@techreport{oai:ipsj.ixsq.nii.ac.jp:00107455,
 author = {瀬々, 潤 and Jun, Sese},
 issue = {4},
 month = {Dec},
 note = {遺伝子網羅的に発現量を観測するマイクロアレイが超並列シーケンサを利用する RNA-seq になり，遺伝子発現の解析に新たな統計手法が必要となっている．要因の一例として，マイクロアレイでは相対的な発現量として採取されいた遺伝子発現量に関し，計数による計量が行える定量性の高さが挙げられる．また，反復実験が一般的となり，発現量の変化を統計的指標に基づいて検出する傾向が高まっている．このような実験の変化に対して，新たに考慮すべき統計解析が存在し，RNA-seq の発現量解析には，Cuffdiff，edgeR， DESeq など独特のソフトウエアが利用されている．本発表では，これらで利用されている統計解析についてレビューを行う．, Frequently used biological experiment technique for observing comprehensive gene expression has been changed from microarray using cDNA hybridization to RNA-seq using high-throughput sequencers so called NGS, which allow us to use statistical model to analyze the changes of gene expression levels of each gene. For example, while microarrays use the brightness of the spots, RNA-seqs measure the number of fragments on each gene, giving us more quantitative values. It is also important that biological replicates are generally required, but the number of really performed experiments is limited because of reducing the experimental cost. To handle these data, several statistical methods to find genes whose expression levels are statistically changed between two different conditions have been introduced, such as Cuffdiff, edgeR and DESeq. We here introduce the statistical methods.},
 title = {発現変動遺伝子抽出の統計～レビュー},
 year = {2014}
}