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Transcriptome Data Analysis

Overview of attention for book
Cover of 'Transcriptome Data Analysis'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Comparison of Gene Expression Profiles in Nonmodel Eukaryotic Organisms with RNA-Seq
  3. Altmetric Badge
    Chapter 2 Microarray Data Analysis for Transcriptome Profiling
  4. Altmetric Badge
    Chapter 3 Pathway and Network Analysis of Differentially Expressed Genes in Transcriptomes
  5. Altmetric Badge
    Chapter 4 QuickRNASeq: Guide for Pipeline Implementation and for Interactive Results Visualization
  6. Altmetric Badge
    Chapter 5 Tracking Alternatively Spliced Isoforms from Long Reads by SpliceHunter
  7. Altmetric Badge
    Chapter 6 RNA-Seq-Based Transcript Structure Analysis with TrBorderExt
  8. Altmetric Badge
    Chapter 7 Analysis of RNA Editing Sites from RNA-Seq Data Using GIREMI
  9. Altmetric Badge
    Chapter 8 Bioinformatic Analysis of MicroRNA Sequencing Data
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    Chapter 9 Microarray-Based MicroRNA Expression Data Analysis with Bioconductor
  11. Altmetric Badge
    Chapter 10 Identification and Expression Analysis of Long Intergenic Noncoding RNAs
  12. Altmetric Badge
    Chapter 11 Analysis of RNA-Seq Data Using TEtranscripts
  13. Altmetric Badge
    Chapter 12 Computational Analysis of RNA–Protein Interactions via Deep Sequencing
  14. Altmetric Badge
    Chapter 13 Predicting Gene Expression Noise from Gene Expression Variations
  15. Altmetric Badge
    Chapter 14 A Protocol for Epigenetic Imprinting Analysis with RNA-Seq Data
  16. Altmetric Badge
    Chapter 15 Single-Cell Transcriptome Analysis Using SINCERA Pipeline
  17. Altmetric Badge
    Chapter 16 Mathematical Modeling and Deconvolution of Molecular Heterogeneity Identifies Novel Subpopulations in Complex Tissues
Attention for Chapter 14: A Protocol for Epigenetic Imprinting Analysis with RNA-Seq Data
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Chapter title
A Protocol for Epigenetic Imprinting Analysis with RNA-Seq Data
Chapter number 14
Book title
Transcriptome Data Analysis
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7710-9_14
Pubmed ID
Book ISBNs
978-1-4939-7709-3, 978-1-4939-7710-9
Authors

Jinfeng Zou, Daoquan Xiang, Raju Datla, Edwin Wang, Zou, Jinfeng, Xiang, Daoquan, Datla, Raju, Wang, Edwin

Abstract

Genomic imprinting is an epigenetic regulatory mechanism that operates through expression of certain genes from maternal or paternal in a parent-of-origin-specific manner. Imprinted genes have been identified in diverse biological systems that are implicated in some human diseases and in embryonic and seed developmental programs in plants. The molecular underpinning programs and mechanisms involved in imprinting are yet to be explored in depth in plants. The recent advances in RNA-Seq-based methods and technologies offer an opportunity to systematically analyze epigenetic imprinting that operates at the whole genome level in the model and crop plants. We are interested using Arabidopsis model system, to investigate gene expression patterns associated with parent of origin and their implications to imprinting during embryo and seed development. Toward this, we have generated early embryo development RNA-Seq-based transcriptome datasets in F1s from a genetic cross between two diverse Arabidopsis thaliana ecotypes Col-0 and Tsu-1. With the data, we developed a protocol for evaluating the maternal and paternal contributions of genes during the early stages of embryo development after fertilization. This protocol is also designed to consider the contamination from other potential seed tissues, sequencing quality, proper processing of sequenced reads and variant calling, and appropriate inference of the parental contributions based on the parent-of-origin-specific single-nucleotide polymorphisms within the expressed genes. The approach, methods and the protocol developed in this study can be used for evaluating the effects of epigenetic imprinting in plants.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 2 20%
Student > Master 2 20%
Unspecified 1 10%
Professor 1 10%
Student > Bachelor 1 10%
Other 2 20%
Unknown 1 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 20%
Unspecified 1 10%
Environmental Science 1 10%
Nursing and Health Professions 1 10%
Biochemistry, Genetics and Molecular Biology 1 10%
Other 2 20%
Unknown 2 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 30 May 2018.
All research outputs
#14,968,843
of 23,025,074 outputs
Outputs from Methods in molecular biology
#4,731
of 13,170 outputs
Outputs of similar age
#255,768
of 442,363 outputs
Outputs of similar age from Methods in molecular biology
#508
of 1,499 outputs
Altmetric has tracked 23,025,074 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,170 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 59% of its peers.
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We're also able to compare this research output to 1,499 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.