SEQUENCE ANALYSIS METHODS ADAPTED TO LARGE SCALE SEQUENCING PROJECTS

大比例尺数据的生物解释 排序项目受到无法管理的大程序输出的困扰 其大小和噪声/信号比模糊了真正相关的 调查结果。这个问题可以归因于多种原因： 不断增加的数据库大小及其质量(冗余、试验性 和文书错误)和生物学的一些内在属性 序列，如重复的元素和局部成分偏向。在……里面 为了缓解这些问题，我们开发了一套程序 现在常规地在信息增强步骤中使用 对大量层序数据的分析。遵循这一步骤， 基因鉴定和序列比较程序的输出成为 在生物学和统计学上无需进一步处理即可解释。 此外，我们还开发了一套独立的模块，可以 使用顺序自动分析大量实验数据 数据。这些工具的威力在以下背景下得到了证明 与实验小组的合作产生了大量的 序列(见项目Z01-LM-00011-01-BRB)。与此同时，我们也在 开发新的序列分析方法，既可用于 对已在数据库中或到数据库中的序列的质量控制 对新确定的问题的解释。

The biological interpretation of the data generated by large scale sequencing projects is plagued by unmanageable large program outputs the size and the noise/signal ratio of which obscure the truly relevant findings. This problem can be attributed to various causes: the increasing size of the databases, their quality (redundancy, experimental and clerical errors) and some intrinsic properties of biological sequences such as repeated elements and local compositional bias. In order to alleviate these problems we have developed a set of programs that are now routinely used in an information enhancement step prior to the analysis of large body of sequence data. Following this steps, the output of gene identification and sequence comparison programs become biologically and statistically interpretable without further processing. In addition we have developed a suite of independent modules that can be used in sequence to automatically analyze large body of experimental data. The power of these tools has been demonstrated in the context of collaborations with experimental groups generating a large amount of sequences (see project Z01-LM-00011-01-BRB). In the meantime, we are also developing new sequence analysis methods than can be both applied to the quality control of sequences already in the databases or to the interpretation of newly determined ones.