Evidence map›Paper›PMID 37420172›Full record

ArticleBMC genomics2023

Bioinformatics for wet-lab scientists: practical application in sequencing analysis.

Vera Laub, Kavi Devraj, Lena Elias, Dorothea Schulte

Abstract read
In one paragraph

Article in BMC genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 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

8 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
  6. Review
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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

4 authors.

Vera Laub *Neurological Institute (Edinger Institute), University Hospital Frankfurt, Goethe University, Frankfurt, Germany. vera.laub@kgu.de.
Kavi Devraj *Neurological Institute (Edinger Institute), University Hospital Frankfurt, Goethe University, Frankfurt, Germany.
Lena EliasNeurological Institute (Edinger Institute), University Hospital Frankfurt, Goethe University, Frankfurt, Germany.
Dorothea SchulteNeurological Institute (Edinger Institute), University Hospital Frankfurt, Goethe University, Frankfurt, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenomics data is available to the scientific community after publication of research projects and can be investigated for a multitude of research questions. However, in many cases deposited data is only assessed and used for the initial publication, resulting in valuable resources not being exploited to their full depth. MAIN: A likely reason for this is that many wetlab-based researchers are not formally trained to apply bioinformatic tools and may therefore assume that they lack the necessary experience to do so themselves. In this article, we present a series of freely available, predominantly web-based platforms and bioinformatic tools that can be combined in analysis pipelines to interrogate different types of next-generation sequencing data. Additionally to the presented exemplary route, we also list a number of alternative tools that can be combined in a mix-and-match fashion. We place special emphasis on tools that can be followed and used correctly without extensive prior knowledge in programming. Such analysis pipelines can be applied to existing data downloaded from the public domain or be compared to the results of own experiments.

conclusionIntegrating transcription factor binding to chromatin (ChIP-seq) with transcriptional output (RNA-seq) and chromatin accessibility (ATAC-seq) can not only assist to form a deeper understanding of the molecular interactions underlying transcriptional regulation but will also help establishing new hypotheses and pre-testing them in silico.

Indexed as

Computational BiologyGenomicsChromatin Immunoprecipitation SequencingHigh-Throughput Nucleotide SequencingRNA-SeqATAC-seqChIP-seqIntegrated data analysisRNA-seqTranscriptional networks

Identifiers

PMID37420172
PMCPMC10326960

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.