ArticleNature communications2018
Optimal compressed representation of high throughput sequence data via light assembly.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed.
- OReO: optimizing read order for practical compression.Bioinformatics advances · 2025Article
- A novel approach to T-cell receptor beta chain (TCRB) repertoire encoding using lossless string compression.Bioinformatics (Oxford, England) · 2023Article
- Hamming-shifting graph of genomic short reads: Efficient construction and its application for compression.PLoS computational biology · 2021Article
- Stoichiogenomics reveal oxygen usage bias, key proteins and pathways associated with stomach cancer.Scientific reports · 2019Article
- Tackling the Challenges of FASTQ Referential Compression.Bioinformatics and biology insights · 2019Article
- BdBG: a bucket-based method for compressing genome sequencing data with dynamic de Bruijn graphs.PeerJ · 2018Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors.
Funding
Abstract
The most effective genomic data compression methods either assemble reads into contigs, or replace them with their alignment positions on a reference genome. Such methods require significant computational resources, but faster alternatives that avoid using explicit or de novo-constructed references fail to match their performance. Here, we introduce a new reference-free compressed representation for genomic data based on light de novo assembly of reads, where each read is represented as a node in a (compact) trie. We show how to efficiently build such tries to compactly represent reads and demonstrate that among all methods using this representation (including all de novo assembly based methods), our method achieves the shortest possible output. We also provide an lower bound on the compression rate achievable on uniformly sampled genomic read data, which is approximated by our method well. Our method significantly improves the compression performance of alternatives without compromising speed.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.