PowerCore (v. 1.0): A program applying the advanced M strategy
Contents
1. display thes Ease pare ogee clic Office Choboard on the Edit menu or press CHH Erica 12 FJ PowerCore 1 0 BEES Number of Accessions 42 Number of Variables 5 Help E3 Input Step1 Step2 Accession NM1 NM2 M3 113 106 99 106 113 HNeEPNNWeENWHWNNWeEN PEN WEN N MONRFWNNKHNWRHRPNNKRPW EWEN EB NONRFPRHENWNHENWREREPWNNNRFPNNW NB Figure 1 b i Clear and Paste functions are used when the existing information is replaced with a new data set H all function is used for exporting the existing data set to a Clipboard for Excel spreadsheet Note PowerCore accepts various has no limit for data input size Data input is based the resources available in the user s computer and not according to the limit of the excel spreadsheet c Other input sources 1 Star Office Star Office windows version similar to that of Microsoft Excel StarOffice 5 2 Sample sdc File Edit View Insert Format Tools Data Window Help x CH file cl documents and settings abc H 5 v lt gt es fg Ew ki x e y m ib IE ES JM z E U A x m 9 96 t Sa o9 em C2 F Etl E 4 D2 Cell Styles x a eoe Bremen Se ee a ae x 2 m o ERES pum L sj Ea 5 B 8 9 10 CEE 13 15 1b 18 19 212. step iRM21 1 Not Available Number of Accessions 1000 Number of Variables 18 Number of Entries Iv Non heuristic Search 116 Max Possible Entries PowerCore Efficiency Index Unfilled Diversity Cells 0 Random Branching MD CR YD VR9 o Wes Diversity Index Option 3 v CoreSet EntireSet PIC C Count E Count Figure 20 Result display of analysis by PowerCore for SSR data 25 c Results of a and b Table 1 Number of accessions selected by PowerCore Experiments 1000 phenotype 1000 SSR Number of 45 87 accessions 1 core 4 5 8 7 collection ratio against entire Note Detailed results of 1000 phenotype and 1000 8558 data sets provided in Results for Phenotypic Dataset xls and Results for SSR Dataset xlIs 8 COMPARISON BETWEEN POWERCORE AND MSTRAT 8 1 Using virtual accessions Using 1000 virtual accessions a comparison was done between the PowerCore and MSTRAT The quantitative characters B001 B002 and B003 of the virtual accessions were designed into three types of distributions as shown in Figure 21 It was noted that BOOI was biased to left side and represented the extreme value B002 had a normal distribution and B003 had a double peak B001 B002 B003 700 600 500 400 N 300 200 100 Oo ou Gr sc
3. CO CO P2 r2 PO P2 n2 P2 P2 r2 n2 Lr n2 P2 NM CO CO 3 n9 P2 n9 n n2 n2 PY n3 za p FPN FPN F x BPH cH cn we CH ro fF L PN P n PB F SJ C HE PRP PRP PRP CH Figure 15 Screen capture of the attached phenotypic data using PowerCore iv Click the Step1 and Classifying tabs m PowerCore 1 0 Number of Classes pF User Total D s ES i Stepi R Step2 Figure 16 Screen capture once classifying is performed v Click Step and click Run tat PowerCore 1 0 B input 86 step1 m gt IUE Py al nin i Number of Accessions 1000 EI Number of Variables 39 ut m n Number of Entries II Iv Non heuristic Search 52 UB B Max Possible Entries 166 PowerCore 6 Efficiency Index Unfilled Diversity Cells 83 Random Branching MD CR VD o e Diversity Index Option iv CoreSet EntireSet EHE Ez L JL i Br as PIC C Count E Count Figure 17 Filling of the diversity panel E PowerCore 1 0 Randoms Number of Accessions 1000 Not Available Number of Variables 39 Number of Entries Iv Non heuristic Search 52 Max Possible Entries 166 PowerCore 45 Efficiency Index
4. 3 3 3 IB 3 4 1 17 3 2 5 8 3 2 2 19 3 2 2 20 2 21 3 2 722 3 2 23 3 2 3 2 18 3 2 2 49 5 2 50 3 2 28 51 2 3 2 Figure 9 Excel spreadsheet depicting the new file developed 11 data generated for the core set is saved a new excel sheet 15 generated by the PowerCore iv Filtering of the core set from the entire collection is done and the core set is automatically marked Y by the software Microsoft Excel TestCore Arial 10 B Z L M L K feJAuric CA F F yJBLSC gt F EOE D Core w No F gt O Ez O e F Sort Ascending 1 5 2 1 2 n 1 2 2 Sort Descending 5 5 5 5 3 2 E E 2 fi 5 5 f 2 5 5 F F F F F F L 10 Y 5 2 1 111 o 5 P 2 2 12 11 5 2 5 13 Y 12 5 2 14 Y i3 E 2 2 15 4 5 P 18 15 5 2
5. Vist ISt dio Developer Tools The NET Framework version 1 1 redistributable package includes everything you need to run applications developed using the NET Framework i Isua u IO Business Solutions i Games amp Xbox On This Page MSN Quick Details Overview Windows Mobile System Requirements Instructions All Downloads 4 Additional Information Related Resources Download Categories 4 What Others Are Downloading Related Downloads Games Directx Internet Windows Security amp i i qiiis Quick Details Windows Media File Name dotnetfx exe Drivers Version 1 Home amp Office Date Published 3 30 2004 Mobile Devices 4 Language English Mac amp Other Platforms System Tools Download Size 23 1 MB Development Resources Estimated Download Time Dial up 56K 57 min Download Resources f 8 i Change Microsoft Update Services Change Language English 2 v Mainmland Hala Internet b Click when prompted File Download Security Warning Do you want to run save this file Mame dotnetfx exe Application 23 1 MB From download microsork com Save Cancel While files from the Internet can be useful this file can potentially harm your computer IF you do not trust the source do nat run save this software What s the nek c Click Run when prompted Internet Explorer Security Warning Do you want to run this software
