TIGER 1.02 – Identify Rapidly-evolving Characters in Evolutionary Data

TIGER 1.02

:: DESCRIPTION

TIGER is open source software for identifying rapidly evolving sites (columns in an alignment, or characters in a morphological dataset). It can deal with many kinds of data (molecular, morphological etc.). Sites like these are important to identify as they are very often removed or reweighted in order to improve phylogenetic reconstruction. When a site is changing very quickly between taxa it might not hold much phylogenetic information and therefore might simply be a source of noise. Use of TIGER can (a) allow you to see the amount of rapid evolution and noise in your alignment and (b) provide a quick and easy way to remove as many of the “noisy” sites as possible.

::DEVELOPER

McInerney lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOS
  • Python

:: DOWNLOAD

TIGER

:: MORE INFORMATION

Citation:

Cummins, C.A. and McInerney, J.O. (2011)
A method for inferring the rate of evolution of homologous characters that can potentially improve phylogenetic inference, resolve deep divergence and correct systematic biases.
Systematic Biology 60 (6) 833-844.

DIME 1.2 – Identifying Differential ChIP-seq Based on an Ensemble of Mixture Models

DIME 1.2

:: DESCRIPTION

DIME (Differential Identification using Mixtures Ensemble) is an ensemble of methods for differential analysis. Specifically, it considers an ensemble of finite mixture models combined with a local false discovery rate (fdr) for analyzing ChIP-seq data comparing two samples. This package can also be used to identify differential in other high throughput data such as microarray and DNA methylation.

::DEVELOPER

Statistical Genetics and Bioinformatics Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 DIME

:: MORE INFORMATION

Citation

Taslim, C., Huang, T., and Lin, S. (2011).
DIME: R-package for Identifying Differential ChIP-seq Based on an Ensemble of Mixture Models.
Bioinformatics, 27, 1569-1570.

fineSTRUCTURE 4.0.1 – Identify Population Structure using Dense Sequencing Data

fineSTRUCTURE 4.0.1

:: DESCRIPTION

fineSTRUCTURE is a fast and powerful algorithm for identifying population structure using dense sequencing data.  By using the output of ChromoPainter as a (nearly) sufficient summary statistic, it is able to perform model-based Bayesian clustering on large datasets, including full resequencing data, and can handle up to 1000s of individuals.

::DEVELOPER

Daniel Lawson

:: SCREENSHOTS

fineSTRUCTURE

:: REQUIREMENTS

  • Linux / Windows with  MinGW/ MacOsX

:: DOWNLOAD

  fineSTRUCTURE

:: MORE INFORMATION

Citation

Lawson, Hellenthal, Myers, and Falush (2012),
Inference of population structure using dense haplotype data“,
PLoS Genetics, 8 (e1002453).

PeakSeq 1.31 – Identify and Rank Peak Regions in ChIP-Seq Experiments

PeakSeq 1.31

:: DESCRIPTION

PeakSeq is a program for identifying and ranking peak regions in ChIP-Seq experiments. It takes as input, mapped reads from a ChIP-Seq experiment, mapped reads from a control experiment and outputs a file with peak regions ranked with increasing Q-values.

::DEVELOPER

Gerstein Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 PeakSeq

:: MORE INFORMATION

Citation:

Rozowsky J, Euskirchen G, Auerbach R, Zhang Z, Gibson T, Bjornson R, Carriero N, Snyder M, Gerstein M
PeakSeq enables systematic scoring of ChIP-seq experiments relative to controls
Nature Biotechnology 27, 66 – 75 (2009).

FusionHunter 1.4 – Identify Fusion Transcripts from Transcriptional Analysis of Paired-end RNA-seq

FusionHunter 1.4

:: DESCRIPTION

FusionHunter is a software which reliably identifies fusion transcripts from transcriptional analysis of paired-end RNA-seq. FusionHunter can accurately detect fusions that were previously confirmed by RT-PCR in a publicly available dataset. The purpose of FusionHunter is to identify potential fusions with high sensitivity and specificity and to guide further functional validation in the laboratory.

::DEVELOPER

Ma Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 FusionHunter

:: MORE INFORMATION

Citation

Bioinformatics. 2011 Jun 15;27(12):1708-10. Epub 2011 May 5.
FusionHunter: identifying fusion transcripts in cancer using paired-end RNA-seq.
Li Y, Chien J, Smith DI, Ma J.

NetSeed – Identify the Seed sets of Networks

NetSeed

:: DESCRIPTION

NetSeed is a software package for identifying the seed sets of networks

::DEVELOPER

the Borenstein Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 NetSeed

:: MORE INFORMATION

Citation

Rogan Carr and Elhanan Borenstein (2012)
NetSeed: A network-based reverse-ecology tool for calculating the metabolic interface of an organism with its environment.
Bioinformatics. doi: 10.1093/bioinformatics/btr721.

coMotif 1.0 – Identify Transcription Co-regulator Binding Sites in ChIP-seq Data

coMotif 1.0

:: DESCRIPTION

coMotif is a software of three-component mixture framework to model the joint distribution of two motifs as well as the situation where some sequences contain only one or none of the motifs.

::DEVELOPER

coMotif team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 coMotif 

:: MORE INFORMATION

Citation:

Mengyuan Xu, Clarice R. Weinberg, David M. Umbach and Leping Li
coMOTIF: a mixture framework for identifying transcription factor and a coregulator motif in ChIP-seq Data
Bioinformatics (2011) 27 (19): 2625-2632.

CPL – An approach to identify Protein Complexes

CPL

:: DESCRIPTION

CPL is a graph clustering software, which is designed to detect protein complexes in protein-protein network (PPI). It detects the complexes by propagating labels, which is to simulate the interacting activities of proteins.

::DEVELOPER

NClab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • Java

:: DOWNLOAD

CPL

:: MORE INFORMATION

Citation

Journal of Computer Science and Technology November 2014, Volume 29, Issue 6, pp 1083–1093
CPL: Detecting Protein Complexes by Propagating Labels on Protein-Protein Interaction Network
Qi-Guo DaiMao-Zu GuoEmail authorXiao-Yan LiuZhi-Xia TengChun-Yu Wang

verifyBamID 1.1.3 – Identify Contamination of Sample Swap in Sequence data

verifyBamID 1.1.3

:: DESCRIPTION

verifyBamID is a software that verifies whether the reads in particular file match previously known genotypes for an individual (or group of individuals), and checks whether the reads are contaminated as a mixture of two samples

::DEVELOPER

Abecasis Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
:: DOWNLOAD

 verifyBamID

:: MORE INFORMATION

Citation

G. Jun, M. Flickinger, K. N. Hetrick, Kurt, J. M. Romm, K. F. Doheny, G. Abecasis, M. Boehnke,and H. M. Kang,
Detecting and Estimating Contamination of Human DNA Samples in Sequencing and Array-Based Genotype Data,
Am J Hum Genet. 2012 Nov 2;91(5):839-48. doi: 10.1016/j.ajhg.2012.09.004. (volume 91 issue 5 pp.839 – 848)