L-Measure 5.3 – Extract quantitative Morphological Measurements from Neuronal Reconstructions

L-Measure 5.3

:: DESCRIPTION

L-Measure allows researchers to extract quantitative morphological measurements from neuronal reconstructions. Neuronal reconstructions are typically obtained from brightfield or fluorescence microscopy preparations using applications such as Neurolucida, Eutectic, or Neuron_Morpho, or can be synthesized via computational simulations. Several hundreds neuronal reconstructions are freely available to the neuroscience community (via web archives and peer-to-peer exchange) from a dozen of laboratories.

::DEVELOPER

Sridevi Polavaram

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows / Linux / MacOsX
  • Java

:: DOWNLOAD

  L-Measure

:: MORE INFORMATION

Citation:

Scorcioni R., Polavaram S., Ascoli G.:
L-Measure: a web-accessible tool for the analysis, comparison and search of digital reconstructions of neuronal morphologies.
Nature Prot. 3:866-76 (2008).

EasyFRAP – Quantitative and Qualitative Analysis of FRAP data

EasyFRAP

:: DESCRIPTION

EasyFRAP assists quantitative and qualitative analysis of FRAP data.The user can handle simultaneously large datasets of raw data, visualize fluorescence recovery curves, exclude low quality data, perform data normalization, extract quantitative parameters, perform batch analysis and save the resulting data and figures for further analysis.

::DEVELOPER

the Cell Cycle Laboratory at the School of Medicine, University of Patras.

:: SCREENSHOTS

EasyFRAP

:: REQUIREMENTS

  • Windows / Linux/ MacOsX
  • MatLab

:: DOWNLOAD

 EasyFRAP

:: MORE INFORMATION

Citation

Bioinformatics. 2012 Jul 1;28(13):1800-1. doi: 10.1093/bioinformatics/bts241. Epub 2012 Apr 27.
easyFRAP: an interactive, easy-to-use tool for qualitative and quantitative analysis of FRAP data.
Rapsomaniki MA1, Kotsantis P, Symeonidou IE, Giakoumakis NN, Taraviras S, Lygerou Z.

E-MAPs 1.1 – Imputing Quantitative Genetic Interactions

E-MAPs 1.1

:: DESCRIPTION

E-MAPs (Epistatic miniarray profiles) are a high-throughput approach capable of quantifying aggravating or alleviating genetic interactions between gene pairs. The datasets resulting from E-MAP experiments typically take the form of a symmetric pairwise matrix of interaction scores. These datasets have a significant number of missing values – up to 35% – that can reduce the effectiveness of some data analysis techniques and prevent the use of others.

::DEVELOPER

the Machine Learning Group (MLG)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows /Mac OsX
  • Python

:: DOWNLOAD

 E-MAPs

:: MORE INFORMATION

Citation

Missing value imputation for epistatic MAPs
Colm Ryan , Derek Greene , Gerard Cagney and Pádraig Cunningham
BMC Bioinformatics 2010, 11:197 doi:10.1186/1471-2105-11-197

hapQTL 0.99 – Haplotype Quantitative Loci

hapQTL 0.99

:: DESCRIPTION

hapQTL performs association testing between local haplotypes and phenotypes at each core marker.

::DEVELOPER

Yongtao Guan

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Mac

:: DOWNLOAD

 hapQTL

:: MORE INFORMATION

Citation

Genetics. 2014 Jul;197(3):823-38. doi: 10.1534/genetics.114.164814. Epub 2014 May 8.
Detecting local haplotype sharing and haplotype association.
Xu H, Guan Y

EBprot 1.1.1 – Bayesian Analysis of labeling-based Quantitative Proteomics Data

EBprot 1.1.1

:: DESCRIPTION

EBprot is a novel probabilistic framework that directly models the peptide-protein hierarchy and rewards the proteins with reproducible evidence of DE over multiple peptides.

::DEVELOPER

EBprot team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Mac OsX / Windows
  • R

:: DOWNLOAD

 EBprot

:: MORE INFORMATION

Citation

EBprot: Statistical analysis of labeling-based quantitative proteomics data.
Koh HW, Swa HL, Fermin D, Ler SG, Gunaratne J, Choi H.
Proteomics. 2015 Aug;15(15):2580-91. doi: 10.1002/pmic.201400620.

