sourceforge.net - OPERA (Optimal Paired-End Read Assembler) is a sequence assembly program (http://en.wikipedia.org/wiki/Sequence_assembly). It uses information from paired-end/mate-pair/long reads to order and orient the intermediate contigs/scaffolds assembled in a...
http://genomeribbon.com/ - Visualization has played an extremely important role in the current genomic revolution to inspect and understand variants, expression patterns, evolutionary changes, and a number of other relationships. However, most of the information in...
eforge.cs.ucl.ac.uk - The eFORGE tool provides a method to view the tissue specific regulatory component of a set of EWAS DMPs. eFORGE analysis takes a set of DMPs, such as those hits above genome-wide significance threshold in an EWAS study, and analyses whether there...
R Graphical Cookbook by Winston Chang
A very nice book by Winston Chang for R ethusiast. The R code presented in these pages is the R code actually used to produce the Figures in the book. There will be differences compared to the code chunks shown...
github.com - SGA is a de novo genome assembler based on the concept of string graphs. The major goal of SGA is to be very memory efficient, which is achieved by using a compressed representation of DNA sequence reads.
More at
https://github.com/jts/sga
SGA...
cutadapt.readthedocs.io - Cutadapt finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from your high-throughput sequencing reads.
Cutadapt helps with these trimming tasks by finding the adapter or primer sequences in an...
github.com - MeGAMerge
MeGAMerge (A tool to merge assembled contigs, long reads from metagenomic sequencing runs)
Description
MeGAMerge is a perl based wrapper/tool that can accept any number of sequence (FASTA) files containing assembled contigs of any...
www.sequenceontology.org - We have developed the Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome. We envisage its use during annotation jamborees, genome comparison and for use by developers...
www.bioinformatics.babraham.ac.uk - Understanding Following table and graphs
Duplication level
kmer profile
per base GC content
per base N content
per base quality
per base sequence content
per sequence GC content
per sequence quality
sequence length distribution
More at...