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Computational Epigenomics and Epitranscriptomics

Overview of attention for book
Cover of 'Computational Epigenomics and Epitranscriptomics'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 DNA Methylation Data Analysis Using Msuite.
  3. Altmetric Badge
    Chapter 2 Interactive DNA Methylation Array Analysis with ShinyÉPICo
  4. Altmetric Badge
    Chapter 3 Predicting Chromatin Interactions from DNA Sequence Using DeepC
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    Chapter 4 Integrating Single-Cell Methylome and Transcriptome Data with MAPLE
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    Chapter 5 Quantitative Comparison of Multiple Chromatin Immunoprecipitation-Sequencing (ChIP-seq) Experiments with spikChIP
  7. Altmetric Badge
    Chapter 6 A Guide to MethylationToActivity: A Deep Learning Framework That Reveals Promoter Activity Landscapes from DNA Methylomes in Individual Tumors.
  8. Altmetric Badge
    Chapter 7 DNA Modification Patterns Filtering and Analysis Using DNAModAnnot.
  9. Altmetric Badge
    Chapter 8 Methylome Imputation by Methylation Patterns
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    Chapter 9 Sequoia: A Framework for Visual Analysis of RNA Modifications from Direct RNA Sequencing Data.
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    Chapter 10 Predicting Pseudouridine Sites with Porpoise.
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    Chapter 11 Pseudouridine Identification and Functional Annotation with PIANO.
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    Chapter 12 Analyzing mRNA Epigenetic Sequencing Data with TRESS.
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    Chapter 13 Nanopore Direct RNA Sequencing Data Processing and Analysis Using MasterOfPores.
  15. Altmetric Badge
    Chapter 14 Data Analysis Pipeline for Detection and Quantification of Pseudouridine (ψ) in RNA by HydraPsiSeq.
  16. Altmetric Badge
    Chapter 15 Analysis of RNA Sequences and Modifications Using NASE
  17. Altmetric Badge
    Chapter 16 Mapping of RNA Modifications by Direct Nanopore Sequencing and JACUSA2.
Attention for Chapter 7: DNA Modification Patterns Filtering and Analysis Using DNAModAnnot.
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (61st percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

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Chapter title
DNA Modification Patterns Filtering and Analysis Using DNAModAnnot.
Chapter number 7
Book title
Computational Epigenomics and Epitranscriptomics
Published in
Methods in molecular biology, January 2023
DOI 10.1007/978-1-0716-2962-8_7
Pubmed ID
36723811
Book ISBNs
978-1-07-162961-1, 978-1-07-162962-8
Authors

Hardy, Alexis, Duharcourt, Sandra, Defrance, Matthieu

Abstract

Mapping DNA modifications at the base resolution is now possible at the genome level thanks to advances in sequencing technologies. Long-read sequencing data can be used to identify modified base patterns. However, the downstream analysis of Pacific Biosciences (PacBio) or Oxford Nanopore Technologies (ONT) data requires the integration of genomic annotation and comprehensive filtering to prevent the accumulation of artifact signals. We present in this chapter, a linear workflow to fully analyze modified base patterns using the DNA Modification Annotation (DNAModAnnot) package. This workflow includes a thorough filtering based on sequencing quality and false discovery rate estimation and provides tools for a global analysis of DNA modifications. Here, we provide an application example of this workflow with PacBio data and guide the user by explaining expected outputs via a fully integrated Rmarkdown script. This protocol is presented with tips showing how to adapt the provided code for annotating epigenomes of any organism according to the user needs.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 67%
Unknown 1 33%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 67%
Unknown 1 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 February 2023.
All research outputs
#13,488,827
of 23,269,984 outputs
Outputs from Methods in molecular biology
#3,550
of 13,322 outputs
Outputs of similar age
#155,996
of 421,877 outputs
Outputs of similar age from Methods in molecular biology
#61
of 360 outputs
Altmetric has tracked 23,269,984 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,322 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 72% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 421,877 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.
We're also able to compare this research output to 360 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.

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