DeepSEA 0.94c -Deep learning-based algorithmic framework for Predicting Chromatin Effects

DeepSEA 0.94c

:: DESCRIPTION

DeepSEA is a deep learning-based algorithmic framework for predicting the chromatin effects of sequence alterations with single nucleotide sensitivity. DeepSEA can accurately predict the epigenetic state of a sequence, including transcription factors binding, DNase I sensitivities and histone marks in multiple cell types, and further utilize this capability to predict the chromatin effects of sequence variants and prioritize regulatory variants.

::DEVELOPER

Troyanskaya Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

DeepSEA

:: MORE INFORMATION

Citation

Zhou J, Troyanskaya OG.
Predicting effects of noncoding variants with deep learning-based sequence model.
Nat Methods. 2015 Oct;12(10):931-4. doi: 10.1038/nmeth.3547. Epub 2015 Aug 24. PMID: 26301843; PMCID: PMC4768299.

Selene 0.4.8 – Library for deep-learning-based Sequence models

Selene 0.4.8

:: DESCRIPTION

Selene is a Python library and command line interface for training deep neural networks from biological sequence data such as genomes.

::DEVELOPER

Troyanskaya Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux
  • Python

:: DOWNLOAD

Selene

:: MORE INFORMATION

Citation

Chen KM, Cofer EM, Zhou J, Troyanskaya OG.
Selene: a PyTorch-based deep learning library for sequence data.
Nat Methods. 2019 Apr;16(4):315-318. doi: 10.1038/s41592-019-0360-8. Epub 2019 Mar 28. PMID: 30923381; PMCID: PMC7148117.

ABrowse – Customizable Next-generation Genome Browser Framework

ABrowse

:: DESCRIPTION

ABrowse is an open source genome browser framework for not only end users, but also data providers and developers. Powered by cutting-edge technologies, ABrowse provides a rather comprehensive set of features as a modern next-generation genome browser framework

::DEVELOPER

Gao Lab, Peking University.

:: SCREENSHOTS

N/A

::REQUIREMENTS

  • Web browser

:: DOWNLOAD

No

:: MORE INFORMATION

Citation

Kong L, Wang J, Zhao S, Gu X, Luo J, Gao G.
ABrowse–a customizable next-generation genome browser framework.
BMC Bioinformatics. 2012 Jan 5;13:2. doi: 10.1186/1471-2105-13-2. PMID: 22222089; PMCID: PMC3265404.

cis-Browser 1.0 – Genome Browser for Cis-regulatory Information

cis-Browser 1.0

:: DESCRIPTION

cis-Browser (cis-Regulatory Browser) is genome browser for cis-regulatory information inferring logic functions of genomic cis-regulatory code and the principles of information processing of genomic regulation

::DEVELOPER

The Istrail Laboratory of Brown University

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux/ Windows/ MacOsX
  • Java

:: DOWNLOAD

 cis-Browser

:: MORE INFORMATION

Citation

Methods Mol Biol. 2010;674:369-99. doi: 10.1007/978-1-60761-854-6_22.
Practical computational methods for regulatory genomics: a cisGRN-Lexicon and cisGRN-browser for gene regulatory networks.
Istrail S, Tarpine R, Schutter K, Aguiar D.

GSDS 2.0 – Gene Structure Display Server

GSDS 2.0

:: DESCRIPTION

GSDS is designed for the visualization of annotated features for genes, and the generation of high-quality figures for publication.

::DEVELOPER

Gao Lab, Peking University.

:: SCREENSHOTS

N/A

::REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

GSDS 2.0: an upgraded gene feature visualization server.
Hu B, Jin J, Guo AY, Zhang H, Luo J, Gao G.
Bioinformatics. 2014 Dec 10. pii: btu817

BM-BC 1.0 – Bayesian method of Base Calling for Solexa Sequence data

BM-BC 1.0

:: DESCRIPTION

BM-BC is a Bayesian method of base calling for Solexa-GA sequencing data. The Bayesian method builds on a hierarchical model that accounts for three sources of noise in the data, which are known to affect the accuracy of the base calls: fading, phasing, and cross-talk between channels.

