Tag: Data Sets

Abacus 20160720 – Extracting Spectral Counts from MS/MS Data Sets.

Abacus 20160720

:: DESCRIPTION

Abacus is a tool for extracting adjusted spectral counts from the result XML files generated by the Trans-Proteomic Pipeline (TPP). Abacus outputs a tab-delimited file that can be used for label-free quantification or simply viewing proteomics results across multiple experimental runs.

::DEVELOPER

Proteomics & Integrative Bioinformatics Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOs
  • Java

:: DOWNLOAD

Abacus 

:: MORE INFORMATION

Citation:

Proteomics. 2011 Apr;11(7):1340-5. doi: 10.1002/pmic.201000650. Epub 2011 Feb 17.
Abacus: a computational tool for extracting and pre-processing spectral count data for label-free quantitative proteomic analysis.
Fermin D, Basrur V, Yocum AK, Nesvizhskii AI.

SiteSampler 1.1 – Sample Sites of Sequence Alignment to Produce Replicate Data Sets

SiteSampler 1.1

:: DESCRIPTION

SiteSampler is a Java application that can sample the sites of a sequence alignment to produce replicate data sets.

::DEVELOPER

the Molecular Ecology, Evolution, and Phylogenetics (MEEP) Lab in the School of Biological Sciences

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • Java

:: DOWNLOAD

 SiteSampler

:: MORE INFORMATION

Citation

Ho SYW, and Lanfear R (2010)
Improved characterization of among-lineage rate variation in cetacean mitogenomes using codon-partitioned relaxed clocks.
Mitochondrial DNA, 21: 138-146.

HattCI 200160218 – Identification of attC sites in large DNA data sets

HattCI 200160218

:: DESCRIPTION

HattCI is a C-program for the identification of attC sites in any type of DNA data. It uses a hidden Markov model (HMM) to describe each part of the attC site in a probabilistic manner.

::DEVELOPER

HattCI team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

  HattCI

:: MORE INFORMATION

Citation:

HattCI: Fast and Accurate attC site Identification Using Hidden Markov Models.
Pereira MB, Wallroth M, Kristiansson E, Axelson-Fisk M.
J Comput Biol. 2016 Jul 18.

Correlate 1.03 – Integrative Analysis of 2 Genomic Data Sets

Correlate 1.03

:: DESCRIPTION

Correlate is an Excel plug-in for performing an integrative analysis of two genomic data sets.

If two sets of assays (e.g. gene expression and DNA copy number) have been performed on the same set of patient samples then sparse CCA can be used to find a set of variables in assay 1 that is maximally correlated with a set of variables in assay 2.

::DEVELOPER

Sam Gross / Balasubramanian Narasimhan / Robert Tibshirani /Daniela Witten

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

Correlate

:: MORE INFORMATION

paper: Witten DM, Tibshirani R, and T Hastie (2009) A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis. Biostatistics 10(3): 515-534

Venn Mapper 1.01 – Compare Heterologous Microarray Data Sets

Venn Mapper 1.01

:: DESCRIPTION

Venn Mapper is a program that cluster heterologous microarray data based on the number of co-occurring differentially expressed genes. The application loads microarray data (gene expression ratios) and determines which genes are up- or down-regulated by a user-defined ratio cut-off level. For each experiment, lists of differentially expressed genes are computed. Every list will be compared to every other list, and the number of co-occurring genes will be calculated. With the use of the binomial distribution, so called z-values can be assigned to the overlap found between two lists. The z-values can be directly imported into the Cluster and/or TreeView software.

::DEVELOPER

Marcel Smid

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows/ Other OS with Perl

:: DOWNLOAD

Venn Mapper for Win ; Perl Resource Code

:: MORE INFORMATION

Citation:

M. Smid ,L.C.J. Dorssers, G. Jenster, Venn Mapping: clustering of heterologous microarray data based on the number of co-occurring differentially expressed genes, Bioinformatics (2003) 19 (16): 2065-2071.