Title |
Optimizing de novo common wheat transcriptome assembly using short-read RNA-Seq data
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Published in |
BMC Genomics, August 2012
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DOI | 10.1186/1471-2164-13-392 |
Pubmed ID | |
Authors |
Jialei Duan, Chuan Xia, Guangyao Zhao, Jizeng Jia, Xiuying Kong |
Abstract |
Rapid advances in next-generation sequencing methods have provided new opportunities for transcriptome sequencing (RNA-Seq). The unprecedented sequencing depth provided by RNA-Seq makes it a powerful and cost-efficient method for transcriptome study, and it has been widely used in model organisms and non-model organisms to identify and quantify RNA. For non-model organisms lacking well-defined genomes, de novo assembly is typically required for downstream RNA-Seq analyses, including SNP discovery and identification of genes differentially expressed by phenotypes. Although RNA-Seq has been successfully used to sequence many non-model organisms, the results of de novo assembly from short reads can still be improved by using recent bioinformatic developments. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | 33% |
France | 1 | 17% |
United States | 1 | 17% |
Unknown | 2 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 3 | 50% |
Members of the public | 3 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 6 | 2% |
Germany | 4 | 1% |
Australia | 3 | 1% |
Italy | 3 | 1% |
Brazil | 3 | 1% |
Uganda | 1 | <1% |
India | 1 | <1% |
Paraguay | 1 | <1% |
Canada | 1 | <1% |
Other | 5 | 2% |
Unknown | 239 | 90% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 70 | 26% |
Student > Ph. D. Student | 66 | 25% |
Student > Master | 36 | 13% |
Other | 17 | 6% |
Student > Doctoral Student | 14 | 5% |
Other | 51 | 19% |
Unknown | 13 | 5% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 189 | 71% |
Biochemistry, Genetics and Molecular Biology | 34 | 13% |
Computer Science | 10 | 4% |
Unspecified | 4 | 1% |
Chemistry | 3 | 1% |
Other | 4 | 1% |
Unknown | 23 | 9% |