scholarly article | Q13442814 |
P50 | author | Eivind Hovig | Q42063731 |
Einar Andreas Rødland | Q43376294 | ||
P2093 | author name string | Vegard Nygaard | |
P2860 | cites work | Linear models and empirical bayes methods for assessing differential expression in microarray experiments | Q27860758 |
Normalization of cDNA microarray data | Q28181692 | ||
A comparison of batch effect removal methods for enhancement of prediction performance using MAQC-II microarray gene expression data | Q28749765 | ||
Ten simple rules for reproducible computational research | Q28974699 | ||
Adjusting batch effects in microarray expression data using empirical Bayes methods | Q29614937 | ||
Tackling the widespread and critical impact of batch effects in high-throughput data | Q30004214 | ||
Removing batch effects in analysis of expression microarray data: an evaluation of six batch adjustment methods | Q33840779 | ||
Relative impact of key sources of systematic noise in Affymetrix and Illumina gene-expression microarray experiments | Q34088518 | ||
Batch correction of microarray data substantially improves the identification of genes differentially expressed in rheumatoid arthritis and osteoarthritis | Q34298215 | ||
Stratified randomization controls better for batch effects in 450K methylation analysis: a cautionary tale | Q34330573 | ||
The sva package for removing batch effects and other unwanted variation in high-throughput experiments | Q35838453 | ||
Comparing the biological impact of glatiramer acetate with the biological impact of a generic | Q41860072 | ||
Gene expression analysis reveals functional pathways of glatiramer acetate activation. | Q45135279 | ||
P275 | copyright license | Creative Commons Attribution 4.0 International | Q20007257 |
P6216 | copyright status | copyrighted | Q50423863 |
P4510 | describes a project that uses | limma | Q112236343 |
P433 | issue | 1 | |
P407 | language of work or name | English | Q1860 |
P921 | main subject | lead | Q708 |
P304 | page(s) | 29-39 | |
P577 | publication date | 2015-08-13 | |
P1433 | published in | Biostatistics | Q4915301 |
P1476 | title | Methods that remove batch effects while retaining group differences may lead to exaggerated confidence in downstream analyses | |
P478 | volume | 17 |
Q89641922 | A Functional Landscape of CKD Entities From Public Transcriptomic Data |
Q92670241 | A multiomics comparison between endometrial cancer and serous ovarian cancer |
Q50420738 | A personalized, multiomics approach identifies genes involved in cardiac hypertrophy and heart failure. |
Q99551129 | A predictive index for health status using species-level gut microbiome profiling |
Q64089840 | A robust qualitative transcriptional signature for the correct pathological diagnosis of gastric cancer |
Q46245907 | ATTED-II in 2018: A Plant Coexpression Database based on Investigation of Statistical Property of the Mutual Rank Index |
Q92694000 | Accumulating Transcriptome Drift Precedes Cell Aging in Human Umbilical Cord-Derived Mesenchymal Stromal Cells Serially Cultured to Replicative Senescence |
Q54968894 | Adjusting for Batch Effects in DNA Methylation Microarray Data, a Lesson Learned. |
Q55499618 | Aerobic exercise and DNA methylation in postmenopausal women: An ancillary analysis of the Alberta Physical Activity and Breast Cancer Prevention (ALPHA) Trial. |
Q47131388 | Age-related gene expression in luminal epithelial cells is driven by a microenvironment made from myoepithelial cells |
Q58757833 | An ontology-based method for assessing batch effect adjustment approaches in heterogeneous datasets |
Q91763012 | Blind estimation and correction of microarray batch effect |
Q38441002 | Cell Cycle M-Phase Genes Are Highly Upregulated in Anaplastic Thyroid Carcinoma |
Q52371383 | Characterizing the replicability of cell types defined by single cell RNA-sequencing data using MetaNeighbor. |
Q64105484 | Comparative Transcriptome and Methylome Analysis in Human Skeletal Muscle Anabolism, Hypertrophy and Epigenetic Memory |
Q58091192 | Comparison of normalization approaches for gene expression studies completed with high-throughput sequencing |
Q55038642 | Cost-effective generation of precise label-free quantitative proteomes in high-throughput by microLC and data-independent acquisition. |
Q60920342 | DEBrowser: interactive differential expression analysis and visualization tool for count data |
Q64093643 | Data-Driven Analysis of Age, Sex, and Tissue Effects on Gene Expression Variability in Alzheimer's Disease |
Q92072210 | Diagnostic Profiling of the Human Public IgM Repertoire With Scalable Mimotope Libraries |
Q37708870 | Differential expression analysis for individual cancer samples based on robust within-sample relative gene expression orderings across multiple profiling platforms |
Q88617540 | Establishing a Twin Register: An Invaluable Resource for (Behavior) Genetic, Epidemiological, Biomarker, and 'Omics' Studies |
Q91386711 | Feature selection with the Fisher score followed by the Maximal Clique Centrality algorithm can accurately identify the hub genes of hepatocellular carcinoma |
Q51764859 | Genome-wide average DNA methylation is determined in utero. |
Q90613049 | Harmonization of radiomic features of breast lesions across international DCE-MRI datasets |
Q55475012 | Identifying differentially expressed genes from cross-site integrated data based on relative expression orderings. |
Q33683844 | Identifying disease-associated pathways in one-phenotype data based on reversal gene expression orderings |
Q88931978 | In Vitro Pluripotent Stem Cell Differentiation to Hepatocyte Ceases Further Maturation at an Equivalent Stage of E15 in Mouse Embryonic Liver Development |
Q57897433 | Learning and Imputation for Mass-spec Bias Reduction (LIMBR) |
Q42367433 | Letter to the Editor response: Nygaard et al. |
Q58694532 | Machine Learning Predicts the Yeast Metabolome from the Quantitative Proteome of Kinase Knockouts |
Q97520285 | Merging microarray studies to identify a common gene expression signature to several structural heart diseases |
Q61810617 | Multi-study inference of regulatory networks for more accurate models of gene regulation |
Q64069434 | Muscle Gene Sets: a versatile methodological aid to functional genomics in the neuromuscular field |
Q63246330 | Network meta-analysis correlates with analysis of merged independent transcriptome expression data |
Q52646651 | New drug candidates for treatment of atypical meningiomas: An integrated approach using gene expression signatures for drug repurposing. |
Q64105537 | Qualitative transcriptional signatures for evaluating the maturity degree of pluripotent stem cell-derived cardiomyocytes |
Q49247828 | Quantitative or qualitative transcriptional diagnostic signatures? A case study for colorectal cancer. |
Q90726742 | Rapid induction of the heat hardening response in an Arctic insect |
Q36323777 | Reduced dosage of β-catenin provides significant rescue of cardiac outflow tract anomalies in a Tbx1 conditional null mouse model of 22q11.2 deletion syndrome. |
Q38832342 | Removal of batch effects using distribution-matching residual networks. |
Q37682494 | Systems Genetics Approach Identifies Gene Pathways and Adamts2 as Drivers of Isoproterenol-Induced Cardiac Hypertrophy and Cardiomyopathy in Mice |
Q99212853 | Systems-based proteomics to resolve the biology of Alzheimer's disease beyond amyloid and tau |
Q61444678 | Temporal dynamics in meta longitudinal RNA-Seq data |
Q92617764 | Transcriptional Profiling of Stem Cells: Moving from Descriptive to Predictive Paradigms |
Q92669055 | Transcriptome meta-analysis reveals differences of immune profile between eutopic endometrium from stage I-II and III-IV endometriosis independently of hormonal milieu |
Search more.