Evidence map›Paper›PMID 24907368›Full record

ArticleBioinformatics (Oxford, England)2014

Preserving biological heterogeneity with a permuted surrogate variable analysis for genomics batch correction.

Hilary S Parker, Jeffrey T Leek, Alexander V Favorov, Michael Considine, Xiaoxin Xia, Sameer Chavan, Christine H Chung, Elana J Fertig

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 91 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
91citing papers in PubMed, 1 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

91 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Phase 2 Trial of Regorafenib in Recurrent/Metastatic Adenoid Cystic Carcinoma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024
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  3. SLC25A4Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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  6. Mechanism of action ofOncology letters · 2025
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  13. Review
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31 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

8 authors.

Hilary S ParkerDepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD 21205, USA, Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow 119333, Russia, Research Institute for Genetics and Selection of Industrial Microorganisms "GosNIIGenetika", Moscow 117545, Russia, Department of Statistics and Biostatistics, Rutgers University, NJ 08854, USA and Division of Allergy & Clinical Immunology, Department of Medicine, Johns Hopkins University, Baltimore, MD 21224, USA.
Jeffrey T LeekDepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD 21205, USA, Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow 119333, Russia, Research Institute for Genetics and Selection of Industrial Microorganisms "GosNIIGenetika", Moscow 117545, Russia, Department of Statistics and Biostatistics, Rutgers University, NJ 08854, USA and Division of Allergy & Clinical Immunology, Department of Medicine, Johns Hopkins University, Baltimore, MD 21224, USA.
Alexander V FavorovDepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD 21205, USA, Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow 119333, Russia, Research Institute for Genetics and Selection of Industrial Microorganisms "GosNIIGenetika", Moscow 117545, Russia, Department of Statistics and Biostatistics, Rutgers University, NJ 08854, USA and Division of Allergy & Clinical Immunology, Department of Medicine, Johns Hopkins University, Baltimore, MD 21224, USA Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD 21205, USA, Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow 119333, Russia, Research Institute for Genetics and Selection of Industrial Microorganisms "GosNIIGenetika", Moscow 117545, Russia, Department of Statistics and Biostatistics, Rutgers University, NJ 08854, USA and Division of Allergy & Clinical Immunology, Department of Medicine, Johns Hopkins University, Baltimore, MD 21224, USA Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD 21205, USA, Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow 119333, Russia, Research Institute for Genetics and Selection of Industrial Microorganisms "GosNIIGenetika", Moscow 117545, Russia, Department of Statistics and Biostatistics, Rutgers University, NJ 08854, USA and Division of Allergy & Clinical Immunology, Department of Medicine, Johns Hopkins University, Baltimore, MD 21224, USA.
Michael ConsidineDepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD 21205, USA, Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow 119333, Russia, Research Institute for Genetics and Selection of Industrial Microorganisms "GosNIIGenetika", Moscow 117545, Russia, Department of Statistics and Biostatistics, Rutgers University, NJ 08854, USA and Division of Allergy & Clinical Immunology, Department of Medicine, Johns Hopkins University, Baltimore, MD 21224, USA.
Xiaoxin XiaDepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD 21205, USA, Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow 119333, Russia, Research Institute for Genetics and Selection of Industrial Microorganisms "GosNIIGenetika", Moscow 117545, Russia, Department of Statistics and Biostatistics, Rutgers University, NJ 08854, USA and Division of Allergy & Clinical Immunology, Department of Medicine, Johns Hopkins University, Baltimore, MD 21224, USA.
Sameer ChavanDepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD 21205, USA, Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow 119333, Russia, Research Institute for Genetics and Selection of Industrial Microorganisms "GosNIIGenetika", Moscow 117545, Russia, Department of Statistics and Biostatistics, Rutgers University, NJ 08854, USA and Division of Allergy & Clinical Immunology, Department of Medicine, Johns Hopkins University, Baltimore, MD 21224, USA.
Christine H ChungDepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD 21205, USA, Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow 119333, Russia, Research Institute for Genetics and Selection of Industrial Microorganisms "GosNIIGenetika", Moscow 117545, Russia, Department of Statistics and Biostatistics, Rutgers University, NJ 08854, USA and Division of Allergy & Clinical Immunology, Department of Medicine, Johns Hopkins University, Baltimore, MD 21224, USA.
Elana J FertigDepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD 21205, USA, Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow 119333, Russia, Research Institute for Genetics and Selection of Industrial Microorganisms "GosNIIGenetika", Moscow 117545, Russia, Department of Statistics and Biostatistics, Rutgers University, NJ 08854, USA and Division of Allergy & Clinical Immunology, Department of Medicine, Johns Hopkins University, Baltimore, MD 21224, USA.

Funding

TUMOR SUPPRESOR GENE PROMOTER HYPERMETHYLATION FOR DETECTION OF HEAD AND NECKP50DE019032 · NIDCR · JOHNS HOPKINS UNIVERSITY · PI WESTRA, WILLIAM H · 2007 to 2016
$27.1M
Preprocessing and Analysis Tools for High-Throughput TechnologiesR01GM083084 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI IRIZARRY, RAFAEL ANGEL · 2007 to 2018
$4.4M
Molecular signatures of HNSCC in response to targeted therapiesR01DE017982 · NIDCR · VANDERBILT UNIVERSITY · PI CHUNG, CHRISTINE H · 2007 to 2011
$1.9M
Dynamical Models of Cetuximab Resistance in HNSCC Based on Serial Genomics DataR01CA177669 · NCI · JOHNS HOPKINS UNIVERSITY · PI FERTIG, ELANA · 2014 to 2019
$1.8M
Statistical models for biological and technical variation in RNA sequencingR01GM105705 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI LEEK, JEFFREY T. · 2013 to 2017
$1.5M
Identifying Malignant Cell Signaling from Protein Interactions an Polyomic DataK25CA141053 · NCI · JOHNS HOPKINS UNIVERSITY · PI FERTIG, ELANA · 2010 to 2014
$419k
NCI NIH HHS CA141053NCI NIH HHS K25 CA141053NIDCR NIH HHS DE017982NIDCR NIH HHS R01 DE017982
6 · The paper itself

Abstract

motivationSample source, procurement process and other technical variations introduce batch effects into genomics data. Algorithms to remove these artifacts enhance differences between known biological covariates, but also carry potential concern of removing intragroup biological heterogeneity and thus any personalized genomic signatures. As a result, accurate identification of novel subtypes from batch-corrected genomics data is challenging using standard algorithms designed to remove batch effects for class comparison analyses. Nor can batch effects be corrected reliably in future applications of genomics-based clinical tests, in which the biological groups are by definition unknown a priori.

resultsTherefore, we assess the extent to which various batch correction algorithms remove true biological heterogeneity. We also introduce an algorithm, permuted-SVA (pSVA), using a new statistical model that is blind to biological covariates to correct for technical artifacts while retaining biological heterogeneity in genomic data. This algorithm facilitated accurate subtype identification in head and neck cancer from gene expression data in both formalin-fixed and frozen samples. When applied to predict Human Papillomavirus (HPV) status, pSVA improved cross-study validation even if the sample batches were highly confounded with HPV status in the training set. AVAILABILITY AND IMPLEMENTATION: All analyses were performed using R version 2.15.0. The code and data used to generate the results of this manuscript is available from https://sourceforge.net/projects/psva.

Indexed as

AlgorithmsArtifactsComputational BiologyGenomicsHead and Neck NeoplasmsHumansModels, StatisticalPapillomavirus InfectionsReproducibility of ResultsSoftware

Identifiers

PMID24907368
PMCPMC4173013

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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.