Estratégia para análise de dados de RNA-seq bacteriano
Resumo
The analysis of transcriptomes by RNA-seq technique is currently the best way to assemble the transcriptome profile of an organism. In this paper, we present a protocol for analysis of RNA-seq, considering possible problems in the samples, such as contamination by ribosomal RNA, what happens with some frequency in preparations of libraries by various RNA-seq platforms.
Referências
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Chou, H.-H. and Holmes, M. H. (2001). Dna sequence quality trimming and vector removal. Bioinformatics, 17(12):1093–1104.
Fu, L., Niu, B., Zhu, Z., Wu, S., and Li, W. (2012). Cd-hit: accelerated for clustering the next-generation sequencing data. Bioinformatics, 28(23):3150–3152.
Langmead, B. and Salzberg, S. L. (2012). Fast gapped-read alignment with bowtie 2. Nat Meth, 9(4):357–359.
Li, H., Handsaker, B.,Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., and Subgroup, . G. P. D. P. (2009). The sequence alignment/map format and samtools. Bioinformatics, 25(16):2078–2079.
McClure, R., Balasubramanian, D., Sun, Y., Bobrovskyy, M., Sumby, P., Genco, C. A., Vanderpool, C. K., and Tjaden, B. (2013). Computational analysis of bacterial rna-seq data. Nucleic Acids Research, 41(14):e140.
Anders, S., Pyl, P. T., and Huber, W. (2014). Htseq; a python framework to work with high-throughput sequencing data. bioRxiv.
Chou, H.-H. and Holmes, M. H. (2001). Dna sequence quality trimming and vector removal. Bioinformatics, 17(12):1093–1104.
Fu, L., Niu, B., Zhu, Z., Wu, S., and Li, W. (2012). Cd-hit: accelerated for clustering the next-generation sequencing data. Bioinformatics, 28(23):3150–3152.
Langmead, B. and Salzberg, S. L. (2012). Fast gapped-read alignment with bowtie 2. Nat Meth, 9(4):357–359.
Li, H., Handsaker, B.,Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., and Subgroup, . G. P. D. P. (2009). The sequence alignment/map format and samtools. Bioinformatics, 25(16):2078–2079.
McClure, R., Balasubramanian, D., Sun, Y., Bobrovskyy, M., Sumby, P., Genco, C. A., Vanderpool, C. K., and Tjaden, B. (2013). Computational analysis of bacterial rna-seq data. Nucleic Acids Research, 41(14):e140.
Publicado
28/07/2014
Como Citar
CUSTÓDIO, Márion; GRECCO, Martin; COELHO, Vitor; NICOLÁS, Marisa.
Estratégia para análise de dados de RNA-seq bacteriano. In: BRAZILIAN E-SCIENCE WORKSHOP (BRESCI), 8. , 2014, Brasília.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2014
.
p. 61-64.
ISSN 2763-8774.
