Changes in PRIMER 6

This is a major update from V5 involving years of development. It is now a 100% .Net application. This is the technology of future Windows operating systems. (Note that PRIMER 6 is not compatible with Windows 95. This version of Windows is no longer supported by Microsoft.)

Faster - Most analyses run about 5 times faster.

Multi-tasking - No need to wait for analyses to finish. Takes full advantage of multi-processor systems.

Graphics - Completely re-written  including versatile Zoom facility. Great for plots with lots of samples.

Worksheet Grid - Purpose written, has very low overhead and greatly improves response times with very large data sets.

Interface

Now uses a workspace idea. Workspaces are saveable in their entirety; PRIMER v6 can be shut down and re-opened at a later date, recalling the workspace content in exactly the form it was left (i.e. irrespective of any subsequent changes or deletions to the data files that were originally read-in to the workspace).

Workspace Explorer -  Can be navigated to recall instantly any of the derived worksheets, plots or results windows. This is not solely a display: the tree structure is used internally to pass information between related data sheets or plots (e.g. new factors defined from a CLUSTER dendrogram are back-propagated through the similarity matrix to the original data matrix, and forward-propagated to an existing MDS plot from that same similarity sheet). Results windows are now local to each analysis, making it easier to find results at a later stage.

Data Entry - Improved dialog and wider selection of input formats. Rectangular Excel sheets of variables by samples (or samples by variables) are read in easily using a new entry ‘Wizard’, which now allows choice of sheet within the Excel file by name. PRIMER does not have the Excel constraint to 255 columns. Larger files can be read-in from multiple Excel sheets and Merged or, if created by a database package in 3-column format (‘sample number, variable number, value’), can now be read directly into PRIMER – and will be automatically converted to rectangular format.

Label Matching - Samples or variables do not need to appear in the same order for those analyses that match two different sheets (e.g. BioEnv, RELATE, ABC dominance plots, Aggregation etc). You usually only need to worry about the selection in the active worksheet and v6 will perform any selection or re-ordering needed for other sheets. One major advantage of label matching is the automatic merging of two species-by-samples sheets in which species lists are only partly overlapping (and in a different order). Consistent spelling of labels is required, naturally!

Data Types - Worksheets are given an explicit data type (abundance, biomass, environment, other), which permit sensible defaults and warnings (e.g. if ABC inputs are not of types abundance and biomass).

Data Tools - New tools include: ranking of variables (e.g. an alternative to individually transforming environmental variables); sorting (by name or factor levels) and moving data; more powerful individual transform options, that can now combine different samples, variables, numeric factors and indicators, as well as other worksheets (using the new label matching); more extensive checks on input data (including validation of aggregation files); and a new Sum tool.

Output Formats - Improved, and a wider range of options. Tables in the results windows are formatted to be able to copy and paste directly into Excel spreadsheets. Many routines will now allow summary information to be sent to a new worksheet (for further operation or export) instead of to text-format results. There is a multiple-page print option, useful for large dendrograms, and additional graphics output formats, including .jpg, .tif, .png. The standard vector format is the Windows enhanced metafile (.emf). Final point co-ordinates (e.g. of the new position of samples after rotation of an MDS plot) can also be output.

Data Input - Data sheets now permit factors on the samples (or indicators on the variables) to be read in from (or saved to) the Excel or text formats, allowing rapid transfer of all information between formats. Factors are now easily imported from other data sheets, combined to produce composite levels (e.g. a site-by-time composite factor could be used to Average or Sum over replicates for each site/time level), and levels can be given default symbols and colours for use in all plots.

Plots

Zoom - Expand any portion of a plot (ordination, dendrogram, funnel plot, draftsman plot etc), whilst retaining axes and scales. Scroll through the plot at the current magnification. This even extends to changing the aspect ratio (though not for ordinations!), by first drawing a rectangle around the portion to magnify. This is particularly useful for dendrograms, which for large numbers of points need to magnify the sample scale but not the similarity scale.

Ordination (MDS, PCA) - More flexible addition of symbols and labels denoting (different) factors. The 3-d plotting routine is greatly improved, both in respect of rotation of axes (and points, for MDS) and reflection of axes, with the ability to add labels to points in addition to symbols. Information displayed on plots is more comprehensive, with the automatic use of subtitles and a ‘history display’ to allow clear differentiation between plots from different transform and similarity options, and a key for bubble size is given when a variable is superimposed.

Clustering - Keyed symbols can now be added (independently of labels) to dendrograms, and the latter can be displayed in any one of four orientations. Clusters produced at a fixed similarity level can be identified and saved as a factor, and can then be displayed on the matching MDS. Alternatively, an MDS plot can show the results of a cluster analysis as smoothed convex contours, drawn round points that are clustered at several specified resemblance levels.

Trajectories - Points in an ordination (in 2- or 3-d) can be joined by straight line segments, in a defined order, allowing trends in time, space or environmental gradient to be more readily seen.

MDS - Diagnostics are improved: Shepard plots of distances in the ordination against original dissimilarities are given for both 2- and 3-d solutions; % contributions of individual points to the stress level are listed; an alternative fitting scheme allows a different treatment of tied similarities, and the user has more control over the precision of output stress values.

