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,...
urgi.versailles.inra.fr - We advise to run first the TEdenovo pipeline but it is not compulsory. We suppose you begin by running the TEannot pipeline on the example provided in the directory "db/" rather than directly on your own genomic sequences. Thus, from now on, the...
github.com - Wtdbg2 is a de novo sequence assembler for long noisy reads produced by PacBio or Oxford Nanopore Technologies (ONT). It assembles raw reads without error correction and then builds the consensus from intermediate assembly output. Wtdbg2...
github.com - This pipeline performs the following steps:
Assembly of nanopore reads using Canu.
Polish canu contigs using racon (optional).
Map a paired-end Illumina dataset onto the contigs obtained in the previous steps...
github.com - dnaPipeTE (for de-novo assembly & annotation Pipeline for Transposable Elements), is a pipeline designed to find, annotate and quantify Transposable Elements in small samples of NGS datasets. It is very useful to quantify the proportion of TEs...
github.com - AlignGraph is a software that extends and joins contigs or scaffolds by reassembling them with help provided by a reference genome of a closely related organism.
Using AlignGraph
AlignGraph --read1 reads_1.fa --read2 reads_2.fa --contig contigs.fa...
github.com - SKESA is a DeBruijn graph-based de-novo assembler designed for assembling reads of microbial genomes sequenced using Illumina. Comparison with SPAdes and MegaHit shows that SKESA produces assemblies that have high sequence quality and contiguity,...
cab.spbu.ru - QUAST-LG is an extension of QUAST intended for evaluating large-scale genome assemblies (up to mammalian-size).
QUAST-LG is included in the QUAST package starting from version 5.0.0 (download the latest release). Run QUAST as...
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