유전자 세트 농축 분석을 사용하여 경로 분석 (GSEA) 수단

유전자 세트 농축 분석에 많은 방법 중 하나입니다 유전자 발현 분석 프로필 데이터와는에 설명되어 있습니다 종이확장 연구소에서 근로자의.

기본 개념은 공부하는 관찰에 의해 메시지가 표시되었습니다 개인 유전자 두 상태 또는 phenotypes 사이의 표현 수준에서 가장 큰 차이를 보여주는 것은 기계론의 통찰력이 부족. 대신에, 그것은을 위해 더 많은 의미가 유전자 세트 일부를 공유 생물 링크, 하고 질문을 - 전체 세트는 통계적으로 표시되는 이유는 무엇입니까 중요한 강화 차동 표현이있는 유전자의?

A 유전자 세트 선택할 수 있습니다, 선천적 인, e.g 데는 여러 가지 이유가. 알려진 유전자의 집합은 이상에 의해 영향을 할- 마이크로 RNA의 이하 표현, 혹은 염색체 위치에 따라 일련의 선택, 또는 유전자가 어떤 분자 함수, 세포 구성 요소와 / 또는 생물학적 과정은의 제어 어휘를 사용하여 할당 된 유전자 온톨로지.

GSEA 접근 방식에 대한 하나의 장점은 통합 할 수 있습니다 것입니다 귀하의 전체 데이터 집합, 임의로 선택한 차동 표현 임계있는 사람 성적뿐 아니라. "어떻게이 전체 데이터 세트를 사용하는 OK 할 수 있습니다 -이을 읽고 많은 사람들이 생각됩니다 확신합니다? 일반적으로 난 단지와 유전자를 생각한다 >2 (또는 다른 좋아하는 가치를)-배 차동 표현식은. "그 접근 방식이 유효합니다 그 이유는 낮은 수준이나 복제 사이에 큰 차이가있는 표현 유전자 GSEA에서 사용되는 주요 메트릭에 기여하지 않는 것입니다, '농축 점수' (ES).

GSEA 처음으로 작동 순위 로 각 유전자의 표현 값 노이즈 신호 비 - 각 표현형을 나타내는 샘플에 대한 평균 값의 차이를 계산하고 표준 편차의 합을 기준으로 결과를 축소. 이 다른 주 (州)와 생물 사이에 약간의 변화 사이의 표현 수준에 큰 차이가있는 유전자 복제 있다는 것을 의미는 매우 순위가 결정됩니다.

다음 단계는 그 ES, GSEA에 의해 생성되는 기본 통계, 각 유전자 집합에 대해 계산 - GSEA 설명서에, 이는 훌륭하게 소프트웨어를 설명, 이 나타내는:

"모든 유전자가 처음 잡음 비율의 신호에 의해 순위가 결정됩니다, 다음 ES는 유전자의 순위 다운 "도보"로 계산됩니다 증가 a 실행 - 합 유전자가 유전자 세트에 통계 및 감소 그 안 때. The 크기 증가의에 따라 달라집니다 상관 관계 있는 유전자의 표현형. ES는 목록을 도보로 발생 0에서 최대 편차입니다. A 긍정적 인 ES는의 유전자 세트 농축을 나타냅니다 상단 순위 목록의; a 음수 ES는의 유전자 세트 농축을 나타냅니다 바닥 순위 목록의. "

ES 값은 표준화 그리고 유전자 세트의 크기와에 따라 잘못된 검색 속도 계산됩니다, 잘못된 반응의 예상 가능성을 제공 할 수. GSEA은 매우 편안한 기본 값을 사용하여 25%, 생물은 복제의 상대적으로 큰 번호와 가설 생성에 적합입니다.

