BOL

github.com - This is a scaffold assembler designed for stLFR reads[1]. It uses the link-reads information from stLFR reads to assemble contigs to scaffolds. Here is an illustration of this pipeline:  

github.com - SqueezeMeta is a full automatic pipeline for metagenomics/metatranscriptomics, covering all steps of the analysis. SqueezeMeta includes multi-metagenome support allowing the co-assembly of related metagenomes and the retrieval of individual genomes...

As I mentioned earlier, I will keep on posting one Python script per day to introduce you to Python programming. Whether you are an experienced programmer or not, this tutorial is intended for everyone who wishes to learn the Python programming...

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...

converting a VCF file into a FASTA file given a reference sequence

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