Evidence map›Paper›PMID 22449401›Full record

ArticleGenomics, proteomics & bioinformatics2012

Gene2DGE: a Perl package for gene model renewal with digital gene expression data.

Xiaoli Tang, Libin Deng, Dake Zhang, Jiari Lin, Yi Wei, Qinqin Zhou, Xiang Li, Guilin Li, Shangdong Liang

Abstract read
In one paragraph

Article in Genomics, proteomics & bioinformatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Long noncoding RNA (lncRNA): a target in neuropathic pain.Expert opinion on therapeutic targets · 2019
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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

9 authors.

Xiaoli TangFaculty of Basic Medical Science, Nanchang University, Nanchang 330006, China.
Libin Deng
Dake Zhang
Jiari Lin
Yi Wei
Qinqin Zhou
Xiang Li
Guilin Li
Shangdong Liang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For transcriptome analysis, it is critical to precisely define all the transcripts across the whole genome. More and more digital gene expression (DGE) scannings have indicated the presence of huge amount of novel transcripts in addition to the known gene models. However, almost all these studies still depend crucially on existing annotation. Here, we present Gene2DGE, a Perl software package for gene model renewal with DGE data. We applied Gene2DGE to the mouse blastomere transcriptome, and defined 98,532 read-enriched regions (RERs) by read clustering supported by more than four reads for each base pair. Taking advantage of this ab initio method, we refined 2,104 exonic regions (4% of a total of 48,501 annotated transcribed regions) with remarkable extension into un-annotated regions (>50 bp). For 5% of uniquely mapped reads falling within intron regions, we identified 13,291 additional possible exons. As a result, we renewed 4,788 gene models, which account for 39% of a total of 12,277 transcribed genes. Furthermore, we identified 12,613 intergenic RERs, suggesting the possible presence of novel genes outside the existing gene models. In this study, therefore, we have developed a suitable tool for renewal of known gene models by ab initio prediction in transcriptome dissection. The Gene2DGE package is freely available at http://bighapmap.big.ac.cn/.

Indexed as

Gene Expression ProfilingHigh-Throughput Nucleotide SequencingModels, GeneticSoftwareAnimalsDNA, IntergenicExonsGenomeIntronsMiceTranscriptomeDNA, Intergenic

Identifiers

PMID22449401
PMCPMC5054491

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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.