From Gigabyte to Kilobyte: A Bioinformatics Protocol for Mining Large RNA-Seq Transcriptomics Data.
RNA-Seq techniques generate hundreds of millions of short RNA reads using next-generation sequencing (NGS). These RNA reads can be mapped to reference genomes to investigate changes of gene expression but improved procedures for mining large RNA-Seq datasets to extract valuable biological knowledge...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2015-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC4406561?pdf=render |
| _version_ | 1828915929537314816 |
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| author | Jilong Li Jie Hou Lin Sun Jordan Maximillian Wilkins Yuan Lu Chad E Niederhuth Benjamin Ryan Merideth Thomas P Mawhinney Valeri V Mossine C Michael Greenlief John C Walker William R Folk Mark Hannink Dennis B Lubahn James A Birchler Jianlin Cheng |
| author_facet | Jilong Li Jie Hou Lin Sun Jordan Maximillian Wilkins Yuan Lu Chad E Niederhuth Benjamin Ryan Merideth Thomas P Mawhinney Valeri V Mossine C Michael Greenlief John C Walker William R Folk Mark Hannink Dennis B Lubahn James A Birchler Jianlin Cheng |
| author_sort | Jilong Li |
| collection | DOAJ |
| description | RNA-Seq techniques generate hundreds of millions of short RNA reads using next-generation sequencing (NGS). These RNA reads can be mapped to reference genomes to investigate changes of gene expression but improved procedures for mining large RNA-Seq datasets to extract valuable biological knowledge are needed. RNAMiner--a multi-level bioinformatics protocol and pipeline--has been developed for such datasets. It includes five steps: Mapping RNA-Seq reads to a reference genome, calculating gene expression values, identifying differentially expressed genes, predicting gene functions, and constructing gene regulatory networks. To demonstrate its utility, we applied RNAMiner to datasets generated from Human, Mouse, Arabidopsis thaliana, and Drosophila melanogaster cells, and successfully identified differentially expressed genes, clustered them into cohesive functional groups, and constructed novel gene regulatory networks. The RNAMiner web service is available at http://calla.rnet.missouri.edu/rnaminer/index.html. |
| first_indexed | 2024-12-13T20:23:16Z |
| format | Article |
| id | doaj.art-dd7b6ee36d2d4e6981a4bc5845bd51b4 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-13T20:23:16Z |
| publishDate | 2015-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-dd7b6ee36d2d4e6981a4bc5845bd51b42022-12-21T23:32:38ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-01104e012500010.1371/journal.pone.0125000From Gigabyte to Kilobyte: A Bioinformatics Protocol for Mining Large RNA-Seq Transcriptomics Data.Jilong LiJie HouLin SunJordan Maximillian WilkinsYuan LuChad E NiederhuthBenjamin Ryan MeridethThomas P MawhinneyValeri V MossineC Michael GreenliefJohn C WalkerWilliam R FolkMark HanninkDennis B LubahnJames A BirchlerJianlin ChengRNA-Seq techniques generate hundreds of millions of short RNA reads using next-generation sequencing (NGS). These RNA reads can be mapped to reference genomes to investigate changes of gene expression but improved procedures for mining large RNA-Seq datasets to extract valuable biological knowledge are needed. RNAMiner--a multi-level bioinformatics protocol and pipeline--has been developed for such datasets. It includes five steps: Mapping RNA-Seq reads to a reference genome, calculating gene expression values, identifying differentially expressed genes, predicting gene functions, and constructing gene regulatory networks. To demonstrate its utility, we applied RNAMiner to datasets generated from Human, Mouse, Arabidopsis thaliana, and Drosophila melanogaster cells, and successfully identified differentially expressed genes, clustered them into cohesive functional groups, and constructed novel gene regulatory networks. The RNAMiner web service is available at http://calla.rnet.missouri.edu/rnaminer/index.html.http://europepmc.org/articles/PMC4406561?pdf=render |
| spellingShingle | Jilong Li Jie Hou Lin Sun Jordan Maximillian Wilkins Yuan Lu Chad E Niederhuth Benjamin Ryan Merideth Thomas P Mawhinney Valeri V Mossine C Michael Greenlief John C Walker William R Folk Mark Hannink Dennis B Lubahn James A Birchler Jianlin Cheng From Gigabyte to Kilobyte: A Bioinformatics Protocol for Mining Large RNA-Seq Transcriptomics Data. PLoS ONE |
| title | From Gigabyte to Kilobyte: A Bioinformatics Protocol for Mining Large RNA-Seq Transcriptomics Data. |
| title_full | From Gigabyte to Kilobyte: A Bioinformatics Protocol for Mining Large RNA-Seq Transcriptomics Data. |
| title_fullStr | From Gigabyte to Kilobyte: A Bioinformatics Protocol for Mining Large RNA-Seq Transcriptomics Data. |
| title_full_unstemmed | From Gigabyte to Kilobyte: A Bioinformatics Protocol for Mining Large RNA-Seq Transcriptomics Data. |
| title_short | From Gigabyte to Kilobyte: A Bioinformatics Protocol for Mining Large RNA-Seq Transcriptomics Data. |
| title_sort | from gigabyte to kilobyte a bioinformatics protocol for mining large rna seq transcriptomics data |
| url | http://europepmc.org/articles/PMC4406561?pdf=render |
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