Use of Computers in Biometrics

GermplasmInternational Plant Genetic Resources Institute (IPGRI)International Potato Center (CIP).International Center for maize and Wheat Improvement (CIMMYT).International Rice Research Institute (IRRI).International Crops research Institute for the Semi-Arid Tropics (ICRISTAT).

Plant Introduction StationsNorthern RPIS, Geneva, New York:

Perennial clover, onion, pea, broccoli, timothy.

Southern RPIS, Georgia:Cantaloupe, cowpea, millet, peanut, sorghum, pepper

North Central RPIS, Ames, Iowa:Alfalfa, corn, sweet clover, beets, cucumber, tomato.

Plant Introduction StationsWestern RPIS, Pullman, Washington:

Bean, cabbage, fescue, wheat, grasses, lentil, lettuce, safflower, chickpea

State and federal Potato Introduction Station, Wisconsin:

Potato

Information

Germplasm Information Resources Network

(GRIN)

Experimental Design

Clerical OperationsDesigning and printing field plans and plot plans.Label printing ~ Planting; harvest; seed inventory and storage.Score books.Data summaries, tables.Keeping track of where things are and what has been done to what lines.

Data Management

Collect data in suitable computer form.◦ Pencil & paper.◦ Handheld data logger.◦ Direct from analog/digital device.Validate data, check for errors.Sort data into suitable order for analyses, including transformation.

Data Storage

Database Management Systems.Spreadsheet.Data types.◦Alpha/numeric characters.◦Numerical data.

Data Analyses and Interpretation

Missing values.Analyze subset of total number of replicates.Handle data transformation.Derive variables.

Data Analyses and Interpretation

Analyze data from each character and location.Analyze multiple characters and sites.Interpretation: ◦ histograms; scatter diagrams; data

tables, correlation, regression, multivariate transformations.

Other Considerations

User FriendlyConsultation with a statistician

Commonly use Software

Experimental Design & Analyses.◦MSTAT, MiniTab, SAS, GENSTATSpreadsheets and data bases.◦ Excell, Lotus 1-2-3, DBase IIIGraphics.◦ PowerPoint, Harvard Graphics, + many

others

Introduction to SAS

SAS is comparable to a high level computer language.◦Specific statements to manipulate

and analyses data.Operates on a “batch” system, designed for punch cards.

Produces:◦ SAS LOG with messages about the

execution of the batch program.◦ SAS LIST with specified output.PC SAS has “windows”◦ Program editor window (in place of

punch cards).◦ LOG window.◦ OUTPUT window.

Introduction to SAS

SAS statements◦ Always use a semi-colon after each

SAS statement;◦ Can have more than one statement

per line;◦Wrap statements into additional

lines;◦ Comment lines start with asterisk;

Introduction to SAS

DATA step

;

PROC step

;

RUN;

Introduction to SAS

File managementData sets can be named:

i.e. DATA newdata;Can be accessed several times in one SAS session if named.Lost when exit SAS.

Permanent data sets called SAS Libraries are not lost on exit, but must be set up in advance.

Introduction to SAS

File management;Combine SAS statements and data in one file.Have SAS statements in one file and data in another (ASCII) file.

INFILE ‘jackdata.dat’Simplest to have one line of data per experimental unit and enter data in parallel.

Introduction to SAS

DATA step• data statement DATA name;

• program statements.setup options;

page size, page numbers, etc.;assign variable names;add titles to output;

Introduction to SAS

DATA step;

• read data into SAS file;

• perform math functions;= + - * / **

• conditional statementsIF rep = 4 THEN DELETE;

• discard variables from data set;

Introduction to SAS

Variables and variable names;Character variables indicated by a $ symbol.

i.e. INPUT variety $ rep yield;Characters data is case sensitive.JACK # jack;

Variable names limit to 8 characters for output.

Introduction to SAS

PROCedure step;◦ Output selected data for printing.◦ Summarize data.◦ Perform statistical analyses.

Introduction to SAS

Common PROC’sMEAN; STAND; SUMM;

TABUL; UNIVAR; PLOT;

ANOVA; GLM; ORTH;

NLIN; REG; STEPW;

CORR; CLUST; PRINCE;

Introduction to SAS

Univariate analysisDATA numbers;

Title “Univariate Procedure Example”;

INPUT yield;

CARDS;

10.2 14.6 17.9 9.23 21.6 …;

PROC UNIVARIATE;

RUN;

RCB Analysis of VarianceDATA;

INPUT variety $ rep nitrogen yield;

CARDS;

Ericka 1 1 24.5

Ericka 2 2 26.3

Ericka 3 3 30.7

.

Ceres 4 3 29.5

RCB Analysis of Variance

: :

PROC ANOVA;

CLASSES rep variety nitrogen;

MODEL yield = rep variety nitrogen variety*nitrogen;

MEANS variety nitrogen /LSD;

RUN;

RCB Analysis of VarianceDATA;

INPUT variety $ rep nitrogen yield; CARDS;

Ericka 1 1 24.5

Ericka 2 2 26.3

Ericka 3 3 30.7

. . . . . .

Ceres 4 3 29.5

PROC ANOVA;

CLASSES rep variety nitrogen;

MODEL yield = rep variety nitrogen variety*nitrogen;

MEANS variety nitrogen /LSD;

RUN;

Need Help?◦Help Icon.◦SAS Manual◦SAS/ASSIST icon.◦Friendly Technicians.◦Ag. Stats. Program

(Bill Pyle).

Introduction to SAS

Experimental Design