2022
DOI: 10.1002/sim.9334
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Assessing reproducibility of high‐throughput experiments in the case of missing data

Abstract: High-throughput experiments are an essential part of modern biological and biomedical research. The outcomes of high-throughput biological experiments often have a lot of missing observations due to signals below detection levels.For example, most single-cell RNA-seq (scRNA-seq) protocols experience high levels of dropout due to the small amount of starting material, leading to a majority of reported expression levels being zero. Though missing data contain information about reproducibility, they are often exc… Show more

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Cited by 5 publications
(3 citation statements)
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“…It demonstrates the usefulness of segCCR for designing reliable and cost‐effective high‐throughput workflows. An extension for handling missing data due to underdetection in high‐throughput experiments (Singh et al., 2022) will be useful.…”
Section: Discussionmentioning
confidence: 99%
“…It demonstrates the usefulness of segCCR for designing reliable and cost‐effective high‐throughput workflows. An extension for handling missing data due to underdetection in high‐throughput experiments (Singh et al., 2022) will be useful.…”
Section: Discussionmentioning
confidence: 99%
“…The filtered reads were then employed to identify CUT&Tag peaks using MACS2 (81). The overlapped peaks in the two biological replicates were identified by the Irreproducibility Discovery Rate (IDR) (82). Final peaks were annotated against the latest T. gondii reference genome in ToxoDB.…”
Section: Methodsmentioning
confidence: 99%
“…The filtered reads were then employed to identify Cut-Tag peaks using MACS2 [48]. The overlapping peaks in two biological replicates were identified by the Irreproducibility Discovery Rate (IDR) [49]. The final peaks were annotated against the latest T. gondii data in ToxoDB.…”
Section: Cut-tag and Data Analysismentioning
confidence: 99%