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R: read.delim2 .txt file and calulate mean of 5 classes

################################################################################
# MC TEST data set by H.Wright                                                 |
#                                                                              |
#                                                                              | 
################################################################################
# set working directory file path
setwd("D:\\Projects\\R_analysis\\mc_30.12.2010\\")
# load the test marechiara dataset 
read.delim2 (file="D:\\Projects\\R_analysis\\mc_30.12.2010\\mc_test1.txt", 
          na.strings = "NA", 
          nrows = -1,
          skip = 0, 
          check.names = TRUE, 
          strip.white = FALSE, 
          blank.lines.skip = TRUE)
# assign data table to object 'mc' 
mc<-(read.delim2  (file="D:\\Projects\\R_analysis\\mc_30.12.2010\\mc_test1.txt", 
          na.strings = "NA", 
          nrows = -1, 
          skip = 0, 
          check.names = TRUE, 
          strip.white = FALSE, 
          blank.lines.skip = TRUE))
# obtain the data table column variables
names(mc)
#[1] "year"    "Acartia.clausi"     "Acartia.danae"      "Acartia.discaudata" "Acartia.longiremis" "Acartia.margalefi"      
 
#define variables in object mc
  col2 <-mc$Acartia.clausi
  col3 <-mc$Acartia.danae
  col4 <-mc$Acartia.discaudata
  col5 <-mc$Acartia.longiremis
  col6 <-mc$Acartia.margalefi
#take the mean of each variable
     mean(col2)
          mean(col3)
               mean(col4)
                    mean(col5)
                         mean(col6)

Created by Pretty R at inside-R.org

R: read.delim2 .txt file and calulate mean of 5 classes

################################################################################
# MC TEST data set by H.Wright                                                 |
#                                                                              |
#                                                                              | 
################################################################################
# set working directory file path
setwd("D:\Projects\R_analysis\mc_30.12.2010\")
# load the test marechiara dataset 
read.delim2 (file="D:\Projects\R_analysis\mc_30.12.2010\mc_test1.txt", 
          na.strings = "NA", 
          nrows = -1,
          skip = 0, 
          check.names = TRUE, 
          strip.white = FALSE, 
          blank.lines.skip = TRUE)
# assign data table to object 'mc' 
mc<-(read.delim2  (file="D:\Projects\R_analysis\mc_30.12.2010\mc_test1.txt", 
          na.strings = "NA", 
          nrows = -1, 
          skip = 0, 
          check.names = TRUE, 
          strip.white = FALSE, 
          blank.lines.skip = TRUE))
# obtain the data table column variables
names(mc)
#[1] "year"    "Acartia.clausi"     "Acartia.danae"      "Acartia.discaudata" "Acartia.longiremis" "Acartia.margalefi"      
 
#define variables in object mc
  col2 <-mc$Acartia.clausi
  col3 <-mc$Acartia.danae
  col4 <-mc$Acartia.discaudata
  col5 <-mc$Acartia.longiremis
  col6 <-mc$Acartia.margalefi
#take the mean of each variable
     mean(col2)
          mean(col3)
               mean(col4)
                    mean(col5)
                         mean(col6)

Created by Pretty R at inside-R.org

catching up on projects

As the title says, I am catching up on projects today.  When is one ever completely caught up on projects? Perhaps it seems un-ending, but today I will make an attempt to push through more of the image analysis phase.  As I mentioned in an earlier post, I collaborated with a colleague last summer at the Shoals Marine Lab.  This project will provide some baseline data on the phytoplankton community composition in and around the Isle of Shoals Archipelago.  Using the FLOWCAM particle imaging system developed in Boothbay, Maine, we sampled from a set of incubations over a 6 day time period to determine abundance and diversity.  To my knowledge, plankton based experiments are not conducted frequently (if at all) on the island due to the lack of resources and/or expertise in this field of research.  Many of the courses at the advanced undergraduate level are organismal based and although this is extremely valuable for a field based ecologist or marine biologist, I still believe that understanding microbial ecology is important.

In order to complete the data analysis phase of this project, I must first process the raw data images.  This sounds straightforward in theory, and more efficient than manually counting microscope samples…however, it is still extremely time consuming and assumes that you have 1) a working knowledge of phytoplankton taxonomy (or the Tomas bible) and 2) a solid understanding of the proprietary software Visual Spreadsheet.

I will be posting more progress updates regarding the SML Nutex (nutrient experiment) project soon…and images, I promise some photos of phytos.

Stirring Up a Bloom off Patagonia

Stirring Up a Bloom off Patagonia : Image of the Day.

From NASA’s ocean color satellite images is a gorgeous MODIS view of the Patagonian shelf break region.  The picoplankton community analysis I conducted as part of my Master’s thesis was from samples taken during the COPAS08 cruise cited in Painter’s article.  The satellite resolution has improved so that it’s possible to detect broad taxonomic groupings from the ocean color algorithms.  I follow this region of the SW Atlantic since my participation in this cruise out of scientific interest.  I hope that future analysis of the picophytoplankton samples through molecular probing leads to some interesting results.

Painter, S.C., et al (2010). The COPAS’08 expedition to the Patagonian Shelf: Physical and environmental conditions during the 2008 coccolithophore bloom. Continental Shelf Research, 30 (18), 1907-1923.

Stirring Up a Bloom off Patagonia

Stirring Up a Bloom off Patagonia : Image of the Day.

From NASA’s ocean color satellite images is a gorgeous MODIS view of the Patagonian shelf break region.  The picoplankton community analysis I conducted as part of my Master’s thesis was from samples taken during the COPAS08 cruise cited in Painter’s article.  The satellite resolution has improved so that it’s possible to detect broad taxonomic groupings from the ocean color algorithms.  I follow this region of the SW Atlantic since my participation in this cruise out of scientific interest.  I hope that future analysis of the picophytoplankton samples through molecular probing leads to some interesting results.

Painter, S.C., et al (2010). The COPAS’08 expedition to the Patagonian Shelf: Physical and environmental conditions during the 2008 coccolithophore bloom. Continental Shelf Research, 30 (18), 1907-1923.

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