标签归档:reprint

为OSX和Linux的TERMINAL增加时间分割线

Add a Handy Separator Between Commands in Your Terminal on Mac OS X and Linux
为终端的命令行之间添加时间线,增加可读性,效果如下。

Last login: Tue Mar 17 13:18:30 on ttys000
----------------------------------------------------------------------- 13:32:37
zzx@zzxdesk:~$ pwd
/Users/zzx
----------------------------------------------------------------------- 13:38:31
zzx@zzxdesk:~$ cd Desktop/
----------------------------------------------------------------------- 13:38:40
zzx@zzxdesk:~/Desktop$ pwd
/Users/zzx/Desktop
----------------------------------------------------------------------- 13:38:42
zzx@zzxdesk:~/Desktop$

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An Explosion Of Bioinformatics Careers (reprint)

Big data is everywhere, and its influence and practical omnipresence across multiple industries will just continue to grow. For life scientists with expertise and an interest in bioinformatics, computer science, statistics, and related skill sets, the job outlook couldn’t be rosier. Big pharma, biotech, and software companies are clamoring to hire professionals with experience in bioinformatics and the identification, compilation, analysis, and visualization of huge amounts of biological and health care information. With the rapid development of new tools to make sense of life science research and outcomes, spurred by innovative research in bioinformatics itself, scientists who are entranced by data can pursue more career options than ever before. By Alaina G. Levine 继续阅读

RNA测序到底可不可靠?(转)

RNA测序可以检测人类和其他生物的基因表达情况。最近这一方法在生物科学和医学研究中非常流行,而且正在逐渐走向临床应用。与之前的方法相比,RNA测序的优势是便于研究选择性剪切形成的基因异构体或转录本。

那么RNA测序到底可不可靠呢?日前,由美国FDA牵头的测序质量控制(SEQC)项目对RNA测序的准确性、可重现性和信息含量进行了综合性评估,并将初步调查结果发表在近日的Nature Biotechnology杂志上。

研究团队使用RNA参照样本,在全球多个实验室的Illumina HiSeq、Life Technologies SOLiD、Roche 454平台上进行了检测。(深圳华大基因、复旦大学、华东师范大学等单位参与了这一项目。)研究人员主要是评估RNA测序在接头区域和差异性表达谱中的表现,并将其与芯片和定量PCR(qPCR)进行比较。

研究人员发现,所有测序深度都会出现未注释的外显子-外显子连接区域,其中80%以上都得到了qPCR的验证。用RNA测序检测相对表达可以得到准确且可重复的结果,但RNA测序和芯片都不能提供精确的绝对测量,而且研究用到的平台都存在基因特异性的偏好,包括qPCR。

数据分析的算法也会对RNA测序产生很大影响,不同算法生成的转录本数据差异很大。研究显示,赫尔辛基大学和曼彻斯特大学开发的BitSeq能生成最可靠的结果,这一方法以概率建模为基础。

这项研究获得的完整SEQC数据集拥有超过10Tb读取,为评估RNA测序分析提供了宝贵的资源。

转自 http://www.biodiscover.com/news/research/112652.html

原文original paper: http://www.nature.com/nbt/journal/v32/n9/full/nbt.2957.html

We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the US Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference RNA samples with built-in controls, we assess RNA sequencing (RNA-seq) performance for junction discovery and differential expression profiling and compare it to microarray and quantitative PCR (qPCR) data using complementary metrics. At all sequencing depths, we discover unannotated exon-exon junctions, with >80% validated by qPCR. We find that measurements of relative expression are accurate and reproducible across sites and platforms if specific filters are used. In contrast, RNA-seq and microarrays do not provide accurate absolute measurements, and gene-specific biases are observed for all examined platforms, including qPCR. Measurement performance depends on the platform and data analysis pipeline, and variation is large for transcript-level profiling. The complete SEQC data sets, comprising >100 billion reads (10Tb), provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings.

总之有些人后来真的再也没见过(转载)

微信群里一姐们,说自己马上要毕业了。昨儿跟自己的好姐妹去夜店里蹦跶,然后半夜在马路上边哭边喊,于是她今天的嗓子哑的和杨坤似的。

想起我毕业的时候倒是风平浪静,啥疯狂的事儿没干。跟兄弟喝酒的时候一直很正常,感觉仿佛毕业只是一个再常见不过的程序,末了我一个人收拾行李的时候,听着yellow,突然间就跟傻逼一样地哭起来。我一直是个钝感严重的傻缺,大概直到那个时候,我才明白自己要告别的是什么。

告别。

尽管我们都在彼此的同学录里写着“友谊常在”之类的字眼——也不知道现在是不是还流行着同学录这样的东西,还是现在早已互留人人微博——但还是莫名其妙地失联。曾经的人人热闹的景象也不见了,取而代之的是一片沉默。

倒不是不想去联系,只是怕联系的时候只剩下一句:“好久不见。” “最近还不错。”便无话可说。谁都害怕曾经的友谊变得如此似是而非,所以干脆不联系。也有因为逐渐开始走向各自的生活轨迹,偶然想起的时候,只是害怕打扰。

六点起床只为了见她一面的那个姑娘;晚上熬夜在楼下一起抽烟的死党连同他欠我的那顿饭;失恋的时候陪我很久又突然失联的姑娘;散伙饭上抱着哭的哥们。

后来就真的再也没见过。 继续阅读