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基因测序:数据处理与标准问题仍待解

2015-11-24 佚名 中国科学报

【导读】目前我国在数据行业标准方面概念还很模糊,这就导致科研机构、医疗机构、企业在利用基因数据的时候,没有统一的规则,也造成基因测序行业良莠不齐。这种情况,亟须得到改变。 目前我国在数据行业标准方面概念还很模糊,这就导致科研机构、医疗机构、企业在利用基因数据的时候,没有统一的规则,也造成基因测序行业良莠不齐。这种情况,亟须得到改变。 基因测序,一直被视为生命科学和生物技术发展的重大革命

【导读】目前我国在数据行业标准方面概念还很模糊,这就导致科研机构、医疗机构、企业在利用基因数据的时候,没有统一的规则,也造成基因测序行业良莠不齐。这种情况,亟须得到改变。

目前我国在数据行业标准方面概念还很模糊,这就导致科研机构、医疗机构、企业在利用基因数据的时候,没有统一的规则,也造成基因测序行业良莠不齐。这种情况,亟须得到改变。

基因测序,一直被视为生命科学和生物技术发展的重大革命。在经历过前些年的积累之后,今年的基因测序行业似乎看到爆发的曙光。

日前,湖南省和贵州省相继发布了关于支持基因测序技术应用的政策。贵州省提出,高龄单独两孩孕产妇出生缺陷基因筛查享受全免费政策。湖南省的政策则似乎更加激进——未来,湖南省将用政府采购的方式开展和推广遗传病基因检测、开展基因检测试点、大力推广个性化医疗、将部分基因检测费用纳入医保等。

但在诸多专家看来,尽管基因测序日益红火,但要想真正爆发,“走入寻常百姓家”,数据量累积带来的处理问题以及行业标准问题仍待解决。

火热的基因测序

2014年,美国当地保险机构Priorty Health宣布,公司与基因测序测试公司Foundation Medicine签订协议,将后者的基因测序产品纳入医保范围。今年,国内贵州、湖南等省份的跟进,又将基因测序推向风口浪尖。

基因测序为何这么热?

在此前的杭州云栖大会上,华大基因互联网发展中心总监官鑫向《中国科学报》记者举了一个例子:“根据现有的科学研究,人能不能喝酒与基因有关,并且还可以通过基因测序测出哪些人能喝酒,哪些人不能喝。”

“这种技术对我就非常有用。因为我不能喝酒。我想,以后是不是可能会出现这种情况,有人劝酒之前,你就可以拿出一个基因测序的结果给他看,避免大家尴尬。”官鑫笑言。当然,基因测序的应用远不止于此,准确地检测某些疾病的患病风险才是它的初衷。

作为国内基因测序的领军企业,华大基因在2014年就在京启动“千万家庭远离遗传出生缺陷”计划,预计通过基因检测技术大幅降低中国的出生缺陷率。该计划首度聚焦唐氏综合征和粘多糖病、鱼鳞病、地中海贫血、苯丙酮尿症等罕见遗传病。其中,唐氏综合征的基因检测方法被称为无创产前检测,是目前最为成熟的基因临床应用。

中科院自动化所博士、聚道科技创始人李夏戎向《中国科学报》记者指出,随着基因测序技术的发展,个人的健康问题,包括遗传病等都可以分析出来,“通过基因数据的分析,我们能够知道未来的后代有多大概率得某个疾病以及怎么预防该疾病的发生” 。

基因测序的火热,也带来整个行业的火暴。目前,国内的基因测序企业不下数百家。而随着全球精准医疗规模的快速增长,也将助推基因测序强势崛起。

有数据显示,2015年全球精准医疗市场规模近600亿美元,预计2015~2020年期间增速达15%,是医药行业增速的3~4倍;2013年基因测序市场规模约45亿美元,2013年至2018年复合增长率为21.2%,而国内2012年至2017年复合增长率将达20%~25%。

数据膨胀呼唤计算能力提高

基因测序行业迎来发展高峰期的同时,数据处理的问题也日益凸显。

官鑫表示,随着下一代基因测序、生物质谱和医学成像等医学技术的迅猛发展,大数据浪潮为生物医学带来了前所未有的机遇,这将根本性地改变生物医学基础研究和医疗实践,但同时生物医学领域数据爆炸式的增长也对海量数据的存储和分析提出新的挑战。

“我们对于很多复杂疾病的了解,包括人的表情与基因数据的关系,都需要很多的样板量去做验证,甚至需要机器学习完成。这就呼唤大数据技术和云计算以及人工智能的介入。”官鑫说。

一脉基因创始人郝向稳也指出,人类的一套基因组包含30亿个碱基对的基因组,能够编码功能蛋白的基因数量在3万左右,但这仅占整个基因组区域的3%,基因组上超过90%区域的功能人类还是未知的。因此,对于生命的解读不仅需要科学领域的不断创新,更需要计算领域的支持和参与。

李厦戎认为,现在所说的基因测序更多在于基因数据的预处理阶段,还没有到基因数据大规模利用的阶段。“未来大的数据出现之后,必然需要大量的计算能力。”

而在奇云诺德创始人罗奇斌看来,基因信息存在大量冗余、分析技术难度高、数据解读跟不上是目前基因测序行业的瓶颈,而这也将催生出大量专注于数据存储、分析、解读服务的公司。

罗奇斌对记者表示,基因数据处理产业的解决方案就是云技术服务,利用云平台运维数据处理流程,以实现大部分工作的高效自动化和低成本,并对接医疗健康应用领域。“云端技术能够解决数据存储、数据运算和数据安全问题,由于云端技术已经成为互联网公司的专宠,未来互联网公司拥抱基因行业指日可待。”罗奇斌说。

期待政府制定行业标准

在基因测序大规模推广和商业化之前,还有很多棘手的问题需要解决,行业规范化就是先决条件。

在采访中记者了解到,作为新兴行业,基因测序目前存在诸多乱象,对此,众多专家呼唤有关部门应及早介入解决。

“就像一本《基因决战》的书中所提的,基因行业不能像其他行业那样,落后于别人,必须得到社会重视和政府的支持。”官鑫表示。

郝向稳也坦言,目前基因测序市场比较混乱,有的企业号称几百元就能帮人作测序,有的则要几千元或者上万元,导致大众产生认知混乱。

“当然,基因检测是宽泛的概念,市场上有针对各种各样不同目的的基因检测套餐。每种套餐价格是不一样的。”因此,郝向稳建议政府部门在科研数据搜集、数据库、基因解读的规范化方面多下功夫,促进整个行业的健康发展。

“我们觉得政府应该做的事情,就是设立数据的行业标准。”李夏戎指出,美国目前在这方面就做得比较好,无论医疗数据还是个人有关的数据都有一系列的标准,保证数据存储、传输、处理的安全性和规范性。但是,目前我国在这方面概念还很模糊,这就导致科研机构、医疗机构、企业在利用基因数据的时候,没有统一的规则,也造成基因测序行业良莠不齐。这种情况,亟须得到改变。

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    2017-05-16 xiaogan8479

    学习

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    2016-08-27 李东泽

    这篇资讯带给我们新知识,启发新思维,不论是科研还是临床工作都有很大的帮助。。。

    0

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    2016-01-13 Lynee劲飞扬

    加油

    0

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    2015-12-30 1de14ca4m57(暂无匿称)

    牛逼

    0

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    2015-12-27 忠诚向上

    0

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    2015-11-24 鲜花飞鸟

    我们要加把油了,不能落在别人后面

    0

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    2015-11-24 vpssa

    这是最好的时候。

    0

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