6. 2 Windows Malicious Software Removal Tool Download Resources 3 Windows Live Local for Outlook Beta z Microsoft Update Services 4 Microsoft Soccer Scoreboard z v Marnmnland Cantar Wala http www microsoft com downloads info aspx na 08p 18SrcDisplayLang en amp SrcCategoryld 85rcFamilyId au 0a 09 09 09 09 09 09 09 Internet a Download the NET Framework Version 1 1 from the Microsoft Website http www microsoft com downloads details aspx Family D 262d25e3 f589 4842 157 034d1le7cf3a3 amp DisplayLang en Download details NET Framework Version 1 1 Redistributable Package Microsoft Internet Explorer File Edit View Favorites Tools Help ay Back v ix a Search Sie Favorites e 2 Lj rel 2 Address uj http Iwww microsoft com downloads details aspx FamilyID 262d25e3 f589 4842 8157 034d1e7cfF3a3 amp displaylang en v Go Links gt Y7 Search Web 2 Far Gy E Mal gt My Yahoo EJ answers ql Games FIFA World Cup gt Music gt Web Personals 45 Sign In Quick Links Home Worldwide Mi Search Microsoft com for icroesoft Download Center Download Center Home Search Downloads Advanced Search 1 Product Families Windows i H i i nh Microsoft NET Framework Version 1 1 Redistributable Package Eur Brief Description
7. Mame deotnetFx exe Publisher Microsoft Corporation E mere options En while Files From the Internet can be useful this File type can potentially harm your computer Only run software From publishers you krust Ehe risk d A prompt for installation appears on the screen Click Yes Microsoft NET Framework 1 1 Setup 3 would you like to install Microsoft Framework 1 1 Package e Installation of Microsoft NET Framework is now complete once the following dialog box appears on the screen iz Microsoft NET Framework 1 1 Setup X Installation of Microsoft MET Framework 1 1 is complete f The PowerCore software 1s now ready to be executed g For installation of PowerCore Program open the PowerCore folder and click on the folder named SETUP a PowerCore File Edit View Favorites Tools Help 2 B gt 9 Address D WPowerCore1 0WPowerCore I PowerCore1 0 Setup File and Folder Tasks Windows Installer Package Microsoft R Visual Studio Win 6 552 KB Microsoft Corporation Make a new folder E amp Publish this folder to the Setup Web s Configuration Settings Share this Folder SR Other Places 2 1 0 L My Documents Shared Documents ij My Computer a My Network Places Details h The following dialog box will appear on the screen Follow the instructions provided by clicking Next i PowerCore1 0
8. Max Possible Entries 26 PowerCore 12 Efficiency Index 0 8 Unfilled Diversity Cels 0 Random Branching Random 8 8 stepi step2 NM1 Not Available Click to detail informations MD 2 78 CR 87 5 VD 31 32 VR 89 82 Diversity Index Option Iv Coreset Entireset PIC C Count E Count Figure 6 Output for the heuristic search 1 Click the diversity index tab to display the diversity index using Nei and Shannon amp Weaver calculation Figure 7 PIC Nei DI C Count Core Set by Heuristic Method E Count Entire collection E PowerCore 1 0 Number of Entries V Non heuristic Search 15 M2 m m im M M m CO D CO Number of amp ccessions 42 Number of Variables 5 Max Possible Entries 26 PowerCore 12 Efficiency Index 0 8 Unfilled Diversity Cells 0 Random Branching 0 MD 2 78 CR 87 5 YD 31 32 WR 89 82 es Diversity Index Option CoreSet EntireSet EIE Random 8 ah Step1 step2 0 704 4 PIC C Count E Count Figure 7 Diversity index using Nei and Shannon amp Weaver calculation 18 E PowerCore 1 0 BRE Random Run the Stepi A Step2 mh Number of Accessions 42 MM 0 704 i BOG Number of Variables 5 Number of Entries v Non heuristic Search 15 Max Possible Entries 26 PowerCore 12 Copy Unfilled Diversity Cels na n
9. Welcome to the PowerCorel 0 Setup Wizard The installer will quide through the steps required to install PowerCore 0 on your computer WARNING This computer program is protected by copyright law and international treaties Unauthorized duplication or distribution of this program or any portion of it may result in severe civil or criminal penalties and will be prosecuted to the masimum extent possible under the law Cancel 1 A prompt for the Installation Folder will appear Click browse to select the location of the required folder T2 PowerCore1 0 Select Installation Folder The installer will install PowerCore 0 to the following folder To install in this folder click To install to a different folder enter it below or click Browse Folder CwPragram Files PowerLore 1 Disk Cost Install PowerCore 0 for yourself for anyone who uses this computer 2 Everyone Just me prompted for confirming installation SEL j Follow the instructions by clicking Next when im PowerCore1 0 Contirm Installation The installer i ready to install 1 0 on your computer Click Nest ta start the installation k The installation process has begun 5 PowerCore1 0 Installing PowerCore1 0 1 01 being installed Please wall Cancel 1 Installation is now complete Close the prompt box im PowerCore1 0 Installat
10. Yo K o G HOH j D DP O 1 XO e gt OQ O O G wn mn s Figure 21 Three types of distributions for the quantitative characters in virtual accessions a PowerCore All default options were used in PowerCore PowerCore resulted in 18 accessions being selected for the core set b MSTRAT A minimal optimum size of 34 entries for the core set was selected by MSTRAT MSTRAT is strongly guided by its Redundance function To obtain the core sets using MSTRAT two experiments were conducted In the first experiment the core value was set at 18 value of which is similar to that provided by PowerCore For the second experiment the core value was set at 34 result of which was obtained using MSTRAT s 26 Redundance function For both experiments the values set for the Redundance function was as follows 50 repetitions 100 iterations and the other options were set as default c Results of PowerCore and MSTRAT Results obtained are as shown in Table 2 Important note PowerCore retains all classes 1n the Core Collection Table 2 Results of the comparison between PowerCore and MSTRAT Variables Class Entire Count Core Count PowerCore MSTRAT 18 MSTRAT 34 A001 1 781 10 amp 21 2 176 3 6 3 35 2 2 3 4 7 2 1 1 5 1 1 1 1 A002 1 1 1 1 2 2 1 1 2 3 995 15 15 30 A003 1
