github.com - RefKA, a reference-based approach for long read genome assembly. This approach relies on breaking up a closely related reference genome into bins, aligning k-mers unique to each bin with PacBio reads, and then assembling each bin in parallel...
github.com - Often, genome assembly projects have illumina whole genome sequencing reads available for the assembled individual. The k-mer spectrum of this read set can be used for independently evaluating assembly quality without the need of a high quality...
github.com - Despite marked recent improvements in long-read sequencing technology, the assembly of diploid genomes remains a difficult task. A major obstacle is distinguishing between alternative contigs that represent highly heterozygous regions. If primary...
github.com - InfoGenomeR is the Integrative Framework for Genome Reconstruction that uses a breakpoint graph to model the connectivity among genomic segments at the genome-wide scale. InfoGenomeR integrates cancer purity and ploidy, total CNAs, allele-specific...
bioinfologics.github.io - What is a k-mer anyway? A k-mer is just a sequence of k characters in a string (or nucleotides in a DNA sequence). Now, it is important to remember that to get all k-mers from a sequence you need to get...
github.com - MitoZ, consisting of independent modules of de novo assembly, findMitoScaf (find Mitochondrial Scaffolds), annotation and visualization, that can generate mitogenome assembly together with annotation and visualization results from HTS raw...
github.com - With advances in Cancer Genomics, Mutation Annotation Format (MAF) is being widely accepted and used to store somatic variants detected. The Cancer Genome Atlas Project has sequenced over 30 different cancers with sample size of each cancer type...
If we only had Illumina reads, we could also assemble these using the tool Spades.
You can try this here, or try it later on your own data.
Get data
We will use the same Illumina data as we used above:
illumina_R1.fastq.gz: the Illumina...
github.com - The GenomeQC web application is implemented in R/Shiny version 1.5.9 and Python 3.6 and is freely available at https://genomeqc.maizegdb.org/ under the GPL license. All source code and a containerized version of the GenomeQC pipeline is...