Evidence map›Paper›PMID 29910842›Full record

ArticleThe annals of applied statistics2016

A Hierarchical Framework for State-Space Matrix Inference and Clustering.

Chandler Zuo, Kailei Chen, Kyle J Hewitt, Emery H Bresnick, Sündüz Keleş

Abstract read
In one paragraph

Article in The annals of applied statistics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. A MAD-Bayes Algorithm for State-Space Inference and Clustering with Application to Querying Large Collections of ChIP-Seq Data Sets.Journal of computational biology : a journal of computational molecular cell biology · 2017
    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

5 authors.

Chandler ZuoDepartment of Statistics, University of Wisconsin, Madison, WI, U.S.A.
Kailei ChenDepartment of Statistics, University of Wisconsin, Madison, WI, U.S.A.
Kyle J HewittDepartment of Cell and Regenerative Biology, University of Wisconsin, Madison, WI, U.S.A.
Emery H BresnickDepartment of Cell and Regenerative Biology, University of Wisconsin, Madison, WI, U.S.A.
Sündüz KeleşDepartment of Statistics, University of Wisconsin, Madison, WI, U.S.A.

Funding

TrainingU54AI117924 · NIAID · UNIVERSITY OF WISCONSIN-MADISON · PI CRAVEN, MARK W. · 2014 to 2018
$11.3M
Transcriptional Control of Hemoglobin Synthesis and Erythrocyte DevelopmentR01DK050107 · NIDDK · UNIVERSITY OF WISCONSIN-MADISON · PI Emery H. Bresnick · 1996 to 2026
$6.1M
Statistical Methods for the Analysis of ChlP-chip DataR01HG003747 · NHGRI · UNIVERSITY OF WISCONSIN-MADISON · PI KELES, SUNDUZ · 2007 to 2024
$4.8M
Transcriptional Control of Hemoglobin SynthesisR37DK050107 · NIDDK · UNIVERSITY OF WISCONSIN-MADISON · PI BRESNICK, EMERY H · 2011 to 2020
$3.5M
Statistical Methods For Annotating Repetitive Genomic Regions Through ENCODE-deriU01HG007019 · NHGRI · UNIVERSITY OF WISCONSIN-MADISON · PI BRESNICK, EMERY H, DEWEY, COLIN NOEL · 2012 to 2015
$1.5M
Statistical Power Calculations for ChIP-seq experimentsR21HG006716 · NHGRI · UNIVERSITY OF WISCONSIN-MADISON · PI KELES, SUNDUZ · 2012 to 2013
$368k
NHGRI NIH HHS R01 HG003747NHGRI NIH HHS R21 HG006716NHGRI NIH HHS U01 HG007019NIAID NIH HHS U54 AI117924NIDDK NIH HHS R01 DK050107NIDDK NIH HHS R37 DK050107
6 · The paper itself

Abstract

In recent years, a large number of genomic and epigenomic studies have been focusing on the integrative analysis of multiple experimental datasets measured over a large number of observational units. The objectives of such studies include not only inferring a hidden state of activity for each unit over individual experiments, but also detecting highly associated clusters of units based on their inferred states. Although there are a number of methods tailored for specific datasets, there is currently no state-of-the-art modeling framework for this general class of problems. In this paper, we develop the MBASIC (

Identifiers

PMID29910842
PMCPMC6003413

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Registered trials

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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.