11. 0 86 Unfilled Diversity Cells O Random Branching 0 MD 6 98 CR 96 85 VD 71 VR 200 51 IE Diversity Index Option CoreSet EntireSet PIC C Count E Count Figure 18 Screen capture indicating the completion of the selection process for entries into the core set using PowerCore b Application of PowerCore on genotypic data The PowerCore is next tested using a set consisting 1000 SSR data for rice whereby the file SSR_Dataset_for_PowerCore xls is used and the Data tab is clicked open E3 Microsoft Excel Rice 1000 SSR for PowerCore xls File Edit Insert Format Tools Data Window Help Type a question For help X 3 1 4 Z C 21 1 4D 100 3 50 i lRM21 1 iRM44 1 iRM48 1 iRM206 1 iRM214 1 iRM228 1 iRM231 1 iRM232 1 ik 2 Bred 0002 99 109 188 155 3 Bred 0004 99 109 190 143 4 Bred 0005 117 109 190 149 5 Bred 0006 115 109 182 153 6 Bred 0007 107 109 182 7 Bred_ooog 127 109 188 8 Bred 0010 127 109 188 9 Bred 0011 127 109 188 10 Bred 0012 117 107 188 11 Bred 0013 117 109 188 12 Bred 0015 117 109 188 13 Bred 0017 117 109 188 14 Bred 0020 117 109 188 15 Bred 0023 117 109 188 16 Bred 0027 109 188 17 Bred 0028 117 107 188 18 Bred 0030 127 109 188 19 Bred 0031 103 109 188 20 Bred 0033 117 109 188 21 Bred 0035 139 117 _225 163 109 188 h Ready NUM Random amp
12. Screen capture of worksheet indicating the phenotypic data for 1000 rice accessions 21 11 All data is selected and copied to the clipboard Microsoft Excel Rice 1 000_Phenotype_for_PowerCore xls File Edit Insert Format Tools Data Window Help ae Z 3 x J 72 0 8 gt 2 Ba lt p 500 E Fi Paste Special Insert Delete Clear Contents Insert Comment Format Cells Pick From Drop down List Create Lis E Cn CH Oe OB Hyperlink Look Up 1002 q 4 k h x Data Descriptions Ready Sum z 199383 1 1 1 i 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 F Me fh he M p3 PO PO n3 p n n3 E nm nr n Oh 6 6 6 DI D D D Ch Ch Oa CD HS J Ch rn dcn Mu Bow OX Dp JT C Bt OB D O r Figure 13 Data is copied to clipboard by right clicking the mouse and selecting the Copy option iii The PowerCore is first launched using the Start menu before data is pasted using th
13. Variables mmm SS iRM21 1 455 54 5 100 0 100 0 iRM44 1 421 579 100 0 iRM48 1 4350 750 80 0 100 0 iRM206 1 450 400 82 5 100 0 iRM214 1 36 8 579 84 2 100 0 30 iRM228 50 0 42 9 92 0 100 0 iRM231 1 66 7 55 6 100 0 100 0 iRM232 50 0 64 3 100 0 100 0 iRM235 1 47 4 31 6 78 9 100 0 18 241 1 45 5 50 0 81 8 100 0 iRM246 1 77 8 66 7 100 0 100 0 iRM247 1 45 8 45 8 95 8 100 0 iRM249 25 0 50 0 85 0 100 0 iRM253 1 46 2 69 2 100 0 100 0 iRM257 1 48 1 44 4 92 6 100 0 iSBE 1 36 4 54 5 12 100 0 1555 1 44 4 66 7 88 9 100 0 iGBSS_1 54 5 63 6 90 9 100 0 Coverage 46 8 55 0 88 9 100 0 9 ISSUES TO BE CONSIDERED INCLUDING SNP DATA a Preferential Selection PowerCore has the ability to allow preferential selection to be performed by the user Preferential selection can be performed when the user decides on including pre existing entries from a present core into the new core to be developed by PowerCore without being validated Some reasons for preferential selection may include that these accessions possess traits of interest to the user or that these accessions are considered as standard reference materials which are needed to be included As explained earlier in section 3 the symbol is placed where necessary PowerCore firstly automatically selects accessions marked to fill the diversity cells before selecting the rest of the accessions using its heuristic estimation To demonstrate this function we are providi
14. 22 23 24 25 eb eH 23 30 manmi CE 33 34 35 Sheet 1 3 Default 100 STD Hy Start E Sample sdc 98 02 9x Figurelc 13 Simple text PowerCore accepts tab separated text format Sample txt Notepad EIB File Edit Format View Help PaAccession I I I 2 2 I z 3 3 I z 2 3 z 4 4 3 z 2 I z 1 2 2 3 z 3 2 I I 2 I I 3 3 3 I z z 3 I I 2 2 2 I z 3 3 3 z 2 I I 2 z I I 9 7 2 a 7 7 2 g 1 F 4 9 7 I 2 7 g Figure 1 d 5 RUNNING POWERCORE a The crucial step would be converting the quantitative data into classes and to validate the reliability of the data set e g deleting missing blank data This is important as in general a continuous data set has no variables and is expressed in real numbers or in integer format Place the mouse pointer on the top right corner of the window and click Step of Accessiots 42 Number Variables 5 Number of asses 0 Gas Secession NM MI M zu Preguency Destrbution Mauwmum Coum of Eny 41 1 i i Figure 2 Display of output results for converting data into classes 14 Click Classifying to create classes of each variable determined by the criterion of Sturge s rule This will allow each accession to be allocated to these created classes Figure 3 displays the output in the form of a h
15. 56 3 3 4 2 768 8 7 19 3 171 5 5 4 2 1 1 5 2 1 1 1 4 1 995 15 15 30 2 1 1 1 1 3 1 1 1 1 4 3 1 1 2 3 00 11 73 722 amp 12 24 11 73 20 45 248 7 5 amp 20 45 29 18 26 1 1 29 18 37 91 1 1 37 91 46 64 46 64 55 36 55 36 64 09 64 09 72 82 72 82 81 55 81 55 90 27 90 27 99 00 1 1 B002 10 00 15 73 3 1 1 1 15 73 21 45 17 2 21 45 27 18 64 1 2 4 2 27 18 32 91 121 3 1 5 32 91 38 64 251 3 5 7 38 64 44 36 281 2 4 7 44 36 50 09 194 2 3 7 50 09 55 82 49 1 1 2 55 82 61 55 15 1 61 55 67 27 2 1 1 1 67 27 73 00 1 1 59 00 67 82 10 EL 67 82 76 64 29 1 1 1 76 64 85 45 35 2 2 3 85 45 94 27 12 1 94 27 103 09 255 3 7 103 09 111 91 171 1 1 111 91 120 73 163 3 3 10 120 73 129 55 237 2 2 129 55 138 36 84 2 1 138 36 147 18 3 1 1 147 18 156 00 1 1 Note Detailed results in Results_ for Virtual 1000 xls file 9 2 Using the real rice phenotype data set of 1 000 accessions 39 phenotype variables consisting of 28 qualitative and 11 quantitative characters To compare the selecting efficiency of PowerCore with the conventional core collection methods using 39 phenotype traits 10 core subsets 100 accessions for each core set were developed using the strategy of the Random core collection R Core and the Proportional core collection P Core in the following steps The quantitative characters of the entire collection were standardi
