# Correlating Crab Variables, Fixed

Alright, last time I created a correlation matrix from this table. However, during Pubathon, it was pointed out that I should probably check to make sure I’m doing things correctly. As it turns out, I wasn’t (thanks, Matt!) Basically, I had to separate my normally-distributed and non-normally-distributed variables (as determined by a Shapiro-Wilk test), along with my continuous and categorical variables. However, since all my categorical variables were (unsurprisingly) non-normal, I just was left with two groups – normal and non-normal. I compared the normal ones using Pearson’s test, the non-normal ones with Kendall rank-correlation test, and then cross-compared using Kendall rank-correlation again. This produced 3 sets of plots. Each set contains: 1 dot plot (big dot = higher absolute value of correlation, blue = positive, red = negative) and: 1 correlation chart (number = correlation, plot = plot of correlation) Note: On the following plots, the variables can be…

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# Correlating Crab Variables

A pretty basic question that I haven’t really answered yet is how different variables are actually correlated with each other! So to figure this out, I decided to make a correlation matrix. Each variable applies to one individual crab. So we’re leaving the time dimension out of it, and are just examining covariance between crabs. I made this table a while back. Each row is a value for each individual crab. As a reminder, the three transcriptomes used for alignment in this experiment are: cbai_transcriptomev2.0: unfiltered by taxa cbai_transcriptomev4.0: filtered, presumably only C. bairdi seqs hemat_transcriptomev1.6: filtered, presumably only Hematodinium seqs The following columns are present: Crab ID (A-I) Uniq_ID: This links the notation used in Grace’s analysis (and mine) with some of the earlier Jensen tables Treatment: The temperature treatment the crab was exposed to Timepoints:The number of timepoints (3 for ambient- and lowered-temperature treatment groups, 2 for elevated)…

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