github.com - proActiv is an R package that estimates promoter activity from RNA-Seq data. proActiv uses aligned reads and genome annotations as input, and provides absolute and relative promoter activity as output. The package can be used to identify active...
3dgenome.fsm.northwestern.edu - Beside visualizing chromatin interaction data, you can also seamlessly browse other omics data such as ChIP-Seq or RNA-Seq for the same genomic region, and gain a complete view of both regulatory landscape and 3D genome structure for any given gene....
github.com - ContigExtender, was developed to extend contigs, complementing de novo assembly. ContigExtender employs a novel recursive Overlap Layout Candidates (r-OLC) strategy that explores multiple extending paths to achieve longer and highly accurate...
github.com - Phylogenomic Analysis Pipeline for Herbarium Specimens
What is PhyloHerb: PhyloHerb is a wrapper program to process genome skimming data collected from plant materials. The outcomes include the plastid genome (plastome) assemblies,...
Once your research group is ready to make a larger investment and hire a bioinformatician to gain a competitive edge, there are several key traits to seek out in potential candidates. The best bioinformatician are:-
www.well.ox.ac.uk - Platypus is a tool designed for efficient and accurate variant-detection in high-throughput sequencing data. By using local realignment of reads and local assembly it achieves both high sensitivity and high specificity. Platypus can detect...
www.melbournebioinformatics.org.au - Written and maintained by Simon Gladman - Melbourne Bioinformatics (formerly VLSCI)
Protocol Overview / Introduction
In this protocol we discuss and outline the process of de novo assembly for small to medium sized...
www.encodeproject.org - The ENCODE project uses Reference Genomes from NCBI or UCSC to provide a consistent framework for mapping high-throughput sequencing data. In general, ENCODE data are mapped consistently to 2 human (GRCH38, hg19) and 2 mouse...
In today’s era of big biology, we’re generating more data than ever before—genomes, transcriptomes, proteomes, metabolomes, microbiomes… you name it. But raw biological data doesn’t speak for itself. Making sense of it requires more than traditional...