TCC 1.10.0 – Differential Expression Analysis for Tag Count data with Robust Normalization Strategies

TCC 1.10.0

:: DESCRIPTION

TCC provides a series of functions for performing differential expression analysis from RNA-seq count data using robust normalization strategy (called DEGES).

::DEVELOPER

Jianqiang Sun <wukong at bi.a.u-tokyo.ac.jp>, Tomoaki Nishiyama <tomoakin at staff.kanazawa-u.ac.jp>, Koji Kadota

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • R
  • BioConductor

:: DOWNLOAD

 TCC

:: MORE INFORMATION

Citation

TCC: an R package for comparing tag count data with robust normalization strategies.
Sun J, Nishiyama T, Shimizu K, Kadota K.
BMC Bioinformatics. 2013 Jul 9;14:219. doi: 10.1186/1471-2105-14-219.

MetTailor 1.0 – Dynamic Block Summary and Data Normalization for Robust Analysis

MetTailor 1.0

:: DESCRIPTION

MetTailor is a software package that performs post-extraction processing steps such as cross-sample realignment and data normalization that are specifically designed to account for the experimental factors from chromatographic separation and MS analysis.

::DEVELOPER

MetTailor team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Mac OsX / Windows
  • R

:: DOWNLOAD

 MetTailor

:: MORE INFORMATION

Citation

MetTailor: Dynamic Block Summary and Intensity Normalization for Robust Analysis of Mass Spectrometry Data in Metabolomics.
Chen G, Cui L, Teo G, Ong CN, Tan CS, Choi H.
Bioinformatics. 2015 Jul 27. pii: btv434.

RPA 1.24.0 – Robust Probabilistic Averaging for probe-level analysis

RPA 1.24.0

:: DESCRIPTION

RPA is a software of scalable microarray preprocessing and analysis of probe performance based on Robust Probabilistic Averaging (R/Bioconductor).

::DEVELOPER

Leo Lahti

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • R package
  • BioConductor

:: DOWNLOAD

 RPA

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2013 May 1;41(10):e110. doi: 10.1093/nar/gkt229. Epub 2013 Apr 5.
A fully scalable online pre-processing algorithm for short oligonucleotide microarray atlases.
Lahti L, Torrente A, Elo LL, Brazma A, Rung J.

CNVtools 1.62.0 – Robust CNV Case Control and Quantitative Trait Association

CNVtools 1.62.0

:: DESCRIPTION

CNVtools is an R package for performing robust case control and quantitative trait association analyses of Copy Number Variants.

::DEVELOPER

Chris Barnes

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • R
  • BioConductor

:: DOWNLOAD

  CNVtools 

:: MORE INFORMATION

Citation

A robust statistical method for case-control association testing with Copy Number Variation.
Barnes C, Plagnol V, Fitzgerald T, Redon R, Marchini J, Clayton D, Hurles ME.
Nature Genetics, 2008 Oct;40(10):1245-52

MARS 1.2 – Robust Automatic Backbone Assignment of Proteins

MARS 1.2

:: DESCRIPTION

MARS is a program for robust automatic backbone assignment of 13C/15N labeled proteins. It can be applied independent of the assignment complexity, it does not require tight thresholds for establishing sequential connectivity or detailed adjustment of these thresholds, it can work with a wide variety of NMR experiments and it is robust against missing chemical shift information. In case of a known 3D structure, residual dipolar couplings can be used to enhance assignment.

::DEVELOPER

Research Group Zweckstetter

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Mac OsX

:: DOWNLOAD

  MARS

:: MORE INFORMATION

Citation

Mars — robust automatic backbone assignment of proteins.
Jung YS, Zweckstetter M.
J Biomol NMR. 2004 Sep;30(1):11-23.

GGD-Lasso – Graph-regularized dual Lasso for robust eQTL mapping

GGD-Lasso

:: DESCRIPTION

GGD-Lasso (Graph-regularized Dual Lasso) is a robust approach for eQTL mapping.

::DEVELOPER

Wei Cheng

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • C Compiler / MatLab

:: DOWNLOAD

 GGD-Lasso

:: MORE INFORMATION

Citation

Bioinformatics. 2014 Jun 15;30(12):i139-i148. doi: 10.1093/bioinformatics/btu293.
Graph-regularized dual Lasso for robust eQTL mapping.
Cheng W, Zhang X, Guo Z, Shi Y, Wang W.

ROS-DET – Robust Detector of Switching Mechanisms in Gene Expression

ROS-DET

:: DESCRIPTION

ROS-DET (standing for RObust Switching mechanisms DETector) is an efficient and robust method for detecting switching mechanisms in gene expression.

::DEVELOPER

Mitsunori, Kayano, Ph.D.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/MacOsX

:: DOWNLOAD

 ROS-DET

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2011 Jun;39(11):e74. doi: 10.1093/nar/gkr130. Epub 2011 Apr 1.
ROS-DET: robust detector of switching mechanisms in gene expression.
Kayano M1, Takigawa I, Shiga M, Tsuda K, Mamitsuka H.

PredBF – Robust Prediction of B-factor Profile from Sequence

PredBF

:: DESCRIPTION

PredBF is a web server for robust prediction of B-factor profile from sequence using two-stage SVR based on random forest feature selection

::DEVELOPER

Computational Systems Biology Group, Shanghai Jiao Tong University

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation:

Protein Pept Lett. 2009;16(12):1447-54.
Robust prediction of B-factor profile from sequence using two-stage SVR based on random forest feature selection.
Pan XY1, Shen HB.

smoothseg 0.0.4 – Robust smooth segmentation approach for array CGH data analysis

smoothseg 0.0.4

:: DESCRIPTION

smoothseg is an R package to compute smooth-segmentation of array CGH data, including the estimation of FDR for comparative studies.

::DEVELOPER

Huang Jian <j.huang@ucc.ie>,  Prof. Yudi Pawitan ,Arief Gusnanto <Arief.Gusnanto@mrc-bsu.cam.ac.uk>

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux /MacOsX
  • R package

:: DOWNLOAD

 smoothseg

:: MORE INFORMATION

Citation

Bioinformatics. 2007 Sep 15;23(18):2463-9. Epub 2007 Jul 27.
Robust smooth segmentation approach for array CGH data analysis.
Huang J1, Gusnanto A, O’Sullivan K, Staaf J, Borg A, Pawitan Y.

FARMS 1.4.1 – Factor Analysis for Robust Microarray Summarization

FARMS 1.4.1

:: DESCRIPTION

FARMS (Factor Analysis for Robust Microarray Summarization ) is a model-based technique for summarizing high-density oligonucleotide array data at probe level for Affymetrix GeneChips. It is based on a factor analysis model for which a Bayesian maximum a posteriori method optimizes the model parameters under the assumption of Gaussian measurement noise. The comparison on the Affymetrix spiked-in bechmark data shows the excellent sensitivity and specificity performance of FARMS.

::DEVELOPER

Institute of Bioinformatics, Johannes Kepler University Linz

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 FARMS

:: MORE INFORMATION

Citation

Sepp Hochreiter, Djork-Arné Clevert, and Klaus Obermayer.
A new summarization method for affymetrix probe level data.”
Bioinformatics 2006 22(8):943-949;