Comparison of statistical methods and the use of quality control samples for batch effect correction in human transcriptome data
A Espín-Pérez, C Portier, M Chadeau-Hyam… - PloS one, 2018 - journals.plos.org
Batch effects are technical sources of variation introduced by the necessity of conducting
gene expression analyses on different dates due to the large number of biological samples …
gene expression analyses on different dates due to the large number of biological samples …
Removing batch effects from longitudinal gene expression-quantile normalization plus ComBat as best approach for microarray transcriptome data
C Müller, A Schillert, C Röthemeier, DA Trégouët… - PloS one, 2016 - journals.plos.org
Technical variation plays an important role in microarray-based gene expression studies,
and batch effects explain a large proportion of this noise. It is therefore mandatory to …
and batch effects explain a large proportion of this noise. It is therefore mandatory to …
Overcoming the impacts of two-step batch effect correction on gene expression estimation and inference
Nonignorable technical variation is commonly observed across data from multiple
experimental runs, platforms, or studies. These so-called batch effects can lead to difficulty in …
experimental runs, platforms, or studies. These so-called batch effects can lead to difficulty in …
A novel statistical method to diagnose, quantify and correct batch effects in genomic studies
G Nyamundanda, P Poudel, Y Patil, A Sadanandam - Scientific reports, 2017 - nature.com
Genome projects now generate large-scale data often produced at various time points by
different laboratories using multiple platforms. This increases the potential for batch effects …
different laboratories using multiple platforms. This increases the potential for batch effects …
Review of batch effects prevention, diagnostics, and correction approaches
Systematic technical variation in high-throughput studies consisting of the serial
measurement of large sample cohorts is known as batch effects. Batch effects reduce the …
measurement of large sample cohorts is known as batch effects. Batch effects reduce the …
Are batch effects still relevant in the age of big data?
Batch effects (BEs) are technical biases that may confound analysis of high-throughput
biotechnological data. BEs are complex and effective mitigation is highly context-dependent …
biotechnological data. BEs are complex and effective mitigation is highly context-dependent …
Risk-conscious correction of batch effects: maximising information extraction from high-throughput genomic datasets
Y Oytam, F Sobhanmanesh, K Duesing, JC Bowden… - BMC …, 2016 - Springer
Background Batch effects are a persistent and pervasive form of measurement noise which
undermine the scientific utility of high-throughput genomic datasets. At their most benign …
undermine the scientific utility of high-throughput genomic datasets. At their most benign …
Detecting hidden batch factors through data-adaptive adjustment for biological effects
Motivation Batch effects are one of the major source of technical variations that affect the
measurements in high-throughput studies such as RNA sequencing. It has been well …
measurements in high-throughput studies such as RNA sequencing. It has been well …
PLSDA-batch: a multivariate framework to correct for batch effects in microbiome data
Microbial communities are highly dynamic and sensitive to changes in the environment.
Thus, microbiome data are highly susceptible to batch effects, defined as sources of …
Thus, microbiome data are highly susceptible to batch effects, defined as sources of …
Batch effect detection and correction in RNA-seq data using machine-learning-based automated assessment of quality
Background The constant evolving and development of next-generation sequencing
techniques lead to high throughput data composed of datasets that include a large number …
techniques lead to high throughput data composed of datasets that include a large number …