Difference between revisions of "Paul"
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"We assume that the number of reads in sample j that are assigned to gene i can be modeled by a negative binomial (NB) distribution, | "We assume that the number of reads in sample j that are assigned to gene i can be modeled by a negative binomial (NB) distribution, | ||
Kij~NB(μij,σ2ij)" | Kij~NB(μij,σ2ij)" | ||
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| + | Goals for Data Analysis and Representation: | ||
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| + | 1. Determine Control Differential Expression Between Maternal Paternal (no need to extensively analyze) | ||
| + | 2. Subtract the control differences from the experimental differences between Trisomic | ||
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| + | Join BeD data and ensembl | ||
Revision as of 15:57, 14 February 2017
Paul's Notes
Understanding the Galaxy Data:
We care about: Fold Change, P-value
Think about total gene expression values and gene functions. Be aware that large gene expression values can be paired with low fold change, but that cn still be significant.
In the data input, the first data set (numerator) and second data set (denominator) order is important to sign of fold change.
Possible tests: M WT vs P WT, disomic vs trisomic
truncation for excel ensembl gene numbers: =left(A1,18)
Potentially helpful DEseq paper: http://genomebiology.biomedcentral.com/articles/10.1186/gb-2010-11-10-r106
https://www.bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.pdf
DEseq2: uses negative binomial distribution to model gene expression "We assume that the number of reads in sample j that are assigned to gene i can be modeled by a negative binomial (NB) distribution, Kij~NB(μij,σ2ij)"
Goals for Data Analysis and Representation:
1. Determine Control Differential Expression Between Maternal Paternal (no need to extensively analyze) 2. Subtract the control differences from the experimental differences between Trisomic
Join BeD data and ensembl
