SAPS/SSPA 20110801 – Statistical Analysis of Protein Sequences & Significant Segment Pair Alignment

SAPS/SSPA 20110801

:: DESCRIPTION

SAPS (statistical analysis of protein sequences) calculates all the statistics for any individual protein sequence input.

SSPA is an acronym for Significant Segment Pair Alignment.

::DEVELOPER

The Brendel Group @ Indiana University

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux

:: DOWNLOAD

SAPS/SSPA

:: MORE INFORMATION

Citation

SAPS
Brendel, V., Bucher, P., Nourbakhsh, I.R., Blaisdell, B.E. & Karlin, S. (1992)
Methods and algorithms for statistical analysis of protein sequences.
Proc. Natl. Acad. Sci. USA 89, 2002-2006.

SSPA
Karlin, S., Weinstock, G. & Brendel, V. (1995)
Bacterial classifications derived from RecA protein sequence comparisons.
J. Bacteriol. 177, 6881-6893.

SNPMStat 4.0 – Statistical Analysis of SNP-Disease Association with Missing Genotype Data

SNPMStat 4.0

:: DESCRIPTION

SNPMStat is a command-line program for the statistical analysis of SNP-disease association in case-control/cohort/cross-sectional studies with potentially missing genotype data. SNPMStat allows the user to estimate or test SNP effects and SNP-environment interactions by maximizing the (observed-data) likelihood that properly accounts for phase uncertainty, study design and gene-environment dependence. For SNPs without missing data, the program performs the standard association analysis. For typed SNPs with missing data or untyped SNPs, the program performs the maximum-likelihood analysis

::DEVELOPER

Danyu Lin

:: SCREENSHOTS

N/A

::REQUIREMENTS

Linux

:: DOWNLOAD

SNPMStat

:: MORE INFORMATION

Citation

Hu, Y. J., Lin, D. Y. and Zeng, D. (2010),
“A General Framework for Studying Genetic Effects and Gene-Environment Interactions with Missing Data“,
Biostat (2010) 11 (4): 583-598.

HAPSTAT 3.0 – Statistical Analysis of Haplotype-disease Association

HAPSTAT 3.0

:: DESCRIPTION

HAPSTAT is a user-friendly software interface for the statistical analysis of haplotype-disease association. HAPSTAT allows the user to estimate or test haplotype effects and haplotype-environment interactions by maximizing the (observed-data) likelihood that properly accounts for phase uncertainty and study design. Cross-sectional, longitudinal, case-control and cohort studies are considered.

::DEVELOPER

Danyu Lin

:: SCREENSHOTS

N/A

::REQUIREMENTS

Linux / Windows

:: DOWNLOAD

HAPSTAT

:: MORE INFORMATION

Citation

D.Y. Lin, Y. Hu, and B.E. Huang
Simple and Efficient Analysis of Disease Associationwith Missing Genotype Data
The American Journal of Human Genetics 82, 444–452, February 2008

TCGA2STAT 1.2 – Simple TCGA Data Access for Integrated Statistical Analysis in R

TCGA2STAT 1.2

:: DESCRIPTION

TCGA2STAT automatically downloads and processes TCGA genomics and clinical data into a format convenient for statistical analyses in the R environment.

:: DEVELOPER

Liu Lab, Baylor College of Medicine

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / windows/ MacOsX
R

:: DOWNLOAD

TCGA2STAT

:: MORE INFORMATION

Citation

TCGA2STAT: Simple TCGA Data Access for Integrated Statistical Analysis in R.
Wan YW, Allen GI, Liu Z.
Bioinformatics. 2015 Nov 14. pii: btv677.

CFAssay 1.26.0 – Statistical analysis for the Colony Formation Assay

CFAssay 1.26.0

:: DESCRIPTION

CFAssay provides functions for calculation of linear-quadratic cell survival curves and for ANOVA of experimental 2-way designs along with the colony formation assay.

::DEVELOPER

Herbert Braselmann <braselm at helmholtz-muenchen.de>

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows/ Linux /MacOsX
R/ Bioconductor

:: DOWNLOAD

CFAssay

:: MORE INFORMATION

Citation

CFAssay: statistical analysis of the colony formation assay.
Braselmann H, Michna A, Heß J, Unger K.
Radiat Oncol. 2015 Nov 4;10(1):223. doi: 10.1186/s13014-015-0529-y.

