Reference no: EM133181181 , Length: 2000 Words

Your task

You have received a set of somatic mutations identified in a multiple myeloma cancer tumour sample. Tumours contain many somatic mutations and some of these have an active role in cancer (referred to as driver mutations), while many other mutations occur in the unstable cellular environment they do not have a role in the disease (referred to as passenger mutations). To understand better the patient's cancer you are going to use bioinformatics resources to analyse each of the mutations and assess:
1) if they are likely to have a functional effect
2) if they are more likely to be driver or passenger mutations

Greater emphasis should be placed on analysis of the functional effect (i.e. Point 1 above).
You will write up the findings of your analysis as a scientific report.

Many bioinformatics databases and web servers have been introduced in the lectures and practical sessions, it is up to you to decide which of them you are going to use. It may be that some resources are relevant for a particular mutation but not for another (e.g. some mutations will be present in protein coding regions, while others will not be).

You are expected to use PolyPhen-2, this method has been introduced in the lectures but not in the practical sessions, it is therefore down to you to work out how to use it. This represents a common task in biosciences research, where new tools are introduced and you need to work out how to use them.

For each mutation you should combine the results obtained from the analyses to suggest for each mutation if it has a functional effect and if it is more likely to be a driver or a passenger mutation and the evidence that supports your decision.

Preparing your reassessment

• Your coursework should be submitted as a scientific report containing each of the sections listed below. You mustuse the word file available on Moodleto write your report. This file includes the layout of the two compulsory tables.

• The word limit for the report is 2000 words (excluding tables, figures, legends and references), this is a MAXIMUM word limit.

• There is also a limit of up to eight tables or figures (i.e. combined total number of tables and figures.) This is a maximum - you do not need to have eight tables/figures. The two compulsory tables are included in this limit (details of their content are provided below). Figures may have multiple parts (e.g. A, B, C) as you often see in papers but each figure must fit on a single page, although the legend may be on a separate page. Note each whole figure should have a single legend, not a legend per part of a figure. If you are unsure what this means then please look at a figure in a paper (e.g. the Multiple myeloma cancer genomics paper from week 8).

• All figures and tables should have a title and a figure/table number and a legend describing them. They must also be referred to in the text. The legends can only be used to explain the figure/table and each legend has a maximum word count of 150words. i.e. do not try to use figure legends to get around the word limit. Any information that is important to your analysis should appear in the main text not only in a figure/table legend.

• The marks associated with each section are displayed below with details of the information that should be included.

• You are expected to include references formatted in a uniform style throughout, you can decide what style to use. I recommend using a reference manager, which will enable you to easily insert and edit the references present in your document.
• The report should be clearly presented. There are no marks specifically assigned for presentation of the coursework but this will factor in all of the individual sections (including referencing, figure and table formats). This means that the scientific data should be presented using a simple, clear, functional style. It is NOT an exercise in desktop publishing.

Your report should include the following sections:

Introduction

The introduction should include the following:
• an introduction to cancer genomics and your project
• the concept of functional variants and the difference between passenger and driver mutations

The two papers that have been discussed in the week 8 lectures can be primarily used to provide information for the introduction.

The introduction section for the coursework is worth 12% of the marks, so this should give an indication of the expected length of the introduction (given that the coursework word limit is 2000 words).

Methods

The methods section should describe the overall approach you have taken for analysing the mutations and details of the resources that you have used.

For each resource you should describe what it has been used for not how it works. Remember that the expectation of a methods section is that others could repeat the analysis based on this section.

The plan for your initial submission may be helpful here BUT this section must be written as a proper methods section (i.e. written in the past tense and NOT just a list of the methods used).

Results

In this section you must have a summary table at the beginning of the results showing the key points for each mutation (format provided in answer document).

In the text you should:
• Briefly review the results you have obtained and explain the selection of Driver/passenger and associated confidence - are there mutations for which there is stronger evidence that they are likely to be a driver or a passenger mutation?

• Consider the results for the mutations as a group - is a combination of mutations likely to be driving the cancer?

• Consider your results in the wider context of multiple myeloma and the literature.

• Consider how confident you can be in the results that you have obtained and the limitations of your work.

Attachment:- Bioinformatics Assessment.rar