에서 데이터 작업 과학자 비 인간 샘플은 여전히​​ GSEA를 사용할 수 있습니다, 하지만 필요조심하다 - 유전자 기호 "는 GSEA에 의해 사용번역"그들의 인간 등가물의 i.e에서. microarray를 대표 관심 종의 유전자에 사용되는 식별자들은 대한 기호로 변환 인간 orthologues, 다음 분석에 사용. Subramanian 및 동료 주장 이 전환은 거의가 있거나하는 효과가 없어요 GSEA의 유틸리티에 대한; 그것은 여러 아닌 인류에 성공적으로 사용되었습니다, 상세 결과를 조사했을 때 물론이 방법은 염두에 보관해야합니다.

훌륭한을 위해, 에 대한 심층적 인, 경로 도구의 검토, 상담:

Khatri, P., Sirota, M., & 버트, A. J. (2012). 경로 분석 십 년: 현재 접근법과 뛰어난 과제. PLoS 전산 생물학, 8(2), e1002375. 두:10.1371/journal.pcbi.1002375

경로 분석에 대한 조언의 또 다른 좋은 소스, 특히 R 통계 패키지에 익숙한 사람들은을위한 여기에.

추가 읽기

Subramanian, Tamayo P, Mootha VK, Mukherjee S, 에베르트 BL, 질레트 MA, 파울로 비치, Pomeroy SL, Golub TR, 착륙선 ES, Mesirov J​​P (2005) 유전자 세트 농축 분석: 게놈 전체의 표현 프로파일을 해석하는 지식 기반 접근 방식. Proc Natl Acad 문화 U S 102:15545-15550

시 X, 루 J, EJ Kulbokas, Golub TR, Mootha V, Lindblad - 토 K, 착륙선 ES, 켈리스 M (2005) 체계적인 인간의 발기인의 규제 작품의 발견과 3[청춘] 여러 포유류의 비교에 의해 UTRs. 자연 434:338-345

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학술 과학 책을 편집 기쁨

Image courtesy of ningmilo / FreeDigitalPhotos.net

Or: “A beginner’s guide to herding cats”.

Consider this scenario: you are an academic scientist, in a busy research institute and your boss is invited to edit a book, but declines due to pressure of work; then suggests that it would look good on your CV. You agree, it would look good on your CV, so you commit yourself to editing your first multi-author academic science book.

So why is that a problem?

Getting authors on board

You want the best people to write the chapters. You Google some big-name experts and invite them to contribute a chapter to your book. They almost all decline, or fail to reply to your email. But, somewhat to your amazement, one agrees. 그러나, this paragon of science then never, ever replies to any future contacts. 그래서, you lower your sights and aim for good scientists, but not Nobel Prize winners. 최종적으로, you get enough authors together to write the chapters around the topic that the publishers have given you – phew!

Getting authors to agree a deadline

Assuming it’s not unreasonable, everyone is usually relaxed about the deadline set. 그러나, the real challenge is:

Getting them to meet the deadline

  1. This should be easy, right? Scientists are grown-up, professional people. Aren’t they? 잘, sort of. In reality, academics typically over-commit themselves, doing not only research and teaching, but also writing grant funding applications, papers, reviews, book chapters, etc, 등. After all, the scientific mission statement is “publish OR be damned.”
  2. As the deadlines go past – “wooshh”, like passing cars, half your authors have submitted their chapters, the rest not. Now another sticky moment arrives – these are meant to be cutting edge reviews. State-of-the-Art. But this delay now means that the ‘good’ authors work is rapidly reaching its sell-by date. You may have to go crawling back to them to ask for updates. Which they are usually not too unhappy about, but you hate the loss of face.
  3. One more thing that I forgot to mention; as the editor, you have to READ these chapters. Worse still, you are expected to produce cogent critiques – what the author needs to add, remove, expand or contract. Even if the topic is on the fringe of your main expertise.

What happens if authors go AWOL?

What do you do when one of your authors decides that they are NOT going to write their chapter? Not simply procrastinate, fail to meet deadlines, but stop all communication. Disappear off the map. So, now you’re stuck – find another au그래서or(s) – more delay – write the chapter yourself? – but it’s too far outside your own area of expe그래서ise. So, eventually, you find someone else. Which means yet more delay.

