核醣體定位技術(ribosome-profiling)是一種新興的高通量定序技術。它可以在轉譯的過程中得知哪些mRNA正在被核醣體結合來進行蛋白質合成，而核醣體結合的區域大約27~40個核苷酸。可能是因為片段太短，這些片段在進行序列比對時，通常會比對到轉錄體中的許多位置，使得這些片段會被丟棄或隨機分配，而導致基因表現量計算錯誤。所以我們開發一個更適合用於核醣體定位技術的分析流程，並且可以用於估算異構體等級的表現量。在我的研究中，我們使用Cutadapt、Bowtie、RSEM和Perl來開發這個分析流程。第一步，預處理，用Cutadapt切除adapter並進行長度篩選。接著，透過Bowtie去除粒線體核醣體RNA，黴漿菌核醣體RNA，人類核醣體RNA等污染物。第二步，透過Bowtie比對片段、RSEM將含糊不清的片段分配到到轉錄體中。第三步，用我們開發的程式（由Perl編寫）計算基因和異構體的表現量。除此之外，可以到資料庫繪製這次分析結果的核醣體結合圖譜，並且供使用者下載。與其他程式相比，我們的分析流程可以提供比先前軟體在每個轉錄物中的表現量估算更為準確、合理。

Ribosome profiling (Ribo-seq) is an emerging high-throughput sequencing technology. It provides the information about what kinds of mRNA are engaged in protein synthesis. Due to the ribosome-bound region is very short, approximately 27~40 nucleotides. These fragments are easily mapped to many positions in the transcript when they are aligned. It will lead to misinterpretation of the expression level of genes. Therefore, we want to develop a pipeline that is more exactly locating the ribosome binding position and can be used to estimate the expression isoform level. In this study, we use Cutadapt, Bowtie, RSEM (RNA-seq by expectation-maximization), and Perl to develop this pipeline. First step, pre-processing, we cut the adapter sequence and length selection by Cutadapt. Then, the contaminations such as mitochondria rRNAs, mycoplasma rRNAs, Homo sapiens rRNAs are removed by Bowtie. Second step, map reads to transcriptome by Bowtie and assign multi-mapped reads by RSEM. Third step, calculate gene and isoform expression levels with the program (written by Perl) developed by us. Additionally, we establish a database to draw the ribosome profile, and the pipeline can be download there. Compared to other programs, we provide a more accurate and reasonable estimation of the expression of each transcript.

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