Evidence map›Paper›PMID 26854477›Full record

ArticleNature biotechnology2016

Fast search of thousands of short-read sequencing experiments.

Brad Solomon, Carl Kingsford

Abstract read
In one paragraph

Article in Nature biotechnology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers.

0numbers the graph read from it
0cells of the map it votes in
63citing 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

63 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. ganon2: up-to-date and scalable metagenomics analysis.NAR genomics and bioinformatics · 2025
    Article
  8. Article
  9. A survey of k-mer methods and applications in bioinformatics.Computational and structural biotechnology journal · 2024
    Review
  10. The Statistics of Parametrized Syncmers in a Simple Mutation Process Without Spurious Matches.Journal of computational biology : a journal of computational molecular cell biology · 2024
    Article
  11. Article
  12. Compression algorithm for colored de Bruijn graphs.Algorithms for molecular biology : AMB · 2024
    Article
  13. Methods for Pangenomic Core Detection.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  14. Compression Algorithm for Colored de Bruijn Graphs.Algorithms in bioinformatics : ... International Workshop, WABI ..., proceedings. WABI (Workshop) · 2023
    Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article

3 more citing papers are in PubMed but not listed here.

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

2 authors.

Brad SolomonJoint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology, Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
Carl KingsfordComputational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.

Funding

Integrated Interdisciplinary, inter-university PhD Program Computational Biology (T32)T32EB009403 · NIBIB · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BAHAR, IVET, BAR-JOSEPH, ZIV · 2009 to 2023
$4.4M
Algorithms for Managing Uncertainty in Chromosome Conformation Capture DataR01HG007104 · NHGRI · CARNEGIE-MELLON UNIVERSITY · PI KINGSFORD, CARLETON LEE · 2013 to 2015
$1.3M
Fast k-mer Counting to Quantify Gene Expression and Improve Genome AssemblyR21HG006913 · NHGRI · CARNEGIE-MELLON UNIVERSITY · PI KINGSFORD, CARLETON LEE · 2012 to 2014
$430k
NHGRI NIH HHS R01 HG007104NHGRI NIH HHS R01HG007104NHGRI NIH HHS R21 HG006913NHGRI NIH HHS R21HG006913NIBIB NIH HHS T32 EB009403
6 · The paper itself

Abstract

The amount of sequence information in public repositories is growing at a rapid rate. Although these data are likely to contain clinically important information that has not yet been uncovered, our ability to effectively mine these repositories is limited. Here we introduce Sequence Bloom Trees (SBTs), a method for querying thousands of short-read sequencing experiments by sequence, 162 times faster than existing approaches. The approach searches large data archives for all experiments that involve a given sequence. We use SBTs to search 2,652 human blood, breast and brain RNA-seq experiments for all 214,293 known transcripts in under 4 days using less than 239 MB of RAM and a single CPU. Searching sequence archives at this scale and in this time frame is currently not possible using existing tools.

Indexed as

Data MiningAlgorithmsHigh-Throughput Nucleotide SequencingHumansRNASequence Analysis, DNASequence Analysis, RNARNA

Identifiers

PMID26854477
PMCPMC4804353

What OpenQuestion holds

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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.