Evidence map›Paper›PMID 26112292›Full record

ArticleBioinformatics (Oxford, England)2015

damidseq_pipeline: an automated pipeline for processing DamID sequencing datasets.

Owen J Marshall, Andrea H Brand

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers.

0numbers the graph read from it
0cells of the map it votes in
93citing 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

93 citing papers in PubMed.

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  19. Damsel: analysis and visualisation of DamID sequencing in R.Bioinformatics (Oxford, England) · 2024
    Article
  20. Article

33 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.

Owen J MarshallWellcome Trust/Cancer Research UK Gurdon Institute, Cambridge, CB2 1QN, UK.
Andrea H BrandWellcome Trust/Cancer Research UK Gurdon Institute, Cambridge, CB2 1QN, UK.

Funding

Biotechnology and Biological Sciences Research Council BB/L00786X/1Cancer Research UK C6946/A14492Wellcome Trust 092096Wellcome Trust 092545Wellcome Trust 103792
6 · The paper itself

Abstract

unlabelledDamID is a powerful technique for identifying regions of the genome bound by a DNA-binding (or DNA-associated) protein. Currently, no method exists for automatically processing next-generation sequencing DamID (DamID-seq) data, and the use of DamID-seq datasets with normalization based on read-counts alone can lead to high background and the loss of bound signal. DamID-seq thus presents novel challenges in terms of normalization and background minimization. We describe here damidseq_pipeline, a software pipeline that performs automatic normalization and background reduction on multiple DamID-seq FASTQ datasets. AVAILABILITY AND IMPLEMENTATION: Open-source and freely available from http://owenjm.github.io/damidseq_pipeline. The damidseq_pipeline is implemented in Perl and is compatible with any Unix-based operating system (e.g. Linux, Mac OSX). CONTACT: o.marshall@gurdon.cam.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

SoftwareBinding SitesDNA-Binding ProteinsHigh-Throughput Nucleotide SequencingSequence Analysis, DNADNA-Binding Proteins

Identifiers

PMID26112292
PMCPMC4595905

What OpenQuestion 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 OpenQuestion graph.