besst.bib

@article{Sahlin02032016,
author = {Sahlin, Kristoffer and Chikhi, Rayan and Arvestad, Lars}, 
title = {Assembly scaffolding with PE-contaminated mate-pair libraries},
year = {2016}, 
doi = {10.1093/bioinformatics/btw064}, 
abstract ={Motivation: Scaffolding is often an essential step in a genome assembly process, in which contigs are ordered and oriented using read pairs from a combination of paired-end libraries and longer-range mate-pair libraries. Although a simple idea, scaffolding is unfortunately hard to get right in practice. One source of problems is so-called PE-contamination in mate-pair libraries, in which a non-negligible fraction of the read pairs get the wrong orientation and a much smaller insert size than what is expected. This contamination has been discussed before, in relation to integrated scaffolders, but solutions rely on the orientation being observable, e.g. by finding the junction adapter sequence in the reads. This is not always possible, making orientation and insert size of a read pair stochastic. To our knowledge, there is neither previous work on modeling PE-contamination, nor a study on the effect PE-contamination has on scaffolding quality.Results: We have addressed PE-contamination in an update to our scaffolder BESST. We formulate the problem as an integer linear program which is solved using an efficient heuristic. The new method shows significant improvement over both integrated and stand-alone scaffolders in our experiments. The impact of modeling PE-contamination is quantified by comparing with the previous BESST model. We also show how other scaffolders are vulnerable to PE-contaminated libraries, resulting in an increased number of misassemblies, more conservative scaffolding and inflated assembly sizes.Availability and implementation: The model is implemented in BESST. Source code and usage instructions are found at https://github.com/ksahlin/BESST. BESST can also be downloaded using PyPI.Contact: ksahlin@kth.seSupplementary information: Supplementary data are available at Bioinformatics online.}, 
URL = {http://bioinformatics.oxfordjournals.org/content/early/2016/03/09/bioinformatics.btw064.abstract}, 
eprint = {http://bioinformatics.oxfordjournals.org/content/early/2016/03/09/bioinformatics.btw064.full.pdf+html}, 
journal = {Bioinformatics} 
}
@article{Sahlin2014,
	author = {Sahlin, K. and Vezzi, F. and Nystedt, B. and Lundeberg, J. and Arvestad, L.},
	title = {{BESST}--efficient scaffolding of large fragmented assemblies.},
	journal = {BMC Bioinformatics},
	volume = {15},
	year = {2014},
	pages = {281},
	pmid = {25128196},
	doi = {10.1186/1471-2105-15-281},
	abstract = {BACKGROUND: The use of short reads from High Throughput Sequencing
(HTS) techniques is now commonplace in de novo assembly. Yet,
obtaining contiguous assemblies from short reads is challenging,
thus making scaffolding an important  step in the assembly pipeline.
Different algorithms have been proposed but many of them use the
number of read pairs supporting a linking of two contigs as an
indicator of reliability. This reasoning is intuitive, but fails
to account for variation in link count due to contig features.We
have also noted that published  scaffolders are only evaluated
on small datasets using output from only one assembler. Two issues
arise from this. Firstly, some of the available tools are not
well suited for complex genomes. Secondly, these evaluations provide
little support for inferring a software's general performance.
RESULTS: We propose a new algorithm, implemented in a tool called
BESST, which can scaffold genomes of all  sizes and complexities
and was used to scaffold the genome of P. abies (20 Gbp).  We
performed a comprehensive comparison of BESST against the most
popular stand-alone scaffolders on a large variety of datasets.
Our results confirm that  some of the popular scaffolders are
not practical to run on complex datasets. Furthermore, no single
stand-alone scaffolder outperforms the others on all datasets.
However, BESST fares favorably to the other tested scaffolders
on GAGE  datasets and, moreover, outperforms the other methods
when library insert size distribution is wide. CONCLUSION: We
conclude from our results that information sources other than
the quantity of links, as is commonly used, can provide useful
information about genome structure when scaffolding.}
}
@article{Sahlin2012,
	author = {Sahlin, K. and Street, N. and Lundeberg, J. and Arvestad, L.},
	title = {Improved gap size estimation for scaffolding algorithms.},
	journal = {Bioinformatics},
	volume = {28},
	number = {17},
	year = {2012},
	month = {Sep},
	pages = {2215-2222},
	pmid = {22923455},
	doi = {10.1093/bioinformatics/bts441},
	abstract = {MOTIVATION: One of the important steps of genome assembly is scaffolding,
in which contigs are linked using information from read-pairs.
Scaffolding provides  estimates about the order, relative orientation
and distance between contigs. We  have found that contig distance
estimates are generally strongly biased and based on false assumptions.
Since erroneous distance estimates can mislead in subsequent analysis,
it is important to provide unbiased estimation of contig distance.
RESULTS: In this article, we show that state-of-the-art programs
for scaffolding are using an incorrect model of gap size estimation.
We discuss why current maximum likelihood estimators are biased
and describe what different cases of bias we are facing. Furthermore,
we provide a model for the distribution of reads that span a gap
and derive the maximum likelihood equation for the gap length.
We motivate why this estimate is sound and show empirically that
it outperforms gap estimators in popular scaffolding programs.
Our results have consequences both for scaffolding software, structural
variation detection and for library insert-size estimation as
is commonly performed by read aligners. AVAILABILITY: A reference
implementation is provided at \verb+https://github.com/SciLifeLab/gapest.+
SUPPLEMENTARY INFORMATION: Supplementary data are availible at
Bioinformatics online.}
}