CREAM 1.1.1 – Clustering of Genomic Regions Analysis Method

CREAM 1.1.1

:: DESCRIPTION

CREAM (Clustering of Genomic Regions Analysis Method) provides a new method for identification of clusters of genomic regions within chromosomes. Primarily, it is used for calling clusters of cis-regulatory elements (COREs). ‘CREAM’ uses genome-wide maps of genomic regions in the tissue or cell type of interest, such as those generated from chromatin-based assays including DNaseI, ATAC or ChIP-Seq. ‘CREAM’ considers proximity of the elements within chromosomes of a given sample to identify COREs in the following steps: 1) It identifies window size or the maximum allowed distance between the elements within each CORE, 2) It identifies number of elements which should be clustered as a CORE, 3) It calls COREs, 4) It filters the COREs with lowest order which does not pass the threshold considered in the approach.

::DEVELOPER

Princess Margaret Bioinformatics and Computational Genomics Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • R

:: DOWNLOAD

 CREAM

:: MORE INFORMATION

 

HML – Tool to perform Hierarchical Maximum Likelihood (HML) Clustering

HML

:: DESCRIPTION

HML is an algorithm which uses distribution and centroid information to cluster a sample and was applied to biological data.

::DEVELOPER

Laboratory for Medical Science Mathematics

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • MatLab

:: DOWNLOAD

  HML

:: MORE INFORMATION

Citation

IEEE Trans Biomed Eng. 2016 Mar 24.
Hierarchical Maximum Likelihood Clustering Approach.
Sharma A, Boroevich K, Shigemizu D, Kamatani Y, Kubo M, Tsunoda T.

QCluster – Extending Alignment-free Measures with Quality Values for Reads Clustering

QCluster

:: DESCRIPTION

Qcluster is a software of extending alignment-free measures with quality values for reads clustering.

::DEVELOPER

Matteo Comin

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 QCluster

:: MORE INFORMATION

Citation

Clustering of reads with alignment-free measures and quality values.
Comin M, Leoni A, Schimd M.
Algorithms Mol Biol. 2015 Jan 28;10:4. doi: 10.1186/s13015-014-0029-x

BiMS 1.0 – Biclustering for Mass Spectrometry data

BiMS 1.0

:: DESCRIPTION

BiMS is a Java application designed to allow the application of biclustering algorithms to mass spectrometry datasets.

::DEVELOPER

SING Group.

:: SCREENSHOTS

BiMS

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • JRE
  • R

:: DOWNLOAD

 BiMS

:: MORE INFORMATION

Citation

H. López-Fernández, M. Reboiro-Jato, Sara C. Madeira, Rubén López Cortés, J. D. Nunes-Miranda, H. M. Santos, Florentino Fdez-Riverola, Daniel Glez-Peña
A Workflow for the Application of Biclustering to Mass Spectrometry Data
7th International Conference on Practical Applications of Computational Biology & Bioinformatics – Advances in Intelligent Systems and Computing, 222, 2013, pp. 145-153. ISBN: 978-3-319-00577-5 (Print) 978-3-319-00578-2 (Online)

QuartPAC 1.2.0 – Identification of Mutational Clusters in Protein Quaternary Structures

QuartPAC 1.2.0

:: DESCRIPTION

QuartPAC (Quaternary Protein Amino acid Clustering) is a novel methodology, that identifies non-random mutational clustering while utilizing the protein quaternary structure in 3D space.

::DEVELOPER

QuartPAC team

:: SCREENSHOTS

N/A

::REQUIREMENTS

  • Linux / Windows/ MacOsX
  • R / BioConductor

:: DOWNLOAD

 QuartPAC

:: MORE INFORMATION

Citation

Leveraging protein quaternary structure to identify oncogenic driver mutations.
Ryslik GA, Cheng Y, Modis Y, Zhao H.
BMC Bioinformatics. 2016 Mar 22;17(1):137. doi: 10.1186/s12859-016-0963-3.

pcaReduce 1.0 – Hierarchical Clustering of Single Cell Transcriptional Profiles

pcaReduce 1.0

:: DESCRIPTION

pcaReduce is a novel agglomerative clustering method to generate a cell state hierarchy where each cluster branch is associated with a principal component of variation that can be used to differentiate two cell states.

::DEVELOPER

pcaReduce team

:: SCREENSHOTS

N/A

::REQUIREMENTS

  • Linux / Windows/ MacOsX
  • R

:: DOWNLOAD

 pcaReduce

:: MORE INFORMATION

Citation

pcaReduce: hierarchical clustering of single cell transcriptional profiles.
Žurauskienė J, Yau C.
BMC Bioinformatics. 2016 Mar 22;17(1):140. doi: 10.1186/s12859-016-0984-y.

MDI-GPU 1.0 – Accelerating integrative modelling for Genomic-scale data using GP-GPU Computing

MDI-GPU 1.0

:: DESCRIPTION

MDI-GPU is an improved implementation of a Bayesian correlated clustering algorithm, that permits integrated clustering to be routinely performed across multiple datasets, each with tens of thousands of items.

::DEVELOPER

Warwick Systems Biology Centre

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 MDI-GPU

:: MORE INFORMATION

Citation

MDI-GPU: accelerating integrative modelling for genomic-scale data using GP-GPU computing.
Mason SA, Sayyid F, Kirk PD, Starr C, Wild DL.
Stat Appl Genet Mol Biol. 2016 Mar 1;15(1):83-6. doi: 10.1515/sagmb-2015-0055.

PATTERN CLUSTERING 20060220 – Cluster a set of DNA patterns

PATTERN CLUSTERING 20060220

:: DESCRIPTION

Pattern clustering is a tool to cluster a set of DNA patterns onto smaller and more representative set of DNA patterns.Most pattern enumeration tools, such as POCO, report patterns overlapping. Therefore after discovering a set of statistically significant nucleotide patterns, it is useful to cluster the overlapping patterns into representative patterns.

::DEVELOPER

Liisa Holm’s Bioinformatics Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

  Pattern clustering

:: MORE INFORMATION

Hammock 1.04 – Hidden Markov Model-based Peptide Clustering algorithm

Hammock 1.04

:: DESCRIPTION

Hammock is a tool for peptide sequence clustering. It is able to cluster extremely large amounts of short peptide sequences into groups sharing sequence motifs.

::DEVELOPER

REGIONAL CENTRE FOR APPLIED MOLECULAR ONCOLOGY (RECAMO)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ MacOsX
  • Java
  • Clustal Omega
  • Hmmer3
  • HHsuite

:: DOWNLOAD

 Hammock

:: MORE INFORMATION

Citation:

Hammock: A Hidden Markov model-based peptide clustering algorithm to identify protein-interaction consensus motifs in large datasets.
Krejci A, Hupp T, Lexa M, Vojtesek B, Muller P.
Bioinformatics. 2015 Sep 5. pii: btv522

TransClust – A Feature-rich Clustering tool for Biomedical Data sets

TransClust

:: DESCRIPTION

TransClust is a comprehensive clustering tool that incorporates the hidden transitive nature occuring e.g. within biomedical data sets. It is based on Weighted Transitive Graph Projection problem.

::DEVELOPER

the Computational Biology research group of Jan Baumbach at the University of Southern Denmark.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows
  • Java

:: DOWNLOAD

  TransClust

:: MORE INFORMATION

Citation

Partitioning biological data with transitivity clustering.
Wittkop T, Emig D, Lange S, Rahmann S, Albrecht M, Morris JH, Böcker S, Stoye J, Baumbach J.
Nat Methods. 2010 Jun;7(6):419-20. doi: 10.1038/nmeth0610-419.