Search Results for "caller"

Often times, the production system network is inaccessible from the local development environment. If issues are encountered in production systems, it is impossible to use IDEs to debug the application remotely. More importantly, debugging in production environment is unacceptable, as it will suspend all the threads, resulting in the suspension of business services. Developers could always try to reproduce the same issue on the test/staging environment. However, this is tricky as some issues...

Now in Github: https://github.com/dnaase/Bis-tools/tree/master/Bis-SNP BisSNP is a package based on the Genome Analysis Toolkit (GATK) map-reduce framework for genotyping in bisulfite treated massively parallel sequencing (Bisulfite-seq, NOMe-seq and RRBS) on Illumina platform. It uses bayesian inference with either manually specified or automatically estimated methylation probabilities of different cytosine context(not only CpG, CHH, CHG in Bisulfite-seq, but also GCH et.al. in other...

...The aim is to parse a GML document or fragment in order to get a WKT output. 2D and 3D inputs are both handled, but it is not permitted to have mixed geometries. The caller can choose if the input coordinates are parsed as X, Y, Z (if present) order, or Y, X, Z (if present) order. The willing of the project is to be a starting point useful for developers that need to parse GML objects in order to use them, for example, in the context of OGC catalogue projects. The library is compiled using Java 1.5 or 1.6. ...

The Base Calling with Vocabulary (BCV) software package is intended for analysis of direct (population) sequencing chromatograms using known vocabulary sequences similar to the target DNA. The current version of BCV can only process chromatogram files obtained on Applied Biosystems capillary sequencing machines (ABIF file format).

Conrad is both a high performance Conditional Random Field engine which can be applied to a variety of machine learning problems and a specific set of models for gene prediction using semi-Markov CRFs.