16. ANDANA vx Al rae 57 RTS12 ux Al i s 2 156 KALUKANTHA Al i 2157 VARY VATO 8 Al BLACKGORA Al Niva26wx M 228155 Niva28wx S 2156 RufiliZwx M i 2156 JAGLIBORO Al 2156 AUS JOTA w RAYADA wx Py z 2156 Rufi 19wx i 2 156 Niva22wx M A i 2142 Rufil ux S B Al 2140 IR64 wx 2141 POR 157 Bar67wx M1 Al 2 2156 Gla 42wx M B Al Ac 2158 Gla45wx M1 AL s GlaSOwx M1 Al sa IST Glu ir20wx B A h 2158 NivazOwx M B 1 Al h CHODONGJI i Ai KHAODAWKMA 1 2156 IR60080 46 B hj AL i 2157 Rufii3wx S Al s 2155 NIPPON Al 2158 PATBEYO ux B AA 215 KHAOKAPXAN 2161 MILYANG23 AA Ab 052158 BASMAIT vx B m Py pao AZUCENA ux B i Heese ow CAROLINA G 166 Al S 2250 GERDEH wx GAAGGC Al E 2158 IGUAPE CAT AA Al 2158 LEMONT vx 2158 MOROBEREKA AA Al i r 1538 PACHOLINHA Al Ha Figure 26 Screenshot after aligning the sequences of particular genes to find and score SNP or Indel variations Till date we do not have SNP data of large collections We used the virtual data set to demonstrate the application of PowerCore u
17. INSTALLATION Microsoft Download Center Microsoft Internet Explorer File Edit View Favorites Tools Help ar Back 2 ix a 2 Search Sip Favorites B LJ rel 3 Address amp http www microsoft com downloads search aspx displaylang en v Go Links gt Adobe yr Search Web 4 CS Mail my Yahoo EJ answers z ql Games 5 FIFA World Cup Music Web Personals X sign In Quick Links Home Worldwide Search Microsoft com for Microsoft Download Center Download Center Home Search All Downloads v Advanced Search Product Families Windows Office Windows Media Player 11 Servers Download the beta today Developer Tools Business Solutions Games amp Xbox MSN Windows Mobile All Downloads rer 7 beta 2 today gt Office Download Categories Games Popular Downloads DirectX Internet 1 Windows Defender Beta 2 3 Windows Security amp 2 Internet Explorer 7 Beta 2 Windows XP SP2 z Mas 3 Directx End User Runtime Windows Media 4 Framework Version 1 1 Redistributable Package Drivers 5 Framework Version 2 0 Redistributable Package x86 Home More Popular Downloads Mobile Devices Mac amp Other Platforms New Downloads System Tools Development Resources 1 Directx End User Runtime y
18. PowerCore v 1 0 A program applying the advanced M strategy using heuristic search for establishing core or allele mining sets User Manual Genetic Resources Division National Institute of Agricultural Biotechnology NIAB Rural Development Administration RDA R Korea Web site http genebank rda go kr powercore TABLE OF CONTENTS 1 OVERVIEW A 3 2 s 5 3 DATA PREPARATION 10 DATA IMPORI i u u unu uu 12 5 RUNNING POWERCORE 14 6 DATA MANAGEMENT 20 Ta RICE SAMPLE DATA u senos Ap 21 8 COMPARISON BETWEEN POWERCORE AND MSTRAT 26 9 ISSUES TO BE CONSIDERED INCLUDING SNP DATA 31 10 COMPLEMENTARY USES OF POWERCORE 39 1 OVERVIEW Many genebanks globally contain untapped resources of distinct alleles which will remain hidden unless efforts are initiated to screen these alleles of its potential use and function The deployment of useful diversity using core collections has been an area of much interests for researches especially those working in the field of allele mining The prerequisite of any core collection established is that it captures the complete diversity of the entire collection it was
19. a na Lm wo Random Branching 2 78 CRY YD 3132 VR 0962 a Class Core Count Entire Count Diversity Index g bos 13 00 17 00 12 Option I v Coreset Entireset B0 e 21 00 3 i 21 00 25 00 4 PIC 25 00 28 00 4 C Cpunt 29 00 33 00 6 33 00 37 00 13 E Count Figure 8 Core Collection data saved Note We have designed to report the probability value of 7 test for qualitative characters and the probability value of Z test for quantitative characters to compare the distribution of data of entire and core sets 19 6 DATA MANAGEMENT Microsoft Excel TestCore dc File Edit View Insert Format Tools Data Window Help Jj n il j X D gt 10 Al fe Core Subtotals Show 4 TESCO Core No VG BP Tm CA IC Validation Advanced Filter A 5 5 K Text to Columns 1 1 5 5 F F F F F E g 13 PivotTable and PivotChart Report B Y 5 Import External Data e 3 List 2 7 5 m P 9 Y 3 3 2 Y Refresh Data Y o 2 3 2 2 1 2 Y 12 3 2 1 Y 3 2 2 14 3 2 15
20. derived from A core set should not be considered a substitute of the entire collection The recent advancements in technological tools related to genomics and bioinformatics have made it possible to discover new alleles for any gene of interest These new techniques also create a further challenge of linking traditional phenotypic information to a larger quantity of sequential and genetic information and to complement activities carried out for germplasm enhancement Allele mining provides the avenue for the validation of specific gene s responsible for a particular trait and mining of the most favorable alleles The advent of PowerCore that implements the advance M strategy using a modified heuristic algorithm is hoped to provide users the added ability to develop core or allele mining sets representing all alleles or classes of their observations whilst ensuring the least allelic redundancy and highly reproducible list of entries PowerCore software uses the NET Framework Version 1 1 environment and is freely available for the MS Windows platforms on personal computer worldwide PowerCore 1s developed by C C is an object oriented language which has accepted many good features of Java and C PowerCore runs on NET Common Language Runtime CLR and can run on any platform installed with CLR CLR is similar to Java Virtual Machine of Sun Microsystems Nowadays there are many attempts to port CLR to Macintosh and Linux 2