Oqtans 0.1 beta – Online Quantitative Transcriptome Analysis

Oqtans 0.1 beta

:: DESCRIPTION

Oqtans is an integrative online platform for quantitatively analyzing RNA-Seq experiments. It is based on the Galaxy-framework and provides tools for read mapping, transcript reconstruction and quantitation as well as differential expression analysis

::DEVELOPER

the Biomedical Informatics Lab of Prof. Dr. Gunnar Rätsch

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/MacOsX

:: DOWNLOAD

 Oqtans

:: MORE INFORMATION

Citation:

Oqtans: the RNA-seq workbench in the cloud for complete and reproducible quantitative transcriptome analysis.
Sreedharan VT, Schultheiss SJ, Jean G, Kahles A, Bohnert R, Drewe P, Mudrakarta P, Görnitz N, Zeller G, Rätsch G.
Bioinformatics. 2014 May 1;30(9):1300-1. doi: 10.1093/bioinformatics/btt731.

QTDT 2.6.1 – Linkage Disequilibrium Analysis for Quantitative and Discrete Traits

QTDT 2.6.1

:: DESCRIPTION

QTDT (Quantitative and Discrete Traits) provides a convenient one-stop interface for family based tests of linkage disequilibrium. The general models can be used to analyse quantitative or discrete traits in nuclear families, with or without parental genotypes, or extended pedigrees. In addition, QTDT can calculate exact p-values by permutation even when multiple linked polymorphisms are tested.

::DEVELOPER

Abecasis Lab

:: SCREENSHOTS

Command Line

:: REQUIREMENTS

  • Windows / Mac /  Linux

:: DOWNLOAD

QTDT

:: MORE INFORMATION

Citation:

Abecasis GR, Cardon LR and Cookson WO
A General Test of Association for Quantitative Traits in Nuclear Families.
Am J Hum Genet (2000) 66:279-292

Abecasis GR, Cookson WO and Cardon LR
Pedigree tests of transmission disequilibrium.
Eur J Hum Genet (2000) 8:545-51

If you decide to use QTDT, please take a minute to register.

MAPDIA 3.1.0 – Model-based Analysis of quantitative Proteomics data in DIA-MS

MAPDIA 3.1.0

:: DESCRIPTION

mapDIA performs essential data preprocessing, including novel retention time-based normalization method and a sequence of peptide/fragment selection steps, and more importantly, hierarchical model-based statistical significance analysis for multi-group comparisons under representative experimental designs.

::DEVELOPER

Proteomics & Integrative Bioinformatics Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • C++ Compiler

:: DOWNLOAD

 MAPDIA

:: MORE INFORMATION

Citation

mapDIA: Preprocessing and Statistical Analysis of Quantitative Proteomics Data from Data Independent Acquisition Mass Spectrometry.
Teo G, Kim S, Tsou CC, Collins B, Gingras AC, Nesvizhskii AI, Choi H.
J Proteomics. 2015 Sep 14. pii: S1874-3919(15)30130-5. doi: 10.1016/j.jprot.2015.09.013

PhosphoSiteAnalyzer 1.4 – Bioinformatical tool for Analyzing (Quantitative) Phosphoproteome datasets

PhosphoSiteAnalyzer 1.4

:: DESCRIPTION

PhosphoSiteAnalyzer is a novel bioinformatical tool for analyzing (quantitative) phosphoproteome datasets. The program retrieves kinase-substrate predictions from NetworKIN (Linding et al) and contains various statistical modules for futher analysis.

::DEVELOPER

PhosphoSiteAnalyzer team

:: SCREENSHOTS

PhosphoSiteAnalyzer

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

  PhosphoSiteAnalyzer

:: MORE INFORMATION

Citation

PhosphoSiteAnalyzer: a bioinformatic platform for deciphering phospho proteomes using kinase predictions retrieved from NetworKIN.
Bennetzen MV, Cox J, Mann M, Andersen JS.
J Proteome Res. 2012 Jun 1;11(6):3480-6. doi: 10.1021/pr300016e.

Q-Gene 1.2 – Process Quantitative Real-time RT-PCR Data

Q-Gene 1.2

:: DESCRIPTION

Q-Gene is an application for the processing of quantitative real-time RT–PCR data. It offers the user the possibility to freely choose between two principally different procedures to calculate normalized gene expressions as either means of Normalized Expressions or Mean Normalized Expressions. In this contribution it will be shown that the calculation of Mean Normalized Expressions has to be used for processing simplex PCR data, while multiplex PCR data should preferably be processed by calculating Normalized Expressions. The two procedures, which are currently in widespread use and regarded as more or less equivalent alternatives, should therefore specifically be applied according to the quantification procedure used.

::DEVELOPER

Perikles Simon

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows
  • Microsoft Excel

:: DOWNLOAD

 Q-Gene

:: MORE INFORMATION

Citation

Simon P.
Q-Gene: processing quantitative real-time RT-PCR data.
Bioinformatics. 2003 Jul 22;19(11):1439-40.