DattaLab Software Page

 

All software/computer codes listed here are for non-commercial use only.

Furthermore, they are being distributed “as is” without any implicit or explicit

warrantee of any kind. In other words, use them at your own will and risk.

                                                       

 

 

Bioinformatics Software

 

·       R Code for computing association scores with NGS-data        

 

References:

 

Pesonen, M., Nevalainen, J., Potter, S. S, , Datta, S. A Combined PLS and negative Datta, S.

binomial regression model for inferring association networks from next-generation sequencing

count data. IEEE/ACM Transactions on Computational Biology and Bioinformatics, to appear . doi: 10.1109/TCBB.2017.2665495, PMID: 28186904

 

·       R Code for Differential network Analysis with Palate Development NGS data (preliminary)         

 

References:

 

“Differential Network Analysis for Palate Development”. Poster Presentation by Tyler Grimes.

FaceBase Meeting, Boston, May 2017.

 

·       R Code for Master Regulator Identification         

 

References:

 

Sikdar, S. and Datta, S. A novel statistical approach for identification of the master regulator transcription factor,  preprint (2016).

 

 

·       R Package for SVAPLS

 

References:

 

Chakraborty, S., Datta, S. and Datta, S. svapls: An R package to correct for residual expression heterogeneity in gene expression data. BMC Bioinformatics  14, 236 (2013).

 

Chakraborty, S., Datta, S. and Datta, S. Surrogate variable analysis using partial least squares (SVA-PLS) in gene expression studies. Bioinformatics  28, 799806 (2012).

 

 

·       R Package for Differential Network Analysis

 

References:

 

Gill, R., Datta, S. and Datta, S. A statistical framework for differential network analysis from microarray data using partial least squares, BMC Bioinformatics, 11, 95 (2010).

 

·       R Code for Ensemble Classifier         

 

References:

 

Datta, S, Pihur, V. and Datta, S. An adaptive optimal ensemble classifier via bagging and rank aggregation with applications to high dimensional data,  BMC Bioinformatics, 11:427 (2010).

 

 

 

References:

 

Pihur, V., Datta, S. and Datta, S. RankAggreg, an R package for weighted rank aggregation. BMC Bioinformatics, 10, 62 (2009).

 

Pihur, V., Datta, S. and Datta, S. Weighted rank aggregation of cluster validation measures: A Monte Carlo cross-entropy approach.  Bioinformatics, 23, 1607-1615 (2007).

 

 

    

References:

 

Datta, S.  and Datta, S. Methods for evaluating clustering algorithms for gene expression data using a reference set of functional classes, BMC Bioinformatics, 7:397 (2006).

 

Datta, S. and Datta, S. Comparisons and validation of statistical clustering techniques for microarray gene expression data. Bioinformatics, 19,  459-466 (2003).

 

 

References:

 

Datta, S.  and Datta, S.  Empirical Bayes screening (EBS) of many p-values with applications to microarray studies, Bioinformatics, 21,1987-1994 (2005).

 

 

 

Proteomics Software

 

 

 

References:

 

Satten, G. A., Datta, S., Moura, H., Woolfitt, A., Carvalho, G., De, B. K,  Pavlopoulos, A., Carlone, G. M., and Barr, J. Standardization and denoising algorithms for mass spectra to classify whole-organism bacterial specimens,  Bioinformatics, 20, 3128-3136 (2004). 

 

·       Peak Detection and Classification using MALDI-TOF Mass Spectra

 

References:

 

Ndukum, J., Atlas, M., Datta, S. (2011). pkDACLASS: open source software for analyzing MALDI-TOF, Bioinformation, 6, 45-47. PMC3064853

 

 

 

Statistics Software

 

 

 

References:

 

Datta, S. and Satten, G. A. Rank-sum tests for clustered data, Journal of the American Statistical Association, 100, 908-915 (2005).

 

 

References:

 

Datta, S. and Satten, G. A. A signed-rank test for clustered data, Biometrics, 64, 501-507 (2008).

 

 

References:

 

Lorenz, D. J., Datta, S. and Harkema, S. J. Marginal association measures for clustered data, Statistics in  Medicine, 30, 3181-3191 (2011).

 

 

          R-package for multistate models

 

References:

 

Ferguson, A. N., Datta, S., Brock, G. msSurv, an R package for nonparametric estimation of multistate models. Journal of Statistical Software (2012).