21. e Clear and Paste function by right clicking the mouse E PowerCore 1 0 Seles Number of Accessions Number of Variables input sh Q step2 Append kem and Paste All Please right click on the screen Figure 14 Phenotype data is pasted unto the clipboard by right clicking the mouse and selecting the desired function 22 m PowerCore 1 0 DE Number of Accessions 1000 Number of Variables Q Hep 5 Input si Step R Step2 o VG n BLSC 1 n 8 5 4 2 P S i X PNP RP CO CO CO CO 1 OD CO 1 00 CO 0 102 CO CO 1 CO CO CAP H pn PR PO PRO B CO PO PO PO n n pP C CH E o EG GR PRP PRP LER HIR m x NN pj pj pn MM wR Bw m RP RP SY X YP LB GG H H HG oH RP BF RP RPRP RP RP NP IND o LB PT OQ YP E x oH EH PN FP P B ee hh rmn nr CO CO n9 CO
22. e 6 Modified data for preferential selection Accession 2 2 M3 A01 1 1 1 37 113 A 02 2 1 2 31 106 A03 1 2 3 34 99 A04 3 1 7 28 113 A05 7 3 2 34 106 A06 1 4 1 31 113 A07 4 3 2 37 106 A08 2 1 2 31 106 A09 1 7 2 34 92 A10 3 2 3 34 99 All 2 1 1 2 99 12 2 1 1 37 106 A13 3 3 3 34 99 14 1 2 2 31 92 15 3 1 1 34 85 A16 2 2 2 119 17 1 2 3 55 99 18 9 3 2 31 113 As shown in Figure 23 the accessions marked with are automatically selected into the core set developed though the number of entries in the new core set has increased 33 m PowerCore 1 0 m Random E input step w TnA A s Number af Accessions 18 0 881 a Number of variables 5 gt Number af Entries 1 iM Non heuristic Search 9 Max Possible Entries 15 Powerlore B Efficiency Index 0 75 Un lled Diversity Cels q fh i Random Branching 0 2 34 100 22 95 109 41 Mes Diversity Index Option W CoreSet iw EntireSet PIC Count E Coaunt Figure 23 Results of PowerCore using the same data for preferential selection b Dealing with null values using PowerCore One of the important features of the PowerCore is that it takes into account the uniqueness in the value of an accession for each character during the filling of the diversity cells The heuristic functions of the PowerCore have been designed to ensu
23. ets for their specific purposes Sometimes these are required for the improvement of an existing core set For both cases PowerCore can be used in combination with conventional clustering tools This process can be easily undertaken using PowerCore while maximum diversity is maintained in the core sets generated To include entries from a pre existing core set a is placed before their accession names before other entries are selected to cover all alleles diversity existing in the entire collection 10 2 Retaining related accessions for specific purposes e g for association analysis Some users require retaining related accessions with particular variations to search for relationships between traits and genes To cater this the user can firstly select these entries using the conventional tools like clustering analysis is then placed before the accession name before running PowerCore to fill in the diversity cells with the pre selected accessions first PowerCore provides the user with the least number of entries while retaining the related accessions and other distant accessions simultaneously 10 3 Other applications of PowerCore in genetic resources and breeding programs In addition to developing cores sets PowerCore is also very useful in selecting diverse sets for improvement of breeding programs in a minimal time Some researchers handle large quantity of breeding materials in certain cases several thousand lines e
24. g Near Inbred Lines NILs Developing a short listing of these lines for intensive investigation such as DNA sequencing or SNP genotyping of specific genes may be cumbersome using conventional methods PowerCore provides a quick solution to this Another point to note is the ability of PowerCore to develop extremely distant sets from an existing reference set As explained in earlier examples the is placed before the names of accessions from the reference set before running the PowerCore which effectively differentiates the reference set from the final list 39
25. he data set 1s complete it 1s now ready to be used for the PowerCore program The Excel spreadsheet can be copied directly into the interface of the program 10 b To run the installed program go to the START toolbar and search for the PowerCore program and click Open M e 5 P s 5 Es C 11 4 DATA IMPORT a Once the program is executed the following window appears on the screen Using the mouse pointer right click on the screen Que trout Mumber of accessions humbur of Varables on the i reen Pieka on the i reen k Append Chow and Parte Copy AJ b An additional prompt will appear Append function is used when new information is added to an existing file This program has the capability to allow the input of an unlimited set of accessions or number of variables used though the excel spreadsheet only allows limited data input The program automatically finds appends the new data according to the accession ID column and variable names row along with the additional information without disrupting the existing information flow as shown below in Figures 1 and 1b mmmm of Acceso of Variables Ee l L Qh Ra L B Qh ka MR de es PO RU a wu Cea and Paste Copy gt B ode PO D am I PJ DE jh
26. i 17 l6 5 2 i 18 7 5 2 5 I 19 i8 5 2 1 1 2 n 2 e t E E tt ft Figure 10 Filtering step for the core set v The results can then be saved in a separate worksheet in the excel spreadsheet 20 Microsoft Excel TestCore File Edit Insert Format Tools Data Window Help GOR CN KNOW GN X SN GR NN NSN SIN CN CN ON CN CN ON SI LOI CON NO CON CON CN OR 03 X NY GUY CU CU OR OP OR OR OR CY GUY OR OP OR OR OR OP OR o BN C GS RO RO RO CU RO RS RS CU AY RO RO RO RO RO 23 CU SO RO COS RO RO SO e cm rg I IW LN CN LUN CN CUN CN CUN CN CN CN CN CN CN CN CN CN ON CNW ON CN ON CN ON ON GN RON RN LAN RON RON AN N AR N SS ANIM UN LN UN UN UN ON CN ON UN ON UN N KR LO GO SNR NO ON EN RN ON GIRO ON ON SNR GN ON RO ON NON UN ONG ON LX RO ROS ROS RO RO CJ RS RU A RO RO RO RO N N A3 UR RS AX RO AX RS AX RANG NP LN NUNN ELM IIA IS Figure 11 Complete accession level detail of core set generated via PowerCore 7 RICE SAMPLE DATA a Application of PowerCore on phenotypic data For actual implementation of the software a real data set using 1000 phenotypic data for rice was tested i The file titled Phenotypic_Dataset_for_PowerCore xls is opened and the Data tab i
27. ion Complete PowerCorel 0 has been successfully installed Click Close to eit Please use Windows Update to check for any critical updates to the NET Framework 3 DATA PREPARATION a Before the PowerCore is executed the data set has to be inputted into an Excel spreadsheet Data format 1 iil V The first row In general contains the information of variable character names e g o Accession NMI NM2 Note A percentage character is placed before the title of the Identification column of accessions to represent each of the accessions in the collection The symbol when placed before the identity of an accession indicates a preferential selection wherein the user decides to retain these accessions in the core set without being validated using the PowerCore The symbol when placed before the identity of a variable represents a continuous quantitative data type e g height The PowerCore program allows any type of character for data input color can be represented as YELLOW or a or a numeric data 1 Note PowerCore supports blank data but does not incorporate these into the final calculation Accession NM2 2 M3 A01 1 l l 206 113 A02 2 l 2 106 A03 1 2 3 34 99 A04 5 1 2 26 113 A05 2 3 2 34 106 A06 1 4 1 Sil 113 A07 4 3 2 37 106 A08 2 1 D 31 106 A09 1 2 2 34 92 10 2 2 5 34 99 All 2 1 1 37 23 A12 2 1 1 106 A13 3 S 3 34 99 Once t
28. istogram 1 0 1 Number of Classes 6 uI fying W input 25 step1 step2 Frequency Distribution Figure 3 Output in the form of a histogram C d Scrolling the scrollbar at the right side of the window allows the user to view the histogram generated for each variable Histograms for quantitative variables are shaded dark blue Histograms for continuous variables are shaded orange The number of classes for continuous variables can be adjusted by checking the User checkbox at the top of window and inputting the desired value Total indicates the total number of user modified variables By clicking the Classifying tab the changed values are applied Place the mouse pointer on the top right corner of the window to proceed to Step 2 The following screen as shown in Figure 4 1s displayed Sturge s rule 1 Log n the observed number of accessions 15 I PowerCore 1 0 Figure 4 Display screen for proceeding to Step 2 Random UI Number of Accessions Number of Variables Number of Entries IW Non heuristic Search Max Possible Entries PowerCore Efficiency Index Unfilled Diversity Cells Random Branching MD CR VD VR Diversity Index Option CoreSet EntireSet PIC C Count E Count EEK Bl input 25 79 step2 A g Click Run to perform the heuristic search By checking the Random butt
29. more effective search Unfilled Diversity Cells Status during the filling of the diversity index Random Branching Selection of nodes randomly during the selection process of same accessions with same values of minimum evaluation functions indicating the number of its occurrence Me Me MD Mean difference percentage MD x100 m Me Mean of entire collection Mc Mean of core sid CR Coincidence Rate CR yum 100 1 Re Range of entire collection Re Range of core collection Ve Vc Vc 1 VD Variance Difference Percentage VD x 100 m 53 Ve Variance of entire collection Vc Variance of core collection 1 m VR Variable Rate VR 100 m 1 CVe CVe coefficient of variation of entire collection CVe coefficient of variation of core collection m number of traits The left most panel on the screen are the selected entries accessions ID as per data set using the heuristic search By right clicking the Entry tab the list could be copied to a clipboard Figure 6 displays the output for the heuristic search completed The panel displayed shows each variable in the form of a histogram By right clicking the histogram a separate table indicating the number of accession for each class core count and the entire count 1s displayed 17 E PowerCore 1 0 Number of amp ccessions 42 Number of Variables 5 Number of Entries Iv Non heuristic Search 15
30. ndary branching PE Panicle exsertion AP Awn presence ApiC Apiculus color SC Stigma color LPC Lemman and Palea color SLC Sterile Lemma color SLL Sterile Lemma length SCC Seed coat color ET Endosperm type LB Leaf blast BLB Bacterial leaf blast Xanthomonas oryzae RSB Striped Rice Borer LS Leaf senescence S Shattering 11 quantitative characters SH Seedling height BL Blade length BW Blade width LL Ligule length NDSH Number of days from seedling date to 50 heading CL Culm length CN Culm number PL Panicle length GL Grain length GW Grain width 1000W 1000 grain weight 8 3 Using the real rice genomic SSR data set of 1 000 accessions 18 loci To compare the selecting efficiency of PowerCore with the conventional core collection methods the genomic data of 12 loci of SSRs were used We have selected 100 accessions 10 of entire collection for the core sets of R core and P core and 87 accessions for MSTRAT since PowerCore retained 100 coverage with 87 selected entries As shown in the phenotype data PowerCore always retains 100 96 of coverage rates in all the loci tested PowerCore was designed to fill all diversity cells all alleles of SSR loci so it selects entries until a core set satisfy 100 96 of coverage in all the cases Table 4 Comparison of selecting efficiency for PowerCore with the conventional core collection methods using the real rice SSR data set of 1 000 accessions Coverage Rate 46
31. ng the results using the same data with the function of preferential selection Table 5 Results of the comparison between PowerCore and MSTRAT without preferential selection Accession 1 NM2 M3 A01 1 1 1 113 02 2 1 31 106 A03 1 2 3 34 99 A04 3 1 2 28 113 05 2 3 2 34 106 31 A06 1 4 1 3l 113 A07 4 3 2 37 106 A08 2 1 2 31 106 A09 1 2 2 34 92 10 3 2 3 34 99 All 2 1 1 E 99 12 2 1 1 37 106 A13 3 3 3 34 99 14 1 2 2 9H Se A15 3 1 1 34 85 A16 2 2 2 9H 11S A17 1 2 5 34 99 18 3 3 2 su 1 15 This data is used without any alteration to it Results obtained using PowerCore indicate that 7 entries were selected Figure 22 m PowerCore 1 0 5 EE lt Random RUA T Random EUM Bion steer tay 88 Number of Accessions S Nl RER 713 Number of Variables Mumber af Entries IV Mon hauristic Search Max Possible Entries Powerlore Efficiency Index 0 97 Unfilled Diversity Cells mq Random Branching MESo 5 08 CR 100 31 73 WRG 128 18 v Diversity Index Option we CoreSet we Entireset PIC C Cotnt E loaunt Figure 22 Results of PowerCore using data without preferential selection The next step would be the modification of the same data by placing to names of certain accessions marked in red to indicate preferential selection This modified data is then re validated using PowerCore 32 Tabl
32. on the search is performed using the random method Accessions are selected randomly instead of being selected by the heuristic evaluation function h The following figure Figure 5 shows the steps whereby the heuristic algorithm searches for the best possible accessions to be selected for the core set Dok E PowerCore 1 0 Number of Accessions 42 Number of Variables 5 Number of Entries Iv Non heuristic Search 15 Max Possible Entries 26 PowerCore 2 Efficiency Index Unfilled Diversity Cels 21 Random Branching MD CR YD YRO be Diversity Index Option CoreSet EntireSet PIC C Count E Count 35 o BERN Figure 5 Heuristic search e Number of Accessions Total number of accessions from the existing collection 16 Number of Variables Represents the number of characters from the data set Non heuristic Search A search which does not use any heuristic algorithm Note Similar to random search but results are always repetitive as search is performed sequentially Max Possible Entries It is the worst case scenario wherein this is the limit for PowerCore to select the maximum number of entries PowerCore Number of the selected accessions using the heuristic search Efficiency Index Effectiveness of PowerCore in comparison to the non heuristic search PowerCore PowerCore when Sequential Entries is Max Possible Entries M Sequencial Entries checked Note A lower value signifies a
33. owerlore Efficiency Index 0 66 Unfilled Diversity Cells Random Branching 0 MESo CRUS VOM VR Yo Cass X Core Count Entire Count 2 Option Emi CoreSet EntireSet i es Diversity Index 1 12 PIC Count E Coaunt Figure 28 Results of PowerCore using sample SNP data PowerCore can accept each SNP genotype as a qualitative character while also accepting the combination of letters representing DNA sequences Heterozygous genotype can be recorded with a separator like However we are recommending the users to record these heterozygote genotype to one form of C A or A C in the case where we have A C or C A sequence variation on the specific SNP locus If you use both PowerCore recognize both to be different alleles As for recording Indel alleles we are recommending to use If we leave deletion alleles as blank PowerCore will ignore those So please use 38 10 COMPLEMENTARY USES OF POWERCORE 10 1 Complementary use for selecting entries from the sub groups when clustering is performed using the conventional methods A major challenge for a user in the selection of entries from a cluster developed using the conventional methods would be choosing those that capture the entire diversity of the cluster itself and possessing unique alleles for the core set Certain users may also want to maintain the genetic clusters of their entire collection and develop core s
34. re no handicaps are caused by a null value of a character Missing values are often common in raw data sets However these values whether missing or null are also considered as suitable candidates for the core set when validated with PowerCore c The influence of the number of classes and characters to the number of entries in the core set developed i Number of classes PowerCore creates the number of classes for any quantitative character as a default value based on Sturge s rule mentioned earlier in section 5 The number of classes for any quantitative character can be adjusted in PowerCore Increasing the number of classes in a quantitative character gives more weight to the particular character The increase in the number of classes leads to more accessions being selected to fill in the range 34 Figure 24 An example illustrating the adjustment in the number of classes ii The number of characters It is important to note that the PowerCore selects entries for the core set based on only given characters Diversity 1s covered within these given characters Thus more characters create more diversity cells which must be filled Increase in the number of characters leads to an increase in the number of entries to be selected for the core set A modified data set of the original 1000 virtual accessions was created by reducing the number of characters A001 A002 B001 B002 and this was used to run with PowerCore As a result the n
35. s clicked Microsoft Excel Rice 1000 Phenotype for PowerCore xls SEE E Pe Edit View Insert Format Tools Data Window Help a question for help f X 9 308 SE RE FE s So Val CoNo WG BP BC BLSC LA FLA LC CC AuriC IC CS PT SB PE AP ApiC SC LPC SLC 5 il L 3 2 1 2 4 1 1 2 322 1 5 a Ee 1 1 EE 1 2 4 1 1 1 alk 2 2 1I 3 3 1 al 1 1 1 2 1 1 1 1 1 2 2 2 1 2 1 1 1 4 1 3 3 1 2 4 1 1 111 791 cd 1 1 1 55 4 1 1 2 1 2 2 2 4 Fd 5 I 1 5 apes e l d 2 2 d 5 1 1 1 1 3 1 2 1 2p 2p 3 TEA 1 1 8 1 3 4 2 2 3 3 3 2 3 4 3 2 2 2 5 7 5 7 4 1 3 2 1 ee eS 1 1 2 3 2 L 1 1 1 1 2 5 S 1 1 3 1 2 1 jJ 5 5 5 2 11 1 1 1 3 2 TET 1 d 1 1 1 1 2 2 2 1 2 2 1 3 1 1 3 2 Ji 1 Tied 1 2 11 2 2 1 4 2 1 3 1 1183182 TIS 2 1 1 Te wl er 1 1 1 1 1 2 1 1 1 51 2 1 1 1 1 J BE a eee l 4 1 1 d d 2 1 1 T T 1 1 3 2 3 1 1 i 1 1 1 2 1 1 1 1 a 8861 111 i 2 1 2 5 Y 2 1 1 1 LS NES 1 1 1 1 2 3 1 1 2 1 1 1 21 ll zl 1 1 1 1 4 h h Data Descriptions lt Ready Figure 12
36. sing SNP data As mentioned above 36 PowerCore accepts any form of qualitative data and we used the data sheet shown Figure 27 So each sequence variations is treated as SNP or Indel loci and subjected to PowerCore for implementing selection of a core set until filling all diversity cells using the given data Improvements will be made for PowerCore to be more compatible with genomic data to meet future needs Microsoft Excel SNP sample data PowerCore xls File Edit wiew Insert Format Tools Data Window Type a question For help 174 W SNP GBSs l SNP GB53 2 SNP GBES5 3 SNP GBs5 4 SNP GESS 5 SNP GBs5 6 SNP GB33 AAT UG AAT UG AAT UG AAT Ct AAT CUT AAT UG UG AAT UG AAT CU AAT UG UG UG Ct CU UG UG UG CU UG UG ddudududud ud uuuuuuuduududd cy Ch ch ch Ch Cy Ch Ch Ci i 2 2 amp 2 n C M 4 hk MH Sheetl Sheet2 Sheet3 Ready Figure 27 Screenshot indicating how to record SNP or Indel data using an Excel worksheet 27 PowerCore 1 0 5 Random Run E trout B Step1 Stepz SNP GB55 1 Mot Available 4 Number of Accessions 34 Number of variables 7 Number of Entries Iv Mon heuristic Search 6 Max Possible Entries 9 P
37. tional core collection methods using the real rice phenotype data set of 1 000 accessions I Coverage MUI P MSTRAT PowerCore VG 80 0 600 80 0 100 0 BP zae 100 0 100 0 BC 80 0 80 0 100 0 100 0 BLSC 50 0 500 100 0 100 0 LA 100 0 1000 100 0 100 0 FLA 100 0 1000 100 0 100 0 LC EE ECCE 100 0 100 0 CC aem I ism 66 7 100 0 AuriC 100 0 1000 100 0 100 0 CA 100 0 1000 100 0 100 0 IC 667 100 0 100 0 100 0 CS 100 0 1000 100 0 100 0 PT 100 0 1000 100 0 100 0 SB 50 0 500 100 0 100 0 PE 60 0 1000 100 0 100 0 AP 100 0 800 100 0 100 0 ApiC 100 0 1000 100 0 100 0 SC 100 0 1000 100 0 100 0 LPC 60 0 60 0 100 0 100 0 SLC 100 0 1000 100 0 100 0 SLL ad 100 0 100 0 SCC 40 0 600 100 0 100 0 ET 100 0 1000 100 0 100 0 LB 100 0 1000 100 0 100 0 BLB 60 0 400 80 0 100 0 RSB 100 0 1000 100 0 100 0 LS wer 93 100 0 100 0 S 60 0 80 0 100 0 100 0 SH SEE 90 9 100 0 20 BL 81 8 63 6 90 9 100 0 BW 88 9 66 7 77 8 100 0 LL 60 0 60 0 90 0 100 0 NDSH 63 6 81 8 100 0 100 0 CL 81 8 2 100 0 100 0 60 0 60 0 80 0 100 0 PL 63 6 p 100 0 100 0 GL 75 0 75 0 75 0 100 0 GW 66 7 33 3 66 7 100 0 W1000 63 6 54 5 100 0 100 0 Coverage 75 9 75 4 94 8 100 0 NOTE 28 qualitative characters VG Variety group BP Blade pubescence BC Blade color BLSC Basal leaf sheath color LA Leaf angle FLA Flag leaf angle LC Ligule color CC Collar color AuriC Auricle color CA Culm angle IC Internode color CS Culm strength PT Panicle type SB Seco
38. umber of entries for the core set decreased to only 14 Figure 25 as compared to 18 from the original results gained in section 8 m PowerCore 1 0 Seles Random E put ie Step1 Q step2 Mumber of Accessions 1000 A001 Not Available Number of variables 4 Number af Entries Iv Non heuristic Search 14 Max Possible Entries 20 Powerlore 14 Efficiency Index 1 Unfilled Diversity Cells D Random Branching MOY 24 73 CRY 97 1 85 98 WRG 248 94 Diversity Index Option W CoreSet w Entireset PIC E loaunt Figure 25 Results attained when characters A001 A002 BOO and B002 of the 1000 virtual accessions are reduced 35 c How to prepare the data sheet for SNP data With the understanding that large scaled SNP data are rarely available in seed banks so far PowerCore was designed for better application of fragment polymorphic data like SSRs However PowerCore does accommodate SNP data through the recording of SNP and Indel variations among accessions applied Once the SNP or Indel genotype data of analyzed accessions is recorded to an Excel worksheet or a text file PowerCore accepts those as qualitative data The rest of the processes are same with that of qualitative data ASWINA wx 228159 IR3 6 wx Al i PETA wx 2156 TEOING wx B Ai 2156 V
39. zed using Z score while qualitative characters were used as encoded Classification analysis was done using the Two Step classification method of the SPSS 13 0 program SPSS Inc 2004 Seven clusters were determined and entries were randomly selected using the criteria of the proportional number of each cluster for developing the P core The R core was developed after random sampling of the entire collection We have also compared the efficiency of PowerCore with MSTRAT which was recently developed for increasing the diversity of sub core sets The same comparison conditions of same number of entries 45 accessions were used since PowerCore selected 45 accessions to fill all diversity cells alleles and intervals of entire collection Default parameters 3 for replicates 30 for maximum iterations were applied for MSTRAT to run the rice data set 28 In the comparison of selecting efficiency using the coverage rate Coverage 96 Dc 100 where Dc is number of classes occupied in m De collection and De is number of classes occupied in entire accessions in each character and m is the number of variables The core sets developed using PowerCore showed 100 coverage of variables without any deviations indicating the highest selecting efficiency in all the phenotype characters This suggests PowerCore maintains all the diversity present in each class Table 3 Comparison of selecting efficiency of PowerCore with the conven
Download Pdf Manuals
Related Search