Evidence map›Paper›PMID 30786165›Full record

ArticleCurrent protocols in bioinformatics2019

Integrating Bacterial ChIP-seq and RNA-seq Data With SnakeChunks.

Claire Rioualen, Lucie Charbonnier-Khamvongsa, Julio Collado-Vides, Jacques van Helden

Abstract read
In one paragraph

Article in Current protocols in bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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.

Claire RioualenAix-Marseille University, INSERM, Laboratory of Theory and Approaches of Genome Complexity (TAGC), Marseille, France.
Lucie Charbonnier-KhamvongsaAix-Marseille University, INSERM, Laboratory of Theory and Approaches of Genome Complexity (TAGC), Marseille, France.
Julio Collado-VidesPrograma de Genómica Computacional, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, México.
Jacques van HeldenAix-Marseille University, INSERM, Laboratory of Theory and Approaches of Genome Complexity (TAGC), Marseille, France.

Funding

HIGH THROUGHPUT LITERATURE CURATION OF GENETIC REGULATION IN BACTERIAL MODELSR01GM110597 · NIGMS · CENTER FOR GENOMIC SCIENCES · PI COLLADO-VIDES, JULIO · 2015 to 2018
$1.6M
NIGMS NIH HHS R01 GM110597
6 · The paper itself

Abstract

Next-generation sequencing (NGS) is becoming a routine approach in most domains of the life sciences. To ensure reproducibility of results, there is a crucial need to improve the automation of NGS data processing and enable forthcoming studies relying on big datasets. Although user-friendly interfaces now exist, there remains a strong need for accessible solutions that allow experimental biologists to analyze and explore their results in an autonomous and flexible way. The protocols here describe a modular system that enable a user to compose and fine-tune workflows based on SnakeChunks, a library of rules for the Snakemake workflow engine. They are illustrated using a study combining ChIP-seq and RNA-seq to identify target genes of the global transcription factor FNR in Escherichia coli, which has the advantage that results can be compared with the most up-to-date collection of existing knowledge about transcriptional regulation in this model organism, extracted from the RegulonDB database. © 2019 by John Wiley & Sons, Inc.

Indexed as

RNA-SeqSoftwareBacteriaBase SequenceChromatin Immunoprecipitation SequencingGenome, BacterialNucleotide MotifsUser-Computer InterfaceChIP-seqEscherichia coli K-12FAIR Guiding Principlesreproducible scienceRNA-seqworkflow

Identifiers

PMID30786165
PMCPMC7302399

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.