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:...
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...
hibberdlab.com - Transrate is software for de-novo transcriptome assembly quality analysis. It examines your assembly in detail and compares it to experimental evidence such as the sequencing reads, reporting quality scores for contigs and assemblies. This...
arthropods.eugenes.org - EvidentialGene is a genome informatics project, "Evidence Directed Gene Construction for Eukaryotes", to construct high quality, accurate gene sets for animals and plants, developed by Don Gilbert at Indiana University,...
github.com - Hagfish is a tool that is to be used in data analysis of Next Generation Sequencing (NGS) experiments. Hagfish builds on the concept of coverage plots and aims to assist (amongst others) in quality control of de novo genome assembly or...
biochem218.stanford.edu - Excellent article to introduce different sequencing methods along with tools for de novo assembly of sequencing reads and their relevant references.
Title: Comparison of Short Read De Novo Alignment Algorithms
Author: Nikhil Gopal
ftp.genomics.org.cn - An efficient tool called Connecting Overlapped Pair-End (COPE) reads, to connect overlapping pair-end reads using k-mer frequencies. We evaluated our tool on 30× simulated pair-end reads from Arabidopsis thaliana with 1% base error. COPE...