SlideShare une entreprise Scribd logo
1  sur  18
Pre-lab (front-end) processing
Different collections have different standards



Challenge is to transform this into a standard
            lab-compatible format



 Core labs operate in 96-well plate format
which require compatible front-end solutions




If this is not addressed collection processing may become the bottleneck in the analytical chain
which could hamper large-scale barcoding projects.
Logistical problems: lots and specimens
Barcoding – Specimen based




  BATCH 09/10/2010
    Multiple taxa from the same
          collecting event




                            Unique voucher number



   Single collection voucher
   with data link to the original
   batch number
Unique voucher number



            Label with
            voucher nr.
             OM2035
Pre-lab (front-end) processing
                                             1. Arraying
            Unprocessed                                                             Formatted
             specimens                                     2. Databasing
                                                                                    data records
                                             Labeling

4 Main steps required to transform
specimen collections into lab-ready          3. Imaging
96-well microplates
                                                                      Formatted
                                                                       images
                                           4. Sampling/ Subsampling



                                   Lab-ready 96 well microplate

                                            Core lab procedure LIMS



                                                   BOLD Systems (www.boldsystems.org)


LIMS – Lab information management system                          Pre-conference Short Course on DNA Barcoding Methods
SAMPLING KITS
        Dispatched by core analytical facilities; To streamline sample submission


1. Sampling plates            2. Sampling instructions          3. CD with templates for
                                                                       data entry



                                                                   4. BMTA & Data Policy
                                                                   Agreement (iBOL)
Specimen arraying + sampling
CONCEPT: Grouping of specimens in an arrangement that is compatible
with a 96-well format used by most labs




 Specimen aggregate matching plate map

                                                        12 x 8 format
                                                 95 samples + 1 negative control


                Arraying      Databasing   Imaging          Sampling
Specimen/sample arraying: Examples

Direct sampling


                                                      Subsample right amount of tissue
                                   1drop/30μl 95-
                                    100% ethanol


                                                                                                        
Specimens order to
 match plate map                                                   Work sterile!
                                                                                                        
                                                                                                      Excessive tissue might
                                                                                                      inhibit DNA extraction


                                Enter corresponding
                                sample ID in CCDB
                                record
                                                               Ensure all cap strips are firmly
                                                               into the wells

                     Arraying                Databasing              Imaging                      Sampling
Specimen/sample arraying: Examples
                                                          A1

                                                  H

                                                                          12




                                                          Plant box




Tissue sampling – line-up the samples

                                             Correct (1 & 2) and incorrect (3 & 4)
                                                        tissue sampling

                 Arraying       Databasing   Imaging           Sampling
Field data
Transferred to specimen data sheet
                                                                   Measurements
Compulsory fields                 Include if available
Collecting number                 Genus
Date of collection                Species
Country/province
GPS
Field identification
Family
Field observations                                                  Total length
Picture numbers
Collectors
Measurements
Weight
Sex                                                                Fork length
                       Arraying        Databasing        Imaging     Sampling
Data collection: BOLD requirements




     Arraying   Databasing   Imaging   Sampling
Data collection: BOLD requirements




     Arraying   Databasing   Imaging   Sampling
BOLD specimen data spreadsheet
MS Exel based – 4 tabs/pages


                       Voucher Information




            Arraying       Databasing   Imaging   Sampling
BOLD specimen data spreadsheet
                Taxonomy




     Arraying   Databasing   Imaging   Sampling
BOLD specimen data spreadsheet
               Specimen details




    Arraying     Databasing   Imaging   Sampling
BOLD specimen data spreadsheet
               Collection Data




    Arraying     Databasing   Imaging   Sampling
Specimen Imaging
Important in the barcoding process – can serve as an electronic voucher




    • .jpg format
    • High resolution pictures up to 20 megapixels
    • Maximum of 10 images per specimen
   Arraying        Databasing       Imaging          Sampling
Specimen Imaging
    Framing/Orientation                       Display maximum diagnostic characters




•   Leave as little margins as possible           Flower/Bud             Fruit    Stem and spines
•   Do not cut off parts of specimen
•   Scale bar can be useful                                    Background
•   BOLD allows batch comparison–
    orientation must be the same




                                                  Colour backgrounds are impractical

                     Arraying        Databasing       Imaging         Sampling
Key stages of front-end processing

         1               2               3


Sampling &
Field data

                                             4



             NEXT STEP IN THE PIPELINE
             PCR
             Sequencing

Contenu connexe

Similaire à Michelle Van der Bank - Front-end processing

Reference Materials Selection and Design Working Group Summary Aug2012
Reference Materials Selection and Design Working Group Summary Aug2012Reference Materials Selection and Design Working Group Summary Aug2012
Reference Materials Selection and Design Working Group Summary Aug2012
GenomeInABottle
 
20100516 bioinformatics kapushesky_lecture08
20100516 bioinformatics kapushesky_lecture0820100516 bioinformatics kapushesky_lecture08
20100516 bioinformatics kapushesky_lecture08
Computer Science Club
 
Informatics In The Manchester Centre For Integrative Systems Biology
Informatics In The Manchester Centre For Integrative Systems BiologyInformatics In The Manchester Centre For Integrative Systems Biology
Informatics In The Manchester Centre For Integrative Systems Biology
Neil Swainston
 
2015.04.08-Next-generation-sequencing-issues
2015.04.08-Next-generation-sequencing-issues2015.04.08-Next-generation-sequencing-issues
2015.04.08-Next-generation-sequencing-issues
Dongyan Zhao
 

Similaire à Michelle Van der Bank - Front-end processing (14)

Reference Materials Selection and Design Working Group Summary Aug2012
Reference Materials Selection and Design Working Group Summary Aug2012Reference Materials Selection and Design Working Group Summary Aug2012
Reference Materials Selection and Design Working Group Summary Aug2012
 
RNA-seq differential expression analysis
RNA-seq differential expression analysisRNA-seq differential expression analysis
RNA-seq differential expression analysis
 
Paper presentation: Taverna, reloaded
Paper presentation: Taverna, reloadedPaper presentation: Taverna, reloaded
Paper presentation: Taverna, reloaded
 
20100516 bioinformatics kapushesky_lecture08
20100516 bioinformatics kapushesky_lecture0820100516 bioinformatics kapushesky_lecture08
20100516 bioinformatics kapushesky_lecture08
 
Giab ashg 2017
Giab ashg 2017Giab ashg 2017
Giab ashg 2017
 
Tools for Using NIST Reference Materials
Tools for Using NIST Reference MaterialsTools for Using NIST Reference Materials
Tools for Using NIST Reference Materials
 
Ashg2014 grc workshop_schneider
Ashg2014 grc workshop_schneiderAshg2014 grc workshop_schneider
Ashg2014 grc workshop_schneider
 
Stephen Friend CRUK-MD Anderson Cancer Workshop 2012-02-28
Stephen Friend CRUK-MD Anderson Cancer Workshop 2012-02-28Stephen Friend CRUK-MD Anderson Cancer Workshop 2012-02-28
Stephen Friend CRUK-MD Anderson Cancer Workshop 2012-02-28
 
To bag, or to boost? A question of balance
To bag, or to boost? A question of balanceTo bag, or to boost? A question of balance
To bag, or to boost? A question of balance
 
Towards automated phenotypic cell profiling with high-content imaging
Towards automated phenotypic cell profiling with high-content imagingTowards automated phenotypic cell profiling with high-content imaging
Towards automated phenotypic cell profiling with high-content imaging
 
160627 giab for festival sv workshop
160627 giab for festival sv workshop160627 giab for festival sv workshop
160627 giab for festival sv workshop
 
Informatics In The Manchester Centre For Integrative Systems Biology
Informatics In The Manchester Centre For Integrative Systems BiologyInformatics In The Manchester Centre For Integrative Systems Biology
Informatics In The Manchester Centre For Integrative Systems Biology
 
2015.04.08-Next-generation-sequencing-issues
2015.04.08-Next-generation-sequencing-issues2015.04.08-Next-generation-sequencing-issues
2015.04.08-Next-generation-sequencing-issues
 
Dario Lijtmaer - DNA extraction
Dario Lijtmaer - DNA extractionDario Lijtmaer - DNA extraction
Dario Lijtmaer - DNA extraction
 

Plus de Consortium for the Barcode of Life (CBOL)

Plus de Consortium for the Barcode of Life (CBOL) (20)

Andrew Lowe - Opening Plenary
Andrew Lowe - Opening PlenaryAndrew Lowe - Opening Plenary
Andrew Lowe - Opening Plenary
 
Axel Hausmann - Invertebrates Plenary
Axel Hausmann - Invertebrates PlenaryAxel Hausmann - Invertebrates Plenary
Axel Hausmann - Invertebrates Plenary
 
Hannah McPherson - Plants Plenary
Hannah McPherson - Plants PlenaryHannah McPherson - Plants Plenary
Hannah McPherson - Plants Plenary
 
Rebecca Johnson - Opening Plenary
Rebecca Johnson - Opening PlenaryRebecca Johnson - Opening Plenary
Rebecca Johnson - Opening Plenary
 
K.A. Seifert - Algae, Protists & Fungi Plenary
K.A. Seifert - Algae, Protists & Fungi PlenaryK.A. Seifert - Algae, Protists & Fungi Plenary
K.A. Seifert - Algae, Protists & Fungi Plenary
 
Scott Miller - Opening Plenary
Scott Miller - Opening PlenaryScott Miller - Opening Plenary
Scott Miller - Opening Plenary
 
Bruce Deagle - Opening Plenary
Bruce Deagle - Opening PlenaryBruce Deagle - Opening Plenