MSClust 20130708 – Clustering 16S rRNA sequences into OTUs

MSClust 20130708

:: DESCRIPTION

MSClust (Multi-Seeds Based Clustering Algorithm) is an Matlab package for Clustering 16S rRNA sequences into OTUs.

::DEVELOPER

Zhao Hongyu’s Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • Matlab

:: DOWNLOAD

 MSClust

:: MORE INFORMATION

Citation

J Microbiol Methods. 2013 Sep;94(3):347-55. doi: 10.1016/j.mimet.2013.07.004. Epub 2013 Jul 28.
MSClust: A Multi-Seeds based Clustering algorithm for microbiome profiling using 16S rRNA sequence.
Chen W1, Cheng Y, Zhang C, Zhang S, Zhao H.

iPAC 1.37.0 – Identification of Protein Amino acid mutation Clustering

iPAC 1.37.0

:: DESCRIPTION

iPAC finds mutation clusters on the amino acid level while taking into account the protein structure.

::DEVELOPER

Zhao Hongyu’s Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 iPAC

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2013 Jun 13;14:190. doi: 10.1186/1471-2105-14-190.
Utilizing protein structure to identify non-random somatic mutations.
Ryslik GA, Cheng Y, Cheung KH, Modis Y, Zhao H.

GenClust 2.0 – Clustering Gene Expression data

GenClust 2.0

:: DESCRIPTION

GenClust is a new genetic algorithm for clustering gene expression data. It has two key features: (a) a novel coding of the search space that is simple, compact and easy to update; (b) it can be used naturally in conjunction with data driven internal validation methods.

::DEVELOPER

Lo Bosco Giosuè , Raffaele Giancarlo

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOSX / Windows

:: DOWNLOAD

 GenClust

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2005 Dec 7;6:289.
GenClust: a genetic algorithm for clustering gene expression data.
Di Gesú V1, Giancarlo R, Lo Bosco G, Raimondi A, Scaturro D.

ClusCo 0.3 – Clustering and Comparison of Protein Models

ClusCo 0.3

:: DESCRIPTION

ClusCo is a software for GPU/CPU clustering and comparison of protein models.

::DEVELOPER

Laboratory of Theory of Biopolymers,  University of Warsaw

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 ClusCo

:: MORE INFORMATION

Citation

ClusCo: clustering and comparison of protein models.
Jamroz M, Kolinski A.
BMC Bioinformatics. 2013 Feb 22;14:62. doi: 10.1186/1471-2105-14-62.

CITE-sort – Artificial-cell-type Aware Surface Marker Clustering method for CITE-seq data

CITE-sort

:: DESCRIPTION

CITE-sort conducts auto-gating with CITE-seq ADT data using recursive Gaussian Mixture Model. It is robust against artificial cell types that stem from multiplets. CITE-sort also provides concrete explanations of its internal decision process by constructing a biologically meaningful sort tree.

::DEVELOPER

Chen Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python
:: DOWNLOAD

CITE-sort

:: MORE INFORMATION

Citation

Lian Q, Xin H, Ma J, Konnikova L, Chen W, Gu J, Chen K.
Artificial-cell-type aware cell-type classification in CITE-seq.
Bioinformatics. 2020 Jul 1;36(Suppl_1):i542-i550. doi: 10.1093/bioinformatics/btaa467. PMID: 32657383; PMCID: PMC7355304.

MULCCH – MULti-task spectral Consensus Clustering for Hierarchically related tasks

MULCCH

:: DESCRIPTION

MULCCH is a consensus extension of a multi-task clustering algorithm to infer high-confidence strain-specific host response modules under infections from multiple virus strains.

::DEVELOPER

Roy Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 MULCCH

:: MORE INFORMATION

Citation

Multi-task Consensus Clustering of Genome-wide Transcriptomes from Related Biological Conditions.
Niu Z, Chasman D, Eisfeld AJ, Kawaoka Y, Roy S.
Bioinformatics. 2016 Jan 21. pii: btw007.

Hammock v1.2.0 – Hidden Markov Model-based Peptide Clustering algorithm

Hammock v1.2.0

:: 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

DGEclust 20171006 – Hierarchical non-parametric Bayesian Clustering of Digital Expression data

DGEclust 20171006

:: DESCRIPTION

DGEclust is a program for clustering and differential expression analysis of expression data generated by next-generation sequencing assays, such as RNA-seq, CAGE and others.

::DEVELOPER

Dimitris Vavoulis

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 DGEclust 

:: MORE INFORMATION

Citation:

Genome Biol. 2015 Feb 20;16:39. doi: 10.1186/s13059-015-0604-6.
DGEclust: differential expression analysis of clustered count data.
Vavoulis DV, Francescatto M, Heutink P, Gough J.

flowPeaks 1.38.0 – Fast unsupervised Clustering for Flow Cytometry Data

flowPeaks 1.38.0

:: DESCRIPTION

flowPeaks is a fast and automatic clustering to classify the cells into subpopulations based on finding the peaks from the overall density function generated by K-means

::DEVELOPER

Yongchao Ge<yongchao.ge at gmail.com>

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • BioConductor/ R

:: DOWNLOAD

 flowPeaks

:: MORE INFORMATION

Citation

flowPeaks: a fast unsupervised clustering for flow cytometry data via K-means and density peak finding.
Ge Y, Sealfon SC.
Bioinformatics. 2012 Aug 1;28(15):2052-8. doi: 10.1093/bioinformatics/bts300

SCENIC 1.1.2 / pySCENIC 0.11.2- Single-cell Regulatory Network Inference and Clustering

SCENIC 1.1.2 / pySCENIC 0.11.2

:: DESCRIPTION

SCENIC is an R package to infer Gene Regulatory Networks and cell types from single-cell RNA-seq data.

pySCENIC is a lightning-fast python implementation of the SCENIC pipeline (Single-Cell rEgulatory Network Inference and Clustering) which enables biologists to infer transcription factors, gene regulatory networks and cell types from single-cell RNA-seq data.

::DEVELOPER

aertslab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/ Linux/ MacOsX
  • R / Python

:: DOWNLOAD

SCENIC / pySCENIC

:: MORE INFORMATION

Citation

Aibar S, et al.
SCENIC: single-cell regulatory network inference and clustering.
Nat Methods. 2017 Nov;14(11):1083-1086. doi: 10.1038/nmeth.4463. Epub 2017 Oct 9. PMID: 28991892; PMCID: PMC5937676.

Van de Sande B,et al.
A scalable SCENIC workflow for single-cell gene regulatory network analysis.
Nat Protoc. 2020 Jul;15(7):2247-2276. doi: 10.1038/s41596-020-0336-2. Epub 2020 Jun 19. PMID: 32561888.