BOL

Learn about bioinformatics online by watching videos, reading engaging articles and practicing bioinformatics skills using public domain datasets.

Shirley is a computational biologist with expertise in cancer epigenetics. Her research focuses on algorithm development and integrative mining from big data generated on microarrays, massively parallel sequencing, and other high throughput...

Genome browsers are useful not only for showing final results but also for improving analysis protocols, testing data quality, and generating result drafts. Its integration in analysis pipelines allows the optimization of parameters, which...

github.com - A comparative genome scaffolding tool based on MUMmer mScaffolder scaffolds a genome using an existing high quality genome as the reference. It aligns the two genomes using nucmer utility from MUMmer and then orders and orients the contigs of the...

sepsis-omics.github.io - This is a tutorial for a workshop on long-read (PacBio) genome assembly. It demonstrates how to use long PacBio sequencing reads to assemble a bacterial genome, and includes additional steps for circularising, trimming, finding plasmids, and...

World’s first $1,000 genome enables ‘factory’ scale sequencing for population and disease studies

github.com - genome simulation across a population with zeta-distributed allele frequency, snps, insertions, deletions, and multi-nucleotide polymorphisms More at https://github.com/ekg/mutatrix ./mutatrix -S sample -P test/ -p 2 -n 10 reference.fasta

wiki.bits.vib.be - compare two BWA mapping methods with the online hg18-mapped data We first operate a rapid inspection of the different BAM files using samtools flagstat. Illumina provided chr21 read mapping obtained with their GA IIx deep...

There are many R software and bioconductor packages for NGS data analysis, some of them are as follows Biostrings The Biostrings package from Bioconductor provides an advanced environment for efficient sequence management and analysis in R. It...

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...