Msaeedi23 Week 11

Process for GenMapp analysis

Microarray paper: <http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4264864/> Genome Paper: <http://www.nature.com/ng/journal/v35/n1/full/ng1227.html>

Week 11

1. • For the microarray paper (GenMAPP Users only), include the following:
     1. Describe the experimental design of the microarray data, including treatments, number of replicates (biological and/or technical), dye swaps.

1. • 1. Determine the sample and data relationships, i.e., which files in the data correspond to which samples in the experimental design.

1. • 1. Construct a flow chart that illustrates the above.

DOCUMENT ALL STEPS TAKEN, MANIPULATIONS OF FILES AND ALL.

1. Experimental design-what is the treatment and what is the control

• Biological vs technical replicants- for vibrio control was the untreated strain, technical replicates = splitting a sample, different from biological replicates. Biological replicates are derived from the original strain. *note how many replicates of each. # of chips(microarrays) (for vibrio it was 9, total number of samples)

1. • • Dye swaps, cy3 green dye and cy5 red. note how many swaps. Swaps done to avoid dye playing an effect in replication.
       • Draw a diagram to help of how chips were obtained.

2. Sample + data relationship. In raw data there should be one file to each chip. Match file name to sample. raw.zip on arrayexpress has one file for each chip. Sdrf.txt open in excel to show whats in the samples-should tell you all of the samples, their matches, and dye swaps.

3. Compiled raw data file. Include columns for: ID, Sample log2FC, sample log2FC. Compiling raw data files into one spreadsheet to prepare for statistical analysis.

4. Normalization + statistical analysis. Customized for each dataset due to different treatments. Either t-test or one way anova. Also due sanity check, which will be a result in the paper. Compare it to what was written in the paper, corresponding to specific genes. Comparing log-fold changes of specific genes between our data and the paper's.

5. GenMAPP + mappfinder. Run data through database created by groupmates.

6. Deliverables-describing methods, production of tables including the sanity check, etc.

• In discussion compare what we found vs to what they found.

Mahrad Saeedi

Class Whoopers Team Page

• <https://xmlpipedb.cs.lmu.edu/biodb/fall2015/index.php/The_Class_Whoopers>

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