SuRankCo: supervised ranking of contigs in de novo assemblies (2015) A machine learning approach to predict quality scores for contigs and to enable the ranking of contigs within an assembly. Information on characteristics of contigs from a de novo assembly are extracted by the SuRankCo-Feature module. These features include common characteristics such as length Read more…
The present and future of de novo whole-genome assembly Jang-il Sohn and Jin-Wu Nam ‘Table 1. Summary of short read assemblers’ Speed Memory efficiency N50 length Input data type Assembly steps ‘Table 2. Strategies for challenges’ Assembly approach Sequencing error Complexity reducing Repeat resolving Uneven depth RAM memory ‘Table 3. Comparison Read more…
Computational Methods for Next Generation Sequencing Data Analysis (2016) ION I. MANDOIU ALEXANDER ZELIKOVSKY Page 129 gave out ‘Performance of Different Algorithms on the H. sapiens (chr 14) Data Set (Short + Long)’ (including ScaffMatch SSPACE OPERA SOPRA MIP SCARPA BESST SGA SOAPdenovo2) OPERA performed best. It provided details about SILP2 Read more…
PHRAP 2007 Assembling Genomic DNA Sequences with PHRAP Cold Spring Harbor Laboratory Current protocols in bioinformatics
2010 Sequencing technologies — the next generation Human Genome Sequencing Center and Department of Molecular & Human Genetics, Baylor College of Medicine Nature reviews Demand has never been greater for revolutionary technologies that deliver fast, inexpensive and accurate genome information. This challenge has catalysed the development of next-generation sequencing (NGS) technologies. The inexpensive production Read more…
https://github.com/isovic/racon https://github.com/PacificBiosciences/FALCON https://github.com/marbl/canu 2015 Assembling large genomes with single-molecule sequencing and locality-sensitive hashing Department of Chemistry and Biochemistry, University of Maryland Nature Biotechnology