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Mechanisms of Mitosis Data Analysis You are now ready to statistically analyze the data your team has collected. I. Mitotic Index and Mitotic Phase Indices Your mitotic cell counts comprise a survey of the number of different stages of mitosis in your two populations (treatment and control). You counted mitotic cells in 8 treatment and 8 control roots, and then calculated a Mitotic Index (M) for each sample. M=n m /N n m = the number of mitotic cells in the sample N = the total number of cells counted in the sample. You also calculated a Mitotic Phase Index (Mxxx) for each phase of mitosis you found in your treatment and control groups. M phase =n phase /n m n phase = # of cells in [mitotic phase] in the sample n m = total number of mitotic cells in the sample Use the indices you recorded in the table templates during Sessions 3 and 4 for the data analysis described in the following section. II. Applying a Statistical Test to Your Mitotic Indices Your mitotic indices are ordinal, non-parametric data that are not distributed along a normal curve. The non-parametric Mann-Whitney U test is appropriate for this type of data. The Mann Whitney U test measures the degree of overlap between two sets of data that can be ranked (i.e., put in order of ascending values). large overlap means no significant difference between your populations o fail to reject the null hypothesis small (5% or less) overlap means a significant difference between your populations o reject your null hypothesis. Non-parametric test for two samples: Mann-Whitney U The Mann-Whitney test allows the investigator (you) to compare your two cell populations without assuming that your Mitotic Index values are normally distributed. The Mann-Whitney U does have its rules. For this test to be appropriate: You must be comparing two random, independent samples (treatment & control) The measurements (Mitotic Indices) should be ordinal No two measurements should have exactly the same value o (though we can deal with “ties” in a way that will be explained shortly)

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Page 1: 151F19 mitosis data analysis - University of Miami › dana › 151 › 151F19_mitosis_data_analysis.pdf · Mechanisms of Mitosis Data Analysis You are now ready to statistically

MechanismsofMitosisDataAnalysis

Youarenowreadytostatisticallyanalyzethedatayourteamhascollected.

I.MitoticIndexandMitoticPhaseIndicesYourmitoticcellcountscompriseasurveyofthenumberofdifferentstagesofmitosisinyourtwopopulations(treatmentandcontrol).Youcountedmitoticcellsin8treatmentand8controlroots,andthencalculatedaMitoticIndex(M)foreachsample.

M=nm/N

nm=thenumberofmitoticcellsinthesampleN=thetotalnumberofcellscountedinthesample.

You also calculated aMitotic Phase Index (Mxxx) for each phase ofmitosis you found in yourtreatmentandcontrolgroups.

Mphase=nphase/nm

nphase=#ofcellsin[mitoticphase]inthesamplenm=totalnumberofmitoticcellsinthesample

UsetheindicesyourecordedinthetabletemplatesduringSessions3and4forthedataanalysisdescribedinthefollowingsection.II.ApplyingaStatisticalTesttoYourMitoticIndicesYourmitotic indicesareordinal, non-parametric data thatarenotdistributedalonganormalcurve.Thenon-parametricMann-WhitneyUtestisappropriateforthistypeofdata.

TheMannWhitneyUtestmeasuresthedegreeofoverlapbetweentwosetsofdatathatcanberanked(i.e.,putinorderofascendingvalues).

• largeoverlapmeansnosignificantdifferencebetweenyourpopulationso failtorejectthenullhypothesis

• small(5%orless)overlapmeansasignificantdifferencebetweenyourpopulations

o rejectyournullhypothesis.Non-parametrictestfortwosamples:Mann-WhitneyUTheMann-Whitneytestallowstheinvestigator(you)tocompareyourtwocellpopulationswithoutassumingthatyourMitoticIndexvaluesarenormallydistributed.TheMann-WhitneyUdoeshaveitsrules.Forthistesttobeappropriate:

• Youmustbecomparingtworandom,independentsamples(treatment&control)• Themeasurements(MitoticIndices)shouldbeordinal• Notwomeasurementsshouldhaveexactlythesamevalue

o (thoughwecandealwith“ties”inawaythatwillbeexplainedshortly)

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1.Stateyournullandalternativehypotheses.

Ho:

HA:

Example: Ho:ThereisnodifferenceintheranksofMitoticIndices(M)betweenmeristematiccellsin anoniontreatedwithaqueoustrifluralinandanoniontreatedwithplainwater.

HA:ThereisadifferenceintheranksofMitoticIndices(M)betweenmeristematiccellsin anoniontreatedwithaqueoustrifluralinandanoniontreatedwithplainwater.

2.Statethesignificancelevel(tobecomparedtoa,0.05)requiredtorejectHo. Thisistypicallyaprobabilityvalue(P)of<0.05

3.RankyourMitoticIndicesfromsmallesttolargestinatable Notewhichindexcamefromwhichpopulationofcells(TreatmentorControl).

Example:• Table1shows16(imaginary)MIfromtreatment(T)andcontrol(C)onionroottips.• Table2showsthevaluesrankedandlabeledbypopulation.