::DEVELOPER

Yuan Ji Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • R package

:: DOWNLOAD

 BM-BC

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2012;13 Suppl 13:S6. doi: 10.1186/1471-2105-13-S13-S6. Epub 2012 Aug 24.
BM-BC: a Bayesian method of base calling for Solexa sequence data.
Ji Y, Mitra R, Quintana F, Jara A, Mueller P, Liu P, Lu Y, Liang S.

VIRS – A Visual tool for Identifying Restriction Sites

VIRS

:: DESCRIPTION

VIRS is an interactive web-based program designed for restriction endonuclease cut sites prediction and visualisation. The system permits to simultaneously process batch DNA sequences, and produces visual restriction maps with several useful options for users’ customisation. These options also perform in-depth analysis of the restriction maps, such as virtual electrophoretic result for digested fragments. Different from other analytical tools, VIRS not only displays visual outputs, but also provides the detailed properties of enzymes that are commercially avaialbe. All the information correlates with enzymes is stored in our database, which is updated monthly from the manufacturers’ websites.

::DEVELOPER

BIS @ Zhejiang University

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Xiang Chen, Cong Luo, Xiaoxia Ma, Ming Chen* (2009)
VIRS: a visual tool for identifying restriction sites in multiple DNA sequences.
Biotechnology Progress, 25(5): 1525-1527.

SToRM 0.0099 – Seed-based Read Mapping tool for SOLiD or Illumina sequencing data

SToRM 0.0099

:: DESCRIPTION

SToRM is a software tool primarily proposed for mapping SOLiD reads or Illumina reads to a reference genome. It was based on seeding techniques adapted to the statistical characteristics of the reads: the default seeds are for example designed (using the Iedera software) to comply with the properties of the SOLiD color encoding, or Illumina more classical encoding as well as the observed reading error distribution along the read.

::DEVELOPER

Bonsai Bioinformatics

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  •  Linux / MacOsX
  • C Compiler

:: DOWNLOAD

 SToRM

:: MORE INFORMATION

Citation

Noé, L. and Gîrdea,. and Kucherov, G.:
Designing efficient spaced seeds for SOLiD read mapping
Advances in Bioinformatics, Volume 2010 2010

BM-Map 2.0.1 – Refining Next-Generation Sequencing (NGS) Read Mapping

BM-Map 2.0.1

:: DESCRIPTION

BM-Map is a powerful NGS genomic loci mapping refiner. It improves the mapping of the multireads (reads mapped to more than one genomic location with similar fidelities), as a refinement step after the general read-alignment is completed.

::DEVELOPER

Yuan Ji Lab  and Dr. Han Liang’s group.

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux / Windows / MacOsX

:: DOWNLOAD

 BM-Map

:: MORE INFORMATION

Citation

BMC Genomics. 2012;13 Suppl 8:S9. doi: 10.1186/1471-2164-13-S8-S9. Epub 2012 Dec 17.
BM-Map: an efficient software package for accurately allocating multireads of RNA-sequencing data.
Yuan Y1, Norris C, Xu Y, Tsui KW, Ji Y, Liang H.

Biometrics. 2011 Dec;67(4):1215-24. doi: 10.1111/j.1541-0420.2011.01605.x. Epub 2011 Apr 22.
BM-map: Bayesian mapping of multireads for next-generation sequencing data.
Ji Y, Xu Y, Zhang Q, Tsui KW, Yuan Y, Norris C Jr, Liang S, Liang H.

BayClone / BayClone2 1.1 – A Bayesian Sequence and Copy Number Caller for Subclones Using NGS Data

BayClone / BayClone2 1.1

:: DESCRIPTION

BayClone2 as an extension of BayClone provides a Bayesian solution using next-generation sequencing (NGS) data for joint inference on both, structure and sequencing variants within a subclone.

::DEVELOPER

Yuan Ji Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX / Windows
  • R

:: DOWNLOAD

 BayClone / BayClone2 

:: MORE INFORMATION

Citation

Pac Symp Biocomput. 2015;20:467-78.
Bayclone: bayesian nonparametric inference of tumor subclones using ngs data.
Sengupta S1, Wang J, Lee J, Müller P, Gulukota K, Banerjee A, Ji Y.

Bayesian Inference for Tumor Subclones Accounting for Sequencing and Structural Variants
Juhee Lee, Peter Mueller, Subhajit Sengupta, Kamalakar Gulukota, Yuan Ji
arXiv:1409.7158 [stat.ME]