic sequences.

::DEVELOPER

Colin Dewey

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 DETONATE

:: MORE INFORMATION

Citation

Genome Biol. 2014 Dec 21;15(12):553. doi: 10.1186/s13059-014-0553-5.
Evaluation of de novo transcriptome assemblies from RNA-Seq data.
Li B, Fillmore N, Bai Y, Collins M, Thomson JA, Stewart R, Dewey CN.

BinPacker 1.1 – Packing-Based De Novo Transcriptome Assembly from RNA-seq Data

BinPacker 1.1

:: DESCRIPTION

BinPacker is a novel de novo assembler by modeling the transcriptome assembly problem as tracking a set of trajectories of items with their sizes representing coverage of their corresponding isoforms by solving a series of bin-packing problems.

::DEVELOPER

BinPacker team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 BinPacker

:: MORE INFORMATION

Citation

BinPacker: Packing-Based De Novo Transcriptome Assembly from RNA-seq Data.
Liu J, Li G, Chang Z, Yu T, Liu B, McMullen R, Chen P, Huang X.
PLoS Comput Biol. 2016 Feb 19;12(2):e1004772. doi: 10.1371/journal.pcbi.1004772.

PRIORITY 2.1.0 – de novo Motif Discovery

PRIORITY 2.1.0

:: DESCRIPTION

PRIORITY is a tool for de novo motif discovery in the context of transcription factor (TF) binding sites. It implements a new approach to motif discovery in which informative priors over sequence positions are used to guide the search.

::DEVELOPER

Alex Hartemink

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • Java

:: DOWNLOAD

  PRIORITY

:: MORE INFORMATION

Citation

Bioinformatics. 2006 Jul 15;22(14):e384-92.
Informative priors based on transcription factor structural class improve de novo motif discovery.
Narlikar L, Gordan R, Ohler U, Hartemink AJ.

MAXIMUS 0.2 – Hybrid Reference and de novo Assembly pipeline

MAXIMUS 0.2

:: DESCRIPTION

MAXIMUS is a genome assembly pipeline which takes the best out of multiple reference assemblies and de novo assembly. The benefits of this approach include better assembled repetitive regions, less gaps and higher accuracy for the resultant assembly.

::DEVELOPER

The Chinese University of Hong Kong

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

  MAXIMUS

:: MORE INFORMATION

IDBA / IDBA-UD 1.1.1 – De Bruijn Graph De Novo Assembler with Highly Uneven Sequencing Depth

IDBA-UD 1.1.1

:: DESCRIPTION

 IDBA is a practical iterative De Bruijn Graph De Novo Assembler for sequence assembly in bioinfomatics. Most assemblers based on de Bruijn graph build a de Bruijn graph with a specific k to perform the assembling task. For all of them, it is very crucial to find a specific value of k. If k is too large, there will be a lot of gap problems in the graph. If k is too small, there will a lot of branch problems. IDBA uses not only one specific k but a range of k values to build the iterative de Bruijn graph. It can keep all the information in graphs with different k values. So, it will perform better than other assemblers.

IDBA-UD is a iterative De Bruijn Graph De Novo Assembler for Short Reads Sequencing data with Highly Uneven Sequencing Depth. It is an extension of IDBA algorithm. IDBA-UD also iterates from small k to a large k. In each iteration, short and low-depth contigs are removed iteratively with cutoff threshold from low to high to reduce the errors in low-depth and high-depth regions. Paired-end reads are aligned to contigs and assembled locally to generate some missing k-mers in low-depth regions. With these technologies, IDBA-UD can iterate k value of de Bruijn graph to a very large value with less gaps and less branches to form long contigs in both low-depth and high-depth regions.

::DEVELOPER

Bioinformatics Research Group of Hong Kong University

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 IDBA-UD

:: MORE INFORMATION

Citation:

Yu Peng, Henry Leung, S.M. Yiu, Francis Y.L. Chin.
IDBA – A Practical Iterative de Bruijn Graph De Novo Assembler
The 14th Annual International Conference on Research in Computational Molecular Biology (RECOMB 2010), Lisbon, Portugal, 25-28 April 2010.

Bioinformatics. 2012 Jun 1;28(11):1420-8. Epub 2012 Apr 11.
IDBA-UD: a de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth.
Peng Y, Leung HC, Yiu SM, Chin FY.