github.com - odgi provides an efficient and succinct dynamic DNA sequence graph model, as well as a host of algorithms that allow the use of such graphs in bioinformatic analyses.
Careful encoding of graph entities allows odgi to efficiently...
shendurelab.github.io - LACHESIS is method that exploits contact probability map data (e.g. from Hi-C) for chromosome-scale de novo genome assembly.
Further information about LACHESIS, including source code, documentation and a user's guide are available...
cloud.google.com - Explore genetic variation interactively. Compare entire cohorts in seconds with SQL-like queries. Compute transition/transversion ratios, genome-wide association, allelic frequency and more.
Process big genomic data easily. Run batch analyses...
www.stackage.org - The Bio.SeqLoc modules in seqloc are designed to represent positions and locations (ranges of positions) on sequences, particularly nucleotide sequences. My original motivation for writing these packages was handing the locations of genes in...
bioinformaticsdotca.github.io - In this lab we will perform de novo genome assembly of a bacterial genome. You will be guided through the genome assembly starting with data quality control, through to building contigs and analysis of the results. At the end of the lab you will...
milkweedgenome.org - Some of the useful bioinformatics scripts.
For example ... contig-stats.pl is a Perl script that will automatically describe features of a sequence assembly.
http://milkweedgenome.org/?q=scripts
training.galaxyproject.org - In this tutorial we assemble and annotate the genome of E. coli strain C-1. This strain is routinely used in experimental evolution studies involving bacteriophages. For instance, now classic works by Holly Wichman and Jim Bull (Bull 1997, Bull...
R is a functional based language, the inputs to a function, including options, are in brackets. Note that all dat and options are separated by a comma
Function(data, options)
Even quit is a function
q()
So is...
www.r2d3.us - In machine learning, computers apply statistical learning techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions.
More at http://www.r2d3.us/visual-intro-to-machine-learning-part-1/