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...
sourceforge.net - Contiguity preserving transposition and sequencing (CPT-seq) is an entirely in vitro means of generating libraries comprised of 9216 indexed pools, each of which contains thousands of sparsely sequenced long fragments ranging from 5 kilobases to...
ftp.ncbi.nih.gov - Now a days there are a lots of genomics databases available around the world. This bookmark is created to provide all links in one place ...
ftp://ftp.ncbi.nih.gov/genomes/
https://hgdownload.soe.ucsc.edu/downloads.html
github.com - MitoHiFi v3.2 is a python pipeline distributed under MIT License !
MitoHiFi was first developed to assemble the mitogenomes for a wide range of species in the Darwin Tree of Life Project...
harvest.readthedocs.io - Harvest is a suite of core-genome alignment and visualization tools for quickly analyzing thousands of intraspecific microbial genomes, including variant calls, recombination detection, and phylogenetic trees.
Tools
Parsnp - Core-genome...
github.com - MECAT is an ultra-fast Mapping, Error Correction and de novo Assembly Tools for single molecula sequencing (SMRT) reads. MECAT employs novel alignment and error correction algorithms that are much more efficient than the state of art of aligners and...
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...
To decide which strategy should be our “preferred” genome assembly approach based on data rather than my gut-feeling about the “best assembly” I decided to do some testing with a known “true” reference E Coli K12 MG1655
github.com - MitoZ is a Python3-based toolkit which aims to automatically filter pair-end raw data (fastq files), assemble genome, search for mitogenome sequences from the genome assembly result, annotate mitogenome (genbank file as result), and mitogenome...