Evidence map›Paper›PMID 25223782›Full record

ReviewNature reviews. Genetics2014

Identifying and mitigating bias in next-generation sequencing methods for chromatin biology.

Clifford A Meyer, X Shirley Liu

Abstract readReview
In one paragraph

Review in Nature reviews. Genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 184 papers.

0numbers the graph read from it
0cells of the map it votes in
184citing 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

184 citing papers in PubMed.

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  13. Computational Analyses and Challenges of Single-cell ATAC-seq.Genomics, proteomics & bioinformatics · 2025
    Review
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124 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.

Clifford A MeyerDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, Massachusetts 02115, USA; and Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA.
X Shirley LiuDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, Massachusetts 02115, USA; and Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA.

Funding

Inferring Mammalian Transcriptional Regulatory Networks from EpigenomicsR01GM099409 · NIGMS · DANA-FARBER CANCER INST · PI LIU, XIAOLE SHIRLEY · 2011 to 2014
$1.4M
NIGMS NIH HHS R01 GM099409NIGMS NIH HHS R01GM099409
6 · The paper itself

Abstract

Next-generation sequencing (NGS) technologies have been used in diverse ways to investigate various aspects of chromatin biology by identifying genomic loci that are bound by transcription factors, occupied by nucleosomes or accessible to nuclease cleavage, or loci that physically interact with remote genomic loci. However, reaching sound biological conclusions from such NGS enrichment profiles requires many potential biases to be taken into account. In this Review, we discuss common ways in which biases may be introduced into NGS chromatin profiling data, approaches to diagnose these biases and analytical techniques to mitigate their effect.

Indexed as

GenomicsArtifactsBiasChromatinChromatin ImmunoprecipitationGenetic LociHigh-Throughput Nucleotide SequencingSequence Analysis, DNAChromatin

Identifiers

PMID25223782
PMCPMC4473780

What OpenQuestion holds

Textmetadata
LicenceTDM
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.