Table1.MitoticIndicesfor Table2.RankedMitoticIndicestreatmentandcontrolroottips Notetiedvaluesinblue.Sample#

Mtreatment

Mcontrol Rank RankedMvalues

CellPopulation

1 0.20 0.55 1 0.10 T2 0.25 0.60 2 0.15 T3 0.45 0.65 3 0.20 T4 0.35 0.80 4 0.25 T5 0.15 0.35 5 0.35 T6 0.10 0.75 6 0.35 C7 0.55 0.70 7 0.40 T8 0.40 0.85 8 0.45 T 9 0.55 T 10 0.55 C 11 0.60 C 12 0.65 C 13 0.70 C 14 0.75 C 15 0.80 C 16 0.85 C

4.Assignpointstoeachrankedvalue(seeTable3):• Each“treatment”rankgetsonepointforevery“control”rankthatappearsbelowit.• Every“control”valuegetsonepointforevery“treatment”valuethatappearsbelowit.• Forexample,thefirstvalue,0.10(T)has8Controlvaluesbelowit,soitgets8points.• Value10(C)has3Treatmentvaluesbelowit,soitgets3points.• Tiedvaluessplitthesumoftheirpoints.Forexample:

o Rank5(0.35)has8pointso Rank6(0.35)has3pointso 8+3=11o Eachrankgetshalfof11,or5.5

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Table3.PointsassignedtorankedMvaluesinTreatmentandControlonioncellpopulations.(example)Tiedvaluessplittheirtotalpointsequally.Rank RankedM

valuesCellpopulation

Points

1 0.10 T 82 0.15 T 83 0.20 T 84 0.25 T 85 0.35 T 8à5.56 0.35 C 3à5.57 0.40 T 78 0.45 T 79 0.55 T 7à3.510 0.55 C 0à3.511 0.60 C 012 0.65 C 013 0.70 C 014 0.75 C 015 0.80 C 016 0.85 C 05.CalculateaUstatisticforeachcategorybyaddingthepointsforeachcellpopulation.

Utreatment=8+8+8+8+5.5+7+7+3.5=55Ucontrol=5.5+3.5+0+0+0+0+0+0=9

YourUstatisticisthesmallerofthesetwovalues.IntheimaginaryexampleourUvalueis9.ThelowertheUvalue,thegreaterthedifferencebetweenthetwogroupsbeingcompared.(Forexample,ifnoneoftheMvaluesoverlapped,theUvaluewouldbezero.)III.Criticalvaluesfornon-parametricstatisticsWehavedefinedoursignificancelevel(a)as0.05.Thisimplies:

• atruenullhypothesiswillberejectedonly5%ofthetime• afalsenullhypothesiswillberejected95%ofthetime

…ifthePvalueobtainedfromyourdataislessthanorequalto0.05.Acritical value of a statistic (e.g.,Mann-WhitneyU) is thevalue associatedwith a significancelevellessthanorequaltoa.(Weareusingthetraditionalvalueofa,0.05.)CriticalvaluesfortheMann-WhitneyUstatistic(atdifferentsamplesizes)areshowninTable4.

Inthepreviousimaginaryexample,treatmentandcontrolgroupswith8sampleseach,acriticalvalueof13isrequiredforrejectionofthenullhypothesis.TheMannWhitneyUstatisticof9isfarlowerthanthiscut-offvalue.Thismeansthereisverylittleoverlapbetweenthetwopopulations(theyaresignificantlydifferent).Thenullhypothesisisrejected.

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Table4. CriticalvaluesfortheMann-WhitneyUstatistic. Findthevaluethatcorrespondstothesamplesizes(8and8)ofyourtwocellpopulations.IfyourUvalueissmallerthanthatshowninthetable,thenthereislessthan5%chancethatthedifferencebetweenyourtwocellpopulationsis due to chance. If your U value is smaller than the one shown in this table, reject your nullhypothesis.IfyourUvalueislargerthanthatshowninthetable,failtorejectyournullhypothesis.

IV.GraphicRepresentationofyourDataTablesofnumericaldataareimportant,buttheyarenotalwaysthebestwaytopresentyourdatatoanaudience.Astheoldsayinggoes,“Apictureisworthathousandwords.”Themosteffectivewaytopresentyourexperimentalresults,wheneverpossible,iswithafigure.

A.MitosisRawData Asimplebargraphcanbeusedtorepresenttheproportionofcellsinyoursamplethatyoufoundineachstageofmitosis.AnexamplecanbeseeninFigure1.Inabargraph,categoriesmaybeplacedinanyorder,anddonotnecessarilyrepresentacontinuum.

Figure1.Abargraphshowingahypotheticaldistributionofcellsineachstageofmitosisinastudypopulationofcells.

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Don’tconfuseabargraphwithahistogram.Ahistogramdepictscontinuousdata.AnexampleofahistogramisshowninFigure2.

Figure2.Ahistogramshowingahypotheticaldistributionofcellsofdifferentdiameterinapopulationofcells.Notethateachbaronthehistogramrepresentsaspecificsubsetofarangeofcontinuousnumericaldatathatoccurinasetorder.

Figures,unliketables,havetheirlegendsplacedunderneath.Alwaysuseproperformatforfiguresandtablesinyourwork.B.VisualizingMann-WhitneyUresultsBecausetheMann-WhitneyUprovidesameasureofhowgreattheoverlapisbetweentwogroupsbeingcompared,abox plot isagoodway torepresentyourMann-WhitneyUresults. Theboxgraphcanbecreatedtoshowthemedianofeachgroup,therangeofvalues,andtheiroverlap.AnexampleofaboxplotisshowninFigure3,withakeyandexplanationinFigure4.

Figure3.Sampleboxplotshowingoverlapofmitoticindexvaluesfortwopopulationsofcells.

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Figure4. Theblackbarinthecenterofeachpopulation’svaluesrepresentsthemedian.TheInterquartileRange(IQR)includes50%ofthevalues,andisborderedonthebottomby the 25th percentile and on the top by the 75th percentile. The range is the regionbetweentheminimumandmaximumvalues. Thestarrepresentsadatapointthatisanoutlier.