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RecountDB: a database of mapped and count corrected transcribed sequences
The field of gene expression analysis continues to benefit from next-generation sequencing generated data, which enables transcripts to be measured with unmatched accuracy and resolution. But the high-throughput reads from these technologies also contain many errors, which can compromise the ability...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3245132/ https://www.ncbi.nlm.nih.gov/pubmed/22139942 http://dx.doi.org/10.1093/nar/gkr1172 |
Sumario: | The field of gene expression analysis continues to benefit from next-generation sequencing generated data, which enables transcripts to be measured with unmatched accuracy and resolution. But the high-throughput reads from these technologies also contain many errors, which can compromise the ability to accurately detect and quantify rare transcripts. Fortunately, techniques exist to ameliorate the affects of sequencer error. We present RecountDB, a secondary database derived from primary data in NCBI's short read archive. RecountDB holds sequence counts from RNA-seq and 5′ capped transcription start site experiments, corrected and mapped to the relevant genome. Via a searchable and browseable interface users can obtain corrected data in formats useful for transcriptomic analysis. The database is currently populated with 2265 entries from 45 organisms and continuously growing. RecountDB is publicly available at: http://recountdb.cbrc.jp. |
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