github.com - HiCanu, a significant modification of the Canu assembler designed to leverage the full potential of HiFi reads via homopolymer compression, overlap-based error correction, and aggressive false overlap filtering.
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support.10xgenomics.com - Supernova generates phased, whole-genome de novo assemblies from a Chromium-prepared library.
Please see Achieving Success with De Novo Assembly and System Requirements before creating your Chromium libraries for...
lh3.github.io - Given a de novo assembly, we often measure the “average” contig length by N50. N50 is neither the real average nor median. It is the length of the contig such that this and longer contigs cover at least 50% of the assembly. A...
https://genome10k.soe.ucsc.edu
The Genome 10K project aims to assemble a genomic zoo—a collection of DNA sequences representing the genomes of 10,000 vertebrate species, approximately one for every vertebrate genus. The trajectory of cost reduction...
github.com - Convenient conversions between genome assemblie. The liftover package makes it easy to remap genomic coordinates to a different genome assembly.
More at...
github.com - Trinity, developed at the Broad Institute and the Hebrew University of Jerusalem, represents a novel method for the efficient and robust de novo reconstruction of transcriptomes from RNA-seq data. Trinity combines three independent software modules:...
www.broadinstitute.org - DISCOVAR is a new variant caller and DISCOVAR de novo a new genome assembler, both designed for state-of-the-art data. Their inputs are chosen to optimize quality while keeping costs low. Currently it takes as input Illumina reads of length 250 or...
github.com - Tools for making blobplots or Taxon-Annotated-GC-Coverage plots (TAGC plots) to visualise the contents of genome assembly data sets as a QC step
Blaxter Lab, Institute of Evolutionary Biology, University of Edinburgh
Goal: To create blobplots or...
github.com - HGA tool version 1.0 This tool helps to apply the Hierarchical Genome Assembly (HGA) method. The tool will apply: 1. Partitioning a given reads dataset into a given number of partitions. 2. Assembling each partitions using a pre-specified assembler...