Evidence map›Paper›PMID 28884399›Full record

ArticleMarine biotechnology (New York, N.Y.)2017

Bias and Correction in RNA-seq Data for Marine Species.

Kai Song, Li Li, Guofan Zhang

Abstract read
PubMed Publisher
In one paragraph

Article in Marine biotechnology (New York, N.Y.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Identification ofFrontiers in molecular biosciences · 2025
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  4. Significance ofPeerJ · 2024
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  6. Transcriptome Analysis Reveals the Response Mechanism ofInternational journal of molecular sciences · 2022
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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

3 authors.

Kai SongKey Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, 7th Nanhai Rd, Qingdao, Shandong, 266071, China.
Li LiKey Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, 7th Nanhai Rd, Qingdao, Shandong, 266071, China. lili@qdio.ac.cn.
Guofan ZhangKey Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, 7th Nanhai Rd, Qingdao, Shandong, 266071, China. gzhang@qdio.ac.cn.

Funding

National Natural Science Foundation of China 31530079National Natural Science Foundation of China 31572620
6 · The paper itself

Abstract

RNA-seq is a recently developed approach widely used for transcriptome profiling in biological analyses that use next-generation sequencing technologies. Accurate estimation of gene expression levels is critical for answering biological questions. Here, we show that the commonly used measure of gene expression levels, fragments per kilobase of transcript per million mapped reads (FPKM), is biased in transcript length, GC content, and dinucleotide frequencies in the RNA-seq analysis of marine species. We used a generalized linear model to correct the observed biases of FPKM. We used RNA-seq data sets from eight species obtained by different sequencing methods to evaluate the correction methods. Our work contributes to the understanding of potential technical artifacts in RNA-seq experiments for marine species, and presents a means by which more accurate gene expression measures can be obtained.

Indexed as

AnimalsAquatic OrganismsBivalviaDrosophila melanogasterFemaleFishesGene Expression ProfilingHigh-Throughput Nucleotide SequencingHumansMaleRNASequence Analysis, RNARNAGC contentGene expressionRNA-seq analysis biasTranscriptome profiling

Identifiers

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.