Projects supporting the any format supported by r data format.


Logo APCluster 1.4.1

by UBod - December 10, 2014, 12:58:29 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 18528 views, 3396 downloads, 3 subscriptions

Rating Whole StarWhole StarWhole StarWhole Star1/2 Star
(based on 2 votes)

About: The apcluster package implements Frey's and Dueck's Affinity Propagation clustering in R. The package further provides leveraged affinity propagation, exemplar-based agglomerative clustering, and various tools for visual analysis of clustering results.

Changes:
  • fixes in C++ code of sparse affinity propagation

Logo KeBABS 1.0.2

by UBod - December 4, 2014, 09:15:24 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1016 views, 151 downloads, 1 subscription

About: Kernel-Based Analysis Of Biological Sequences

Changes:
  • a few C code changes for mismatch kernel
  • correction of MCC
  • correction of computation of feature weights for LiblineaR with more than 3 classes

Logo jackstraw 1.0

by nc - February 1, 2014, 22:53:41 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1257 views, 261 downloads, 1 subscription

About: Estimates statistical significance of association between variables and their principal components (PCs).

Changes:

Initial Announcement on mloss.org.


Logo FABIA 2.8.0

by hochreit - October 18, 2013, 10:14:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 9670 views, 2012 downloads, 1 subscription

Rating Whole StarWhole StarWhole StarWhole Star1/2 Star
(based on 1 vote)

About: FABIA is a biclustering algorithm that clusters rows and columns of a matrix simultaneously. Consequently, members of a row cluster are similar to each other on a subset of columns and, analogously, members of a column cluster are similar to each other on a subset of rows. Biclusters are found by factor analysis where both the factors and the loading matrix are sparse. FABIA is a multiplicative model that extracts linear dependencies between samples and feature patterns. Applications include detection of transcriptional modules in gene expression data and identification of haplotypes/>identity by descent< consisting of rare variants obtained by next generation sequencing.

Changes:

CHANGES IN VERSION 2.8.0

NEW FEATURES

o rescaling of lapla
o extractPlot does not plot sorted matrices

CHANGES IN VERSION 2.4.0

o spfabia bugfixes

CHANGES IN VERSION 2.3.1

NEW FEATURES

o Getters and setters for class Factorization

2.0.0:

  • spfabia: fabia for a sparse data matrix (in sparse matrix format) and sparse vector/matrix computations in the code to speed up computations. spfabia applications: (a) detecting >identity by descent< in next generation sequencing data with rare variants, (b) detecting >shared haplotypes< in disease studies based on next generation sequencing data with rare variants;
  • fabia for non-negative factorization (parameter: non_negative);
  • changed to C and removed dependencies to Rcpp;
  • improved update for lambda (alpha should be smaller, e.g. 0.03);
  • introduced maximal number of row elements (lL);
  • introduced cycle bL when upper bounds nL or lL are effective;
  • reduced computational complexity;
  • bug fixes: (a) update formula for lambda: tighter approximation, (b) corrected inverse of the conditional covariance matrix of z;

1.4.0:

  • New option nL: maximal number of biclusters per row element;
  • Sort biclusters according to information content;
  • Improved and extended preprocessing;
  • Update to R2.13

About: Infrastructure for representing, manipulating and analyzing transaction data and frequent patterns.

Changes:

Initial Announcement on mloss.org.