02-Crab-qpcr
================

``` r
library("dplyr")
```

    ## 
    ## Attaching package: 'dplyr'

    ## The following objects are masked from 'package:stats':
    ## 
    ##     filter, lag

    ## The following objects are masked from 'package:base':
    ## 
    ##     intersect, setdiff, setequal, union

``` r
qpcr <- read.csv("../data/hematqpcr_crabRNA.csv")

head(qpcr)
```

    ##       Uniq_ID  FRP tube_number trtmnt_tank sample_day infection_status maturity
    ## 1 6101_206_12 6101         206        cold          2                0        I
    ## 2 6101_415_26 6101         415        cold         17                0        I
    ## 3   6101_84_9 6101          84        <NA>          0                0        I
    ## 4   6102_18_9 6102          18        <NA>          0                0        I
    ## 5   6102_18_9 6102          18        <NA>          0                0        I
    ## 6 6102_439_26 6102         439        cold         17                0        I
    ##   RNA_ng.ul total.yield_ng elution_vol_ul org_sample_ul target sq_all.runs_mean
    ## 1     19.90         258.70             15            70 Hemato           42.225
    ## 2     12.30         159.90             15            70 Hemato           42.225
    ## 3     34.70         451.10             15            70 Hemato           42.225
    ## 4      4.46          57.98             15            70 Hemato           32.544
    ## 5      4.46          57.98             15            70 Hemato           32.544
    ## 6     21.60         280.80             15            70 Hemato           32.544
    ##   sample_pos.neg Library_ID
    ## 1            pos     329775
    ## 2            pos     329777
    ## 3            pos         NA
    ## 4            neg         NA
    ## 5            pos         NA
    ## 6            neg     304428

Want to get average sqallmeans for each FRP…

``` r
avQpcr <- group_by(qpcr, FRP) %>%
summarize(avg_sq = mean(sq_all.runs_mean, na.rm=TRUE), trtmnt_tank, infection_status, maturity, sample_pos.neg) %>% 
distinct_all() %>%
filter(trtmnt_tank == "cold" | trtmnt_tank == "warm" | trtmnt_tank == "ambient")
```

    ## `summarise()` has grouped output by 'FRP'. You can override using the `.groups` argument.

``` r
avQpcr
```

    ## # A tibble: 210 x 6
    ## # Groups:   FRP [172]
    ##      FRP avg_sq trtmnt_tank infection_status maturity sample_pos.neg
    ##    <int>  <dbl> <chr>                  <int> <chr>    <chr>         
    ##  1  6101   42.2 cold                       0 I        pos           
    ##  2  6102   32.5 cold                       0 I        neg           
    ##  3  6102   32.5 cold                       0 I        pos           
    ##  4  6103  183.  cold                       1 I        pos           
    ##  5  6104   18.6 cold                       0 I        neg           
    ##  6  6104   18.6 cold                       0 I        pos           
    ##  7  6106   78.8 cold                       0 M        pos           
    ##  8  6107   61.2 ambient                    0 M        neg           
    ##  9  6107   61.2 ambient                    0 M        pos           
    ## 10  6108   71.1 cold                       1 I        pos           
    ## # … with 200 more rows

``` r
library(ggplot2)
```

``` r
ggplot(avQpcr, aes(x = avg_sq)) +
  geom_histogram(bins = 100) +
  scale_x_log10() +
  facet_grid(~infection_status)
```

    ## Warning: Transformation introduced infinite values in continuous x-axis

    ## Warning: Removed 26 rows containing non-finite values (stat_bin).

![](02-crab-qpcr_files/figure-gfm/unnamed-chunk-5-1.png)<!-- -->