北京诺禾致源生物信息科技有限公司
12．差异基因蛋白互作网络分析
对差异分析中所产生的差异基因列表，在STRING数据库中找出这些差异基因间的互作关系，并将得到的互作数据导入 Cytoscape 软件实现互作网络的可视化。蛋白质互作数据来源于STRING数据库（http://string-db.org/）。
互作网络如下图所示，其中节点（node）的大小与此节点的度（degree）成正比，即与此节点相连的边越多，它的度越大，节点也就越大。节点的颜色与此节点的聚集系数（clustering coefficient）相关，颜色梯度由绿到红对应聚集系数的值由低到高；聚集系数表示此节点的邻接点之间的连通性好坏，聚集系数值越高表示此节点的邻接点之间的连通性越好。边（edge）的宽度表示此边连接的两个节点间的互相作用的关系强弱，互相作用的关系越强，边越宽。
46 北京诺禾致源生物信息科技有限公司
图11 差异基因互作网络图
四、参考文献
Anders, S., and Huber, W. Differential expression analysis for sequence count data. Genome Biol 11, R106. Chepelev, I., Wei, G., Tang, Q., and Zhao, K. (2009). Detection of single nucleotide variations in expressed exons of the human genome using RNA-Seq. Nucleic acids research 37, e106-e106.
Cock, P.J.A., Fields, C.J., Goto, N., Heuer, M.L., and Rice, P.M. The Sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ variants. Nucleic acids research 38, 1767-1771.
Dohm, J.C., Lottaz, C., Borodina, T., and Himmelbauer, H. (2008). Substantial biases in ultra-short read data sets from high-throughput DNA sequencing. Nucleic acids research 36, e105-e105.
Erlich, Y., and Mitra, P.P. (2008). Alta-Cyclic: a self-optimizing base caller for next-generation sequencing. Nature methods 5, 679-682.
47 北京诺禾致源生物信息科技有限公司 Foissac, S., and Sammeth, M. (2007). ASTALAVISTA: dynamic and flexible analysis of alternative splicing events in custom gene datasets. Nucleic acids research 35, W297-W299.
Hansen, K.D., Brenner, S.E., and Dudoit, S. Biases in Illumina transcriptome sequencing caused by random hexamer priming. Nucleic acids research 38, e131-e131.
Hansen, K.D., Wu, Z., Irizarry, R.A., and Leek, J.T. Sequencing technology does not eliminate biological variability. Nature biotechnology 29, 572-573.
Jensen L J, Kuhn M, Stark M, Chaffron S, Creevey C, Muller J, Doerks T, Julien P, Roth A, Simonovic M, Bork P and von Mering C. 2009. STRING 8-a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Research 37: D412-D416.
Jiang, L., Schlesinger, F., Davis, C.A., Zhang, Y., Li, R., Salit, M., Gingeras, T.R., and Oliver, B. Synthetic spike-in standards for RNA-seq experiments. Genome research 21, 1543-1551.
Kent, W.J. (2002). BLAT鈥攖he BLAST-like alignment tool. Genome research 12, 656-664.
Mamanova, L., Andrews, R.M., James, K.D., Sheridan, E.M., Ellis, P.D., Langford, C.F., Ost, T.W.B., Collins, J.E., and Turner, D.J. FRT-seq: amplification-free, strand-specific transcriptome sequencing. Nature methods 7, 130-132.
Marquez, Y., Brown, J.W.S., Simpson, C.G., Barta, A., and Kalyna, M. Transcriptome survey reveals increased complexity of the alternative splicing landscape in Arabidopsis. Genome research.
Mortazavi, A., Williams, B.A., McCue, K., Schaeffer, L., and Wold, B. (2008). Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nature methods 5, 621-628.
Sammeth, M. (2009). Complete alternative splicing events are bubbles in splicing graphs. Journal of Computational Biology 16, 1117-1140.
Sammeth, M., Foissac, S., and Guig贸, R. (2008). A general definition and nomenclature for alternative splicing events. PLoS computational biology 4, e1000147.
Trapnell, C., Pachter, L., and Salzberg, S.L. (2009). TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25, 1105-1111.
Trapnell, C., Williams, B.A., Pertea, G., Mortazavi, A., Kwan, G., Van Baren, M.J., Salzberg, S.L., Wold, B.J., and Pachter, L. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nature biotechnology 28, 511-515.
Wang, E.T., Sandberg, R., Luo, S., Khrebtukova, I., Zhang, L., Mayr, C., Kingsmore, S.F., Schroth, G.P., and Burge, C.B. (2008). Alternative isoform regulation in human tissue transcriptomes. Nature 456, 470-476.
Young, M.D., Wakefield, M.J., Smyth, G.K., and Oshlack, A. goseq: Gene Ontology testing for RNA-seq datasets.
48
转录组有参考生物信息分析结题报告模版-V2.0
