BOL

https://cblab.org/camsa/ - CAMSA – is a tool for Comparative Analysis and Merging of Scaffold Assemblies, distributed both as a standalone software package and as Python library under the MIT license. Main features: works with any number of...

bitbucket.org - TAndem REpeat ANalyzer -TAREAN – is a computational pipeline for unsupervised identification of satellite repeats from unassembled sequence reads. The pipeline uses low-pass whole genome sequence reads and performs their...

github.com - BFC is a standalone high-performance tool for correcting sequencing errors from Illumina sequencing data. It is specifically designed for high-coverage whole-genome human data, though also performs well for small genomes. The BFC algorithm is a...

http://higlass.io/ - HiGlass is a tool for exploring genomic contact matrices and tracks. Please take a look at the examples and documentation for a description of the ways that it can be configured to explore and compare contact matrices. To load private data, HiGlass...

www.healthcare.uiowa.edu - Getting Started These simple steps will help you integrate LSC into your transcriptomics analysis pipeline. Read the LSC_requirements for running LSC. Download and set-up the LSC package. Follow the tutorial to see how...

github.com - Here is the command to run the tool: python finisherSC.py destinedFolder mummerPath If you are running on server computer and would like to use multiple threads, then the following commands can generate 20 threads to run FinisherSC. python...

github.com - rHAT is a seed-and-extension-based noisy long read alignment tool. It is suitable for aligning 3rd generation sequencing reads which are in large read length with relatively high error rate, especially Pacbio's Single Molecule Read-time (SMRT)...

www.kegg.jp - KOALA (KEGG Orthology And Links Annotation) is KEGG's internal annotation tool for K number assignment of KEGG GENES using SSEARCH computation. BlastKOALA and GhostKOALA assign K numbers to the user's sequence data...

github.com - It is designed to work with patterned data. Famous examples of problems related to patterned data are: recovering signals in networks after a stimulation (cascade network reverse engineering), analysing periodic signals.

http://efs.heiderlab.de/ - The software EFS (Ensemble Feature Selection) makes use of multiple feature selection methods and combines their normalized outputs to a quantitative ensemble importance. Currently, eight different feature selection methods have been integrated in...