:: DESCRIPTION
GeneValidator is a tool to identify problematic gene predictions based on comparisons between gene predictions and similar sequences in public databases (e.g., SwissProt).
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
GeneValidator: identify problems with protein-coding gene predictions.
Drăgan MA, Moghul I, Priyam A, Bustos C, Wurm Y.
Bioinformatics. 2016 Jan 18. pii: btw015
:: DESCRIPTION
baySeq identifies differential expression in high-throughput ‘count’ data, such as that derived from next-generation sequencing machines, calculating estimated posterior likelihoods of differential expression (or more complex hypotheses) via empirical Bayesian methods.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Bioinformatics. 2015 Oct 1. pii: btv569.
Generalised empirical Bayesian methods for discovery of differential data in high-throughput biology.
Hardcastle TJ
BMC Bioinformatics. 2010 Aug 10;11:422. doi: 10.1186/1471-2105-11-422.
baySeq: empirical Bayesian methods for identifying differential expression in sequence count data.
Hardcastle TJ, Kelly KA.
:: DESCRIPTION
SNPYGoat Software allows users of the SNPYGoat multiplex system to rapidly identify several goat Y-chromosomal haplotypes Y1A, Y1B, Y1C and Y2 by automatically comparing the obtained profile with a reference database.
::DEVELOPER
:: SCREENSHOTS
: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Pereira F, Carneiro J, Soares P, Maciel S, Nejmeddine F, Lenstra JA, Gusm?o L, Amorim A
A multiplex primer extension assay for the rapid identification of paternal lineages in domestic goat (Capra hircus): laying the foundations for a detailed caprine Y chromosome phylogeny
Molecular Phylogenetics and Evolution. 2008. 49:663-668
:: DESCRIPTION
The OMiMa (the Optimized Mixture Markov model) System is a computational tool for identifying functional motifs in DNA or protein sequences. OMiMa System is based on the Optimized Mixture of Markov models that are able to incorporate most dependencies within a motif. Most important, OMiMa is capable to adjust model complexity according to motif dependency structures, so it can minimize model complexity without compromising prediction accuracy. OMiMa uses our fast Markov chain optimization method, the Directed Neighbor-Joining (DNJ), which makes OMiMa more computationally efficent.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Weichun Huang, David M Umbach, Uwe Ohler, Leping Li.
Optimized mixed Markov models for motif identification.
BMC Bioinformatics 2006, 7:279
:: DESCRIPTION
LaneRuler will identify lanes in a gel image. The lanes on such gels may not be straight and parallel due to various reasons, and these deviations must be accounted for in order to accurately size the restriction fragments in each lane. In order to meet the high throughput requirements by the projects at the British Columbia Cancer Agency Genome Sciences Center (GSC), the software has capability to verify and correct its results automatically, and prompting for user inspection only for extremely abnormal cases. In validation testing using Bacterial Artificial Chromosome (BAC) clones, the automatic lane tracking results gave restriction fragment sizing results that are comparable to those from manually supervised lane tracking results, achieving sensitivity and specificity of restriction fragment identification exceeding 95%. The current conception of the program is able to successfully process 96% of the gels with no human intervention.
::DEVELOPER
Canada’s Michael Smith Genome Sciences Centre
:: SCREENSHOTS
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Wong, R.T.F.; Flibotte, S.; Corbett, R.; Saeedi, P.; Jones, S.J.M.; Marra, M.A.; Schein, J.E.; Birol, I.; (2010 )
LaneRuler: Automated Lane Tracking for DNA Electrophoresis Gel Images
Automation Science and Engineering, IEEE Transactions Volume: 7 Issue:3 706 – 708
:: DESCRIPTION
mapDamage is a computational framework written in Python and R, which tracks and quantifies DNA damage patterns among ancient DNA sequencing reads generated by Next-Generation Sequencing platforms.
::DEVELOPER
The Centre for Anthropobiology and Genomics of Toulouse
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Jónsson H, Ginolhac A, Schubert M, Johnson P, Orlando L.
mapDamage2.0: fast approximate Bayesian estimates of ancient DNA damage parameters.
Bioinformatics (2013) 29 (13): 1682-1684. doi: 10.1093/bioinformatics/btt193
:: DESCRIPTION
Bacterial ID Lab: Use DNA sequencing techniques to identify deadly pathogens.
::DEVELOPER
The Howard Hughes Medical Institute (HHMI)
:: SCREENSHOTS
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
:: 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
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: 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.
:: DESCRIPTION
COSEG is a program which automatically identifies repeat subfamilies using significant co-segregating ( 2-3 bp ) mutations.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
:: 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
:: 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.
