Question

高分求助翻译一段话

Sensitivity to detect and differential bias. Detection
of CNVs from array data is sensitive to the
detailed noise properties of each hybridization,
which in turn arise from sample and hybridization
quality. (A survey of the supplementary data sets
underlying many CNV-discovery approaches
indicates that the number of CNVs detected per
sample can vary 4-fold from sample to sample.)
As the DNA from affected and unaffected individuals
in GWAS often originates at different clinical
sites, is extracted at different times, or is analyzed
in different experimental plates or batches,
‘differential bias’ —the confounding of
detection sensitivity with Case/Control status—is
pervasive. The problem is particularly severe
in analyses of the ‘genomic burden’ of CNVs
across the genome, since such analyses aggregate
the effects of confounds at thousands of loci. It is
therefore important to carefully dissect the
sample- and batch-specific influences on detection
sensitivity, and to develop carefully controlled
analyses. Algorithmic approaches for this are an
urgent need in the field.
Rare CNVs that are shared by unrelated individuals are frequently present on a long
shared haplotype (blue); the possibility that some other feature of this haplotype might be the causal feature needs to be evaluated in an integrated analysis of
CNV and SNP haplotypes.

Answer 1

敏感性检测和鉴别。从数组数据的CNVs发现对于每个杂交详细噪声性能是敏感的，这反过来又出现样品和杂交质量。 （一补充调查数据集许多潜在的CNV，发现方法检测表明，每拷贝数变异数从抽样样本可以不同4倍采样。）由于受影响和未受影响个体的DNA在GWAS往往起源于不同的临床地点是在不同时间提取，或进行了分析在不同的实验板或批次，'微分偏见'的干扰的检测灵敏度与案例/控制地位是无孔不入。这个问题在整个基因组中的'基因组拷贝数变异的负担'分析显得尤为严重，因为这种分析总在成千上万的作用位点困惑。因此，必须认真剖析采样和特定批次的对检测的影响敏感性，并制定严格控制分析。在这个领域中这是一迫切需要的方法。罕见的是CNVs是目前经常在长
共享单倍型（蓝色）的可能性与个人分享无关，一些其他功能，这单倍型可能是因果功能需要在综合分析评价CNV的和SNP单倍型。

Answer 2

敏感性检测和微分的偏见。检测
从数组数据的CNVs敏感的
详细的噪声性能,每个杂交,
反过来,杂交产生于样品吗
质量。(进行的一项调查显示,补充数据集
许多CNV-discovery潜在方法
显示的数量,CNVs检测
样品可以改变从样品样本。性滴定终点可以4倍)。
当DNA的影响和未受影响的个体
不同于通常来源于GWAS临床
网站、提取时间不同,或进行了分析
在不同的实验板或批次,
“差”——这是一种混杂的偏见
检测灵敏度和案例/控制status-is
普及。这个问题尤为严重
在分析的CNVs’的基因组负担
整个基因组,因为这种分析聚合
在成千上万的影响的位点混淆。它是
所以重要解剖仔细
batch-specific样品,影响检测
灵敏度,并制定严格控制下
分析。这是一种算法的方法
在这个领域的迫切需要。