ReviewMolecular bioSystems2009
Scoring overlapping and adjacent signals from genome-wide ChIP and DamID assays.
Review in Molecular bioSystems, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed.
- The H2Bub1-deposition complex is required for human and mouse cardiogenesis.Development (Cambridge, England) · 2023Article
- Bedshift: perturbation of genomic interval sets.Genome biology · 2021Article
- Role of co-repressor genomic landscapes in shaping the Notch response.PLoS genetics · 2017Article
- DamID-seq: Genome-wide Mapping of Protein-DNA Interactions by High Throughput Sequencing of Adenine-methylated DNA Fragments.Journal of visualized experiments : JoVE · 2016Article
- The dilemma of choosing the ideal permutation strategy while estimating statistical significance of genome-wide enrichment.Briefings in bioinformatics · 2014Article
- Exploring the cooccurrence patterns of multiple sets of genomic intervals.BioMed research international · 2013Article
- An effective statistical evaluation of ChIPseq dataset similarity.Bioinformatics (Oxford, England) · 2012Article
- A graphical modelling approach to the dissection of highly correlated transcription factor binding site profiles.PLoS computational biology · 2012Article
- On the use of resampling tests for evaluating statistical significance of binding-site co-occurrence.BMC bioinformatics · 2010Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Much of the research utilising genome-wide ChIP and DamID assays aims to understand the combinatorial feature of transcription factor binding and the chromatin modification code. With these experimental methods becoming more affordable and widespread, the focus of research is shifting to making sense of the data. Amongst the many challenges arising from data analyses, we are concerned with identifying biologically meaningful co-occurrences of transcription factor binding or chromatin modifications, using genome-wide profiles generated from ChIP and DamID assays. Co-occurrences are reflected in overlapping and adjacent signals in multiple ChIP or DamID profiles. We review existing quantitative methods to score overlaps and to cluster binding events in ChIP and DamID profiles. For pairwise comparison, existing methods either are based on a single score at the genome level or take a genomic, region-specific view. To draw inference from many profiles simultaneously, methods exist to cluster regions by their regulatory importance or to infer cis-regulatory modules for a particular region. We provide a simple guide to some of the statistical tools used by these methods.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.