Evidence map›Paper›PMID 24810850›Full record

ArticleNucleic acids research2014

mrsFAST-Ultra: a compact, SNP-aware mapper for high performance sequencing applications.

Faraz Hach, Iman Sarrafi, Farhad Hormozdiari, Can Alkan, Evan E Eichler, S Cenk Sahinalp

Abstract read
In one paragraph

Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed.

  1. Article
  2. Local genetic adaptation to habitat in wild chimpanzees.bioRxiv : the preprint server for biology · 2024
    Article
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  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. Pan-genomics in the human genome era.Nature reviews. Genetics · 2020
    Review
  13. Human-specific tandem repeat expansion and differential gene expression during primate evolution.Proceedings of the National Academy of Sciences of the United States of America · 2019
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Faraz HachSchool of Computing Science, Simon Fraser University, Burnaby, BC, Canada, V5A 1S6 fhach@sfu.ca.
Iman SarrafiSchool of Computing Science, Simon Fraser University, Burnaby, BC, Canada, V5A 1S6.
Farhad HormozdiariComputer Science Department, University of California, Los Angeles, CA, USA, 90095.
Can AlkanDepartment of Computer Engineering, Bilkent University, 06800 Ankara, Turkey.
Evan E EichlerDepartment of Genome Sciences, University of Washington, Seattle, WA, USA, 98195.
S Cenk SahinalpSchool of Computing Science, Simon Fraser University, Burnaby, BC, Canada, V5A 1S6 School of Informatics and Computing, Indiana University, Bloomington, IN, USA, 47405 cenk@sfu.ca.

Funding

Novel algorithms and hardware designs for ultra-fast next-gen sequence analysisR01HG006004 · NHGRI · CARNEGIE-MELLON UNIVERSITY · PI MUTLU, ONUR · 2011 to 2014
$1.4M
NHGRI NIH HHS HG006004
6 · The paper itself

Abstract

High throughput sequencing (HTS) platforms generate unprecedented amounts of data that introduce challenges for processing and downstream analysis. While tools that report the 'best' mapping location of each read provide a fast way to process HTS data, they are not suitable for many types of downstream analysis such as structural variation detection, where it is important to report multiple mapping loci for each read. For this purpose we introduce mrsFAST-Ultra, a fast, cache oblivious, SNP-aware aligner that can handle the multi-mapping of HTS reads very efficiently. mrsFAST-Ultra improves mrsFAST, our first cache oblivious read aligner capable of handling multi-mapping reads, through new and compact index structures that reduce not only the overall memory usage but also the number of CPU operations per alignment. In fact the size of the index generated by mrsFAST-Ultra is 10 times smaller than that of mrsFAST. As importantly, mrsFAST-Ultra introduces new features such as being able to (i) obtain the best mapping loci for each read, and (ii) return all reads that have at most n mapping loci (within an error threshold), together with these loci, for any user specified n. Furthermore, mrsFAST-Ultra is SNP-aware, i.e. it can map reads to reference genome while discounting the mismatches that occur at common SNP locations provided by db-SNP; this significantly increases the number of reads that can be mapped to the reference genome. Notice that all of the above features are implemented within the index structure and are not simple post-processing steps and thus are performed highly efficiently. Finally, mrsFAST-Ultra utilizes multiple available cores and processors and can be tuned for various memory settings. Our results show that mrsFAST-Ultra is roughly five times faster than its predecessor mrsFAST. In comparison to newly enhanced popular tools such as Bowtie2, it is more sensitive (it can report 10 times or more mappings per read) and much faster (six times or more) in the multi-mapping mode. Furthermore, mrsFAST-Ultra has an index size of 2GB for the entire human reference genome, which is roughly half of that of Bowtie2. mrsFAST-Ultra is open source and it can be accessed at http://mrsfast.sourceforge.net.

Indexed as

Polymorphism, Single NucleotideSoftwareGenome, HumanHigh-Throughput Nucleotide SequencingHumansInternetSequence Alignment

Identifiers

PMID24810850
PMCPMC4086126

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.