PCA - vector plots are now permitted (since the axes are linear combinations of the variables) and any pair or triple of PCs can be plotted in the 2- or 3-d configurations.

Dominance - Plots from a single sheet (abundance or biomass) can have the multiple lines identified as different levels of a factor (by differing line colours and/or symbols). For ABC curves, the full set of plots from all samples are now automatically created in one run of the routine. The (confusing) option in v5 of automatic summation of selected samples has been removed (if needed, it can be carried out using the new Sum tool prior to entering Dominance or Geometric plot menu).

Taxdtest -  The ‘funnel’ and ‘ellipse’ plots for average (and variance in) taxonomic distinctness indices are also enhanced, with more flexible choice of labels and symbols, colour shading etc

MDS Subset - Easily repeat an MDS plot  for a subset of points. Drawing a box around the subset on the plot allows a re-run of the MDS for those points, with a single click on a menu/toolbar icon!

Tools

Pre-treatment operations - Greatly expanded: standardisation options are now by species or variable, and by total or maximum; a cumulate operation assists in widening the application of these routines to size classes in particle or body-size distributions;  variables can be weighted, e.g. downweighting some species on the basis of misidentification rates. Overall transformation and normalisation options remain as in v5 but, importantly, all pre-treatments now become an initial step, separated from similarity calculations, allowing a highly flexible range of alternatives. New ‘dispersion weighting’, the downweighting of individual species counts using their innate heterogeneity.

Resemblance - The new user is still guided to ‘safe’, standard choices (e.g. Bray-Curtis on transformed species abundances, normalised Euclidean distance for environmental variables), but the more experienced user now has access to nearly 50 similarity/dissimilarity/distance measures, drawn from different literature contexts, and collectively referred to as ‘resemblance measures’. New ‘taxonomic dissimilarities’, extending the concepts of taxonomic distinctness introduced in PRIMER v5 from diversity measures to dissimilarity coefficients.

Missing values - are now tolerated in some routines and, where they are sparse, can be assumed ‘missing at random’, many fewer variables than samples are selected, and the variables can be transformed to approximate normality (e.g. environmental-type variables), an EM (Expectation-Maximisation) algorithm for optimal prediction of missing data is provided. (Use with care!)

Resemblance Tools - Tools such as transforming and ranking now apply to resemblance matrices, which allows conversion of correlation matrices to similarities, e.g. to obtain environmental variable MDS plots. Similarities can be explicitly switched to dissimilarities, and vice-versa, and another resemblance tool is a ‘Model matrix’, for building model matrices in RELATE tests (non-parametric Mantel-type): these might represent serial or cyclic trends with replication of groups.

Analyses

Several new global significance tests are provided (robust, non-parametric, permutation-based and exact), to test for presence of meaningful structure before interpreting results and displays:

SIMPER -  identifying variables that contribute most to the difference between two groups, is expanded to cover two-factor designs and to apply to Euclidean distance (e.g. for environmental variables) as well as Bray-Curtis. Other menu items are regrouped: Bio-Env and BVStep are merged (into BEST) and ANOSIM2 absorbed into the ANOSIM menu; all global permutation tests now create histograms of null distributions.

DOMDIS - , which computes distances between the curves in dominance plots, which can then be input to an ANOSIM test of a priori group structure;

BEST - match test, which allows for the bias inherent in selection of a subset of variables from one matrix (e.g. environmental) that best ‘explains’ the pattern in a second (e.g. species);

SIMPROF - (similarity profile) routine, which tests for evidence of structure in an a priori unstructured set of samples. In combination with clustering and a new facility to condense specific substructures in dendrograms (by clicking on vertical lines), this can generate trees that are pruned to objectively-defined groups. A factor defining these groups can be automatically created.

LINKTREE - a new routine to link biotic patterns to environmental variables (or similar linkage problems). Linkage trees – a non-parametric version of multivariate regression trees or CARTs – optimise successive binary divisions of biotic patterns using threshold values of environmental variables, and aim to provide piecemeal ‘explanations’ of assemblage groupings in terms of single environmental variables. It is effective in conjunction with the Bio-Env (BEST) routine, or may provide better explanations where BEST fails because forcing variables are very non-additive. It can be combined with SIMPROF, to test for the ‘significant’ structure requiring explanation.

Species-accumulation plots - now calculate and plot a wide range of richness estimators (Chao 1&2, Jacknife 1&2, Bootstrap, Michaelis-Menten, UGE) as samples are cumulated in original, specified or permuted orders. Results are sent to a worksheet for easy export.

TAXDTEST - A unique feature of v5 was the calculation of taxonomic distinctness measures of biodiversity, based on taxonomic or phylogenetic relatedness of species in a sample, and testing for ‘biodiversity loss’ by simulating selection from a master species list. v6 enhances this not only by better graphics but by the ability to use a different master list for the simulation than the sample data (e.g. fossil lists can now be compared with modern ones), and the option to specify a data sheet that determines the frequency with which each species is drawn from the master species list, when constructing the ‘null model’ simulations.