Jstacs 2.3 – Java Framework for Statistical Analysis and Classification of Biological Sequences

Jstacs 2.3

:: DESCRIPTION

Jstacs is an open source Java library, which focuses on the statistical analysis of biological sequences instead. Jstacs comprises an efficient representation of sequence data and provides implementations of many statistical models with generative and discriminative approaches for parameter learning. Using Jstacs, classifiers can be assessed and compared on test datasets or by cross-validation experiments evaluating several performance measures.

::DEVELOPER

Jstacs Team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows / Linux/ MacOSX
Java

:: DOWNLOAD

Jstacs

:: MORE INFORMATION

Citation

Michael Seifert, Marc Strickert, Alexander Schliep and Ivo Grosse
Exploiting prior knowledge and gene distances in the analysis of tumor expression profiles with extended Hidden Markov Models
Bioinformatics (2011) 27 (12): 1645-1652.

metagenomeSeq 1.34.0 – Statistical Analysis of Sparse High-throughput Sequencing data

metagenomeSeq 1.34.0

:: DESCRIPTION

metagenomeSeq is designed to determine features (be it Operational Taxanomic Unit (OTU), species, etc.) that are differentially abundant between two or more groups of multiple samples. metagenomeSeq is designed to address the effects of both normalization and under-sampling of microbial communities on disease association detection and the testing of feature correlations.

::DEVELOPER

HCBravo Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / Windows/ MacOsX
R
BioCOnductor

:: DOWNLOAD

metagenomeSeq

:: MORE INFORMATION

Citation:

Nat Methods. 2013 Dec;10(12):1200-2. doi: 10.1038/nmeth.2658. Epub 2013 Sep 29.
Differential abundance analysis for microbial marker-gene surveys.
Paulson JN1, Stine OC, Bravo HC, Pop M.

mlegp 3.1.8 – Statistical Analysis for Computer Models of Biological Systems

mlegp 3.1.8

:: DESCRIPTION

mlegp (Maximum Likelihood Estimates of Gaussian Processes) is an R package to analyze computer models of complex systems.

::DEVELOPER

Bioinformatics Laboratory at Eastern Connecticut State University.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux/windows / MacOsX
R Package

:: DOWNLOAD

mlegp

:: MORE INFORMATION

Citation

Dancik GM, Dorman KS (2007)
mlegp: statistical analysis for computer models of biological systems using R.
Bioinformatics (2008) 24 (17): 1966-1967.

Geneland 4.0.6 – Statistical Analysis of Population Genetics data

Geneland 4.0.6

:: DESCRIPTION

Geneland is a computer program for statistical analysis of population genetics data. Its main goal is to detect population structure in form of systematic variation of allele frequency that can be detected from departure from Hardy-Weinberg and linkage equilibrium.

::DEVELOPER

Gilles Guillot

:: SCREENSHOTS

:: REQUIREMENTS

Linux / Windows/ MacOsX
R package

:: DOWNLOAD

Geneland

:: MORE INFORMATION

Citation

G. Guillot, Mortier, F., Estoup, A.
Geneland: a computer package for landscape genetics
Molecular Ecology Notes, 5, 712-715, 2005.

ENViz 3.1.5 – Integrated Statistical Analysis and Visualization of Sample-Matched Data with Multiple Data Types

ENViz 3.1.5

:: DESCRIPTION

ENViz (Enrichment Analysis and Visualization) is a Cytoscape app that performs joint enrichment analysis of two types of sample matched datasets in the context of systematic annotations.

::DEVELOPER

Agilent Laboratories

:: SCREENSHOTS

:: REQUIREMENTS

Windows / Linux / MacOsX
Java
Cytoscape

:: DOWNLOAD

ENViz

:: MORE INFORMATION

Citation

ENViz: a Cytoscape App for integrated statistical analysis and visualization of sample-matched data with multiple data types.
Steinfeld I, Navon R, Creech ML, Yakhini Z, Tsalenko A.
Bioinformatics. 2015 Jan 9. pii: btu853