Title |
Analysis of stranded information using an automated procedure for strand specific RNA sequencing
|
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Published in |
BMC Genomics, July 2014
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DOI | 10.1186/1471-2164-15-631 |
Pubmed ID | |
Authors |
Benjamín Sigurgeirsson, Olof Emanuelsson, Joakim Lundeberg |
Abstract |
Strand specific RNA sequencing is rapidly replacing conventional cDNA sequencing as an approachfor assessing information about the transcriptome. Alongside improved laboratory protocols the developmentof bioinformatical tools is steadily progressing. In the current procedure the IlluminaTruSeq library preparation kit is used, along with additional reagents, to make stranded libraries in anautomated fashion which are then sequenced on Illumina HiSeq 2000. By the use of freely availablebioinformatical tools we show, through quality metrics, that the protocol is robust and reproducible.We further highlight the practicality of strand specific libraries by comparing expression of strand specificlibraries to non-stranded libraries, by looking at known antisense transcription of pseudogenesand by identifying novel transcription. Furthermore, two ribosomal depletion kits, RiboMinus andRiboZero, are compared and two sequence aligners, Tophat2 and STAR, are also compared. |
X Demographics
Geographical breakdown
Country | Count | As % |
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France | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
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Scientists | 1 | 50% |
Members of the public | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Italy | 2 | 2% |
Portugal | 1 | 1% |
Germany | 1 | 1% |
France | 1 | 1% |
Brazil | 1 | 1% |
Sweden | 1 | 1% |
Finland | 1 | 1% |
New Zealand | 1 | 1% |
Mexico | 1 | 1% |
Other | 1 | 1% |
Unknown | 77 | 88% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 26 | 30% |
Researcher | 17 | 19% |
Student > Master | 11 | 13% |
Student > Doctoral Student | 8 | 9% |
Student > Bachelor | 8 | 9% |
Other | 8 | 9% |
Unknown | 10 | 11% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 43 | 49% |
Biochemistry, Genetics and Molecular Biology | 18 | 20% |
Medicine and Dentistry | 4 | 5% |
Computer Science | 2 | 2% |
Immunology and Microbiology | 2 | 2% |
Other | 8 | 9% |
Unknown | 11 | 13% |