Writing your own chapter

Oh, yes, you forgot that you agreed to write one of the chapters yourself. Oops. Oh well, not a problem. Offer co-authorship to one of your PhD students – they’ll be falling over themselves to get another publication on their CV. Or maybe not: no, they are not interested after all; obviously suspecting (correctly) that your aim is to let them write the whole thing, then submit the chapter to you for a little light editorial polishing.

Pleading with the publishers for more time

  1. You now hold the dubious record for the longest gestation period of a multi-author academic book in human history, excluding the Bible.
  2. ‘Please, sir, I want some more.’
  3. The publishers are not impressed, but quietly resigned, telling you to go away and come back when you meet a new deadline.

Losing your marbles and giving up completely

It’s all taking SO LONG – too few authors have submitted first drafts of their chapters. You start to get desperate – the original deadline was so long ago that you’ve forgotten it – the “new” deadline is also now history. You consider giving the whole thing up – apologise to the authors and the publishers and say the book can’t be finished. But your co-editor and the authors who have delivered on time are indignant – naturally enough they don’t want to see their work wasted – and insist that you go back to the recalcitrant scientists with a big stick. How do you threaten authors with a stick by email? Or by phone? 그러나, a combination of the metaphorical big stick, pleas for mercy and piling on the guilt eventually work and all the chapters are delivered! Hooray.

Hooray!

그래서, now, you’re on the last lap. Or the last dregs – the soul-destroying process of assembling the index and proofreading. Once, a sub-editor with a scientific background might have written an index, but not now. Academic publishers want their pound of flesh, so this task is delegated to authors and editors. Authors select keywords from their chapters, with varying degrees of enthusiasm or accuracy, then the editor attempts to assemble them into something useful to the reader. 최종적으로, a draft proof arrives by email. You are now heartily sick of every word, but a final spurt of enthusiasm drives you on and the book is finished.

One more thing – did I forget? – you don’t get paid – but you are given a few free copies of your own book. Such fun!

 

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어떻게 전사 인자의 원인 접착제의 귀에 돌연변이을 수행?

Acute otitis media, sometimes known as “glue ear”, is the most common bacterial infectionchildren and by 1 year of age about 60% of children will have had one episode. In some cases, children develop a chronic condition, which, despite the infection being cured, the “glue” doesn’t go away and causes deafness.  In an inherited 마우스 model of chronic glue ear the causative mutation has been shown to be in a gene encoding a transcription factor, Evi1.

The EVI1 protein has multiple domains, can repress or enhance expression of target genes and interact with many other proteins. 참으로, the multiplicity of known and potential interactions is a challenge to determining the role of the mutation.  There were clues, however, as to how this mutation might lead to disease from differences in phenotype e.g. mutant mice raised in a “clean” SPF animal facility were less likely to become deaf than those kept in the older, “dirty” animal house.

Did this mean that gene-environment interactions e.g. between immune system and microbes, influence disease susceptibility? It was also known that mutant mice showed high levels of influx of neutrophils into their middle ear cavities (inflammation), but it was unclear whether EVI1 was acting directly or indirectly in this process. Possible answers to these questions came recently from studies in cultured cells, showing that EVI1 can act as an inhibitor of one of the key proteins regulating inflammation, another transcription factor, nuclear factor kappa B (NFkB).  EVI1 binds to to one of the subunits of NFkB and interferes with a critical protein modification, acetylation.  However, EVI1 does not acetylate proteins directly, so other factors must be involved. What were those other factors?

I combined public and unpublished data using literature searchesopen source software e.g. iRefWeb in order to identify steps in the NFkB signalling pathways that might be disturbed by the mutation in EVI1.  The novel target proteins and starting points for drug development I discovered are suitable for testing in this preclinical model of chronic otitis media.

Read our testimonial from Dr Michael Cheeseman.

 

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Target discovery in childhood-onset asthma

Asthma is caused by a combination of environmentalgenetic influences, but the specific factors are poorly understood. A significant “hit” detected in a genome-wide association scan (GWAS) for childhood asthma led a client to believe that one gene might be partially responsible. Proving that this genetic association really was causing asthma was, however, difficult. Firstly, no one knew the function of the protein made by the gene and secondly, changing genes in humans to test a hypothesis, rather than as therapy, is technically challenging & ethically questionable, especially in children. Fortunately, mice share about 90% of their genes with humans, so scientists “knocked-out” the equivalent gene, then tested whether these animals behaved like children with asthma. The short answer is – they didn’t. In lung-function tests that would have had asthmatics reaching for their inhalers, the knock-out mice were completely 표준. 그래서, what was going on? Were mice not enough like humans? Was this the wrong gene?

For this project, I went back to first principles – what was the evidence supporting the idea that this gene was responsible for increased asthma risk? Digging through the online literature, in particular papers from other groups studying the same gene and supplementary material not available in print, there were suggestions that the genetic effects were more complex. I found evidence that two other genes nearby were either more or less transcriptionally active in asthmatics and so might play a role in susceptibility to asthma. Furthermore, using data from the ENCODE project, I found that the regulatory element predicted to control these genes was conserved in mice, so it would be possible to test the predictions experimentally.

This suggested a novel therapeutic target – altering the activity of a cluster of genes, rather than just one, might alter disease risk.

Testimonial

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유전자 발현 데이터의 경로 분석 – 남자 감소 다산 / 불임

A group of animals that can breed and produce fertile offspring is one of the definitions of a species.

This means that the biological mechanisms of fertility and infertility are of interest not only to evolutionary biologists, but also to clinicians and of course to the wider public. At the Institute of Molecular Genetics in Prague, 교수. Jiri Forejt is studying what controls fertility in the hybrid offspring produced by the mating of mouse sub-species. He wanted to know why some male mice were infertile – he knew that genes in one particular genome region were important, but not how those genes influenced the expression of the rest of the genome.

This is where I was recruited into the team, to help with identifying the classes of genes disrupted in mice with reduced fertility. Scientists in his group had produced Affymetrix gene expression results from the testes of fertile, sub-fertile and infertile mice and I analysed these data genome-wide for differentially-expressed transcripts. Using the Broad Institute’s marvellous GSEA tool, I assessed the statistical evidence that specific Gene Ontology terms and pathways were over-represented and also whether differential genes were localised to particular genome regions. This analysis uncovered evidence that specific, functionally related sets of genes were over-represented in the expression data and helped to develop novel hypotheses about the causes of reduced fertility.

Posted in 경로 분석, 대상 발견 | 1 Response

상속 근육 약점의 대상 발견

Muscle weakness can be caused by a rare inherited disease called myofibrillar myopathy. Gonzalo Blanco’s team found a mouse model of this disease and wanted to identify the underlying cause of the severe muscle weakness. Their aim was to discover potential therapeutic targets to translate into pre-clinical and clinical studies.

Before I became involved, the disease had been mapped to a large region of one chromosome and Dr Blanco’s team were planning to use conventional positional cloning methods to find the mutation. I proposed that a faster approach would be to use next-generation sequencing targeted at genes in the region. I designed a set of probes to enrich specific DNA fragments and I worked with a bioinformatician, 박사. Michelle Simon, to design a software pipeline to find and characterise mutations.

At the end of the design process, the pipeline was used to identify mutations in the muscle weakness mutants and predict that they altered the coding sequences of two genes; Myh4Pmp22. Two lines of evidence suggested that the mutation in Myh4, which codes for a muscle myosin protein, was the most likely cause of the weakness. Firstly, our colleagues found that mice carrying only the myosin mutation still had the trait and secondly, abnormal protein aggregates from affected mice contained large amounts of the myosin.

Scientists at the MRC’s Mammalian Genetics Unit have used the same approach, that Michelle Simon and I pioneered, to find mutations in other disease models.

Publication in Human Molecular Genetics

Testimonial from 박사. Gonzalo Blanco

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