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Batch effect detection and correction in RNA-seq data using machine-learning-based automated assessment of quality

BMC bioinformatics, 2022-07, Vol.23 (Suppl 6), p.1-279, Article 279

2022

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Propensity scores as a novel method to guide sample allocation and minimize batch effects during the design of high throughput experiments

BMC bioinformatics, 2023-03, Vol.24 (1), p.86-86, Article 86

2023

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A comparison of batch effect removal methods for enhancement of prediction performance using MAQC-II microarray gene expression data

The pharmacogenomics journal, 2010-08, Vol.10 (4), p.278-291

2010

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Extent, impact, and mitigation of batch effects in tumor biomarker studies using tissue microarrays

eLife, 2021-12, Vol.10

2021

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A comparison of methods accounting for batch effects in differential expression analysis of UMI count based single cell RNA sequencing

Computational and structural biotechnology journal, 2020-01, Vol.18, p.861-873

2020

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A benchmark of batch-effect correction methods for single-cell RNA sequencing data

Genome Biology, 2020-01, Vol.21 (1), p.12-12, Article 12

2020

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Batch Effect Adjustment to Lower the Drug Attrition Rate of MCF-7 Breast Cancer Cells Exposed to Silica Nanomaterial-Derived Scaffolds

Assay and drug development technologies, 2021-01, Vol.19 (1), p.46-61

2021

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Mass-Spectrometry-Based Food Metabolomics in Routine Applications: A Basic Standardization Approach Using Housekeeping Metabolites for the Authentication of Asparagus

Journal of agricultural and food chemistry, 2020-12, Vol.68 (49), p.14343-14352

2020

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Evaluating and minimizing batch effects in metabolomics

Mass spectrometry reviews, 2022-05, Vol.41 (3), p.421-442

2022

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Using control genes to correct for unwanted variation in microarray data

Biostatistics (Oxford, England), 2012-07, Vol.13 (3), p.539-552

2012

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Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis

Current Protocols in Bioinformatics, 2016-09, Vol.55 (1), p.14.10.1-14.10.91

2016

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Harmonizing multisite data with the ComBat method for enhanced Parkinson's disease diagnosis via DAT-SPECT

Frontiers in neurology, 2024-02, Vol.15, p.1306546-1306546

2024

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Comparative analysis of methods for batch correction in proteomics — a two-batch case

Biological Communications, 2023-05, Vol.68 (1)

2023

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Why Batch Effects Matter in Omics Data, and How to Avoid Them

Trends in biotechnology (Regular ed.), 2017-06, Vol.35 (6), p.498-507

2017

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MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics

Metabolites, 2020-05, Vol.10 (5), p.186

2020

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SCDC: bulk gene expression deconvolution by multiple single-cell RNA sequencing references

Briefings in bioinformatics, 2021-01, Vol.22 (1), p.416-427

2021

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Harmonization strategies for multicenter radiomics investigations

Physics in medicine & biology, 2020-12, Vol.65 (24), p.24TR02-24TR02

2020

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CONFOUNDER ADJUSTMENT IN MULTIPLE HYPOTHESIS TESTING

The Annals of statistics, 2017-10, Vol.45 (5), p.1863-1894

2017

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Evaluation of Computational Methods for Single Cell Multi-Omics Integration

Procedia computer science, 2023, Vol.218, p.2744-2754

2023

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Population structure discovery in meta-analyzed microbial communities and inflammatory bowel disease using MMUPHin

Genome Biology, 2022-10, Vol.23 (1), p.208-31, Article 208

2022

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Transcriptional Atlas of Intestinal Immune Cells Reveals that Neuropeptide α-CGRP Modulates Group 2 Innate Lymphoid Cell Responses

Immunity (Cambridge, Mass.), 2019-10, Vol.51 (4), p.696-708.e9

2019

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Overcoming the impacts of two-step batch effect correction on gene expression estimation and inference

Biostatistics (Oxford, England), 2023-07, Vol.24 (3), p.635-652

2023

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A review of recent advances in spatially resolved transcriptomics data analysis

Neurocomputing (Amsterdam), 2024-10, Vol.603, p.128283, Article 128283

2024

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Field and laboratory guidelines for reliable bioinformatic and statistical analysis of bacterial shotgun metagenomic data

Critical reviews in biotechnology, 2024-08, Vol.44 (6), p.1164-1182

2024

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How missing value imputation is confounded with batch effects and what you can do about it

Drug discovery today, 2023-09, Vol.28 (9), p.103661-103661, Article 103661

2023

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Batch effect detection and correction in RNA-seq data using machine-learning-based automated assessment of quality

Propensity scores as a novel method to guide sample allocation and minimize batch effects during the design of high throughput experiments

A comparison of batch effect removal methods for enhancement of prediction performance using MAQC-II microarray gene expression data

Extent, impact, and mitigation of batch effects in tumor biomarker studies using tissue microarrays

A comparison of methods accounting for batch effects in differential expression analysis of UMI count based single cell RNA sequencing

A benchmark of batch-effect correction methods for single-cell RNA sequencing data

Batch Effect Adjustment to Lower the Drug Attrition Rate of MCF-7 Breast Cancer Cells Exposed to Silica Nanomaterial-Derived Scaffolds

Mass-Spectrometry-Based Food Metabolomics in Routine Applications: A Basic Standardization Approach Using Housekeeping Metabolites for the Authentication of Asparagus

Evaluating and minimizing batch effects in metabolomics

Using control genes to correct for unwanted variation in microarray data

Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis

Harmonizing multisite data with the ComBat method for enhanced Parkinson's disease diagnosis via DAT-SPECT

Comparative analysis of methods for batch correction in proteomics — a two-batch case

Why Batch Effects Matter in Omics Data, and How to Avoid Them

MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics

SCDC: bulk gene expression deconvolution by multiple single-cell RNA sequencing references

Harmonization strategies for multicenter radiomics investigations

CONFOUNDER ADJUSTMENT IN MULTIPLE HYPOTHESIS TESTING

Evaluation of Computational Methods for Single Cell Multi-Omics Integration

Population structure discovery in meta-analyzed microbial communities and inflammatory bowel disease using MMUPHin

Transcriptional Atlas of Intestinal Immune Cells Reveals that Neuropeptide α-CGRP Modulates Group 2 Innate Lymphoid Cell Responses

Overcoming the impacts of two-step batch effect correction on gene expression estimation and inference

A review of recent advances in spatially resolved transcriptomics data analysis

Field and laboratory guidelines for reliable bioinformatic and statistical analysis of bacterial shotgun metagenomic data

How missing value imputation is confounded with batch effects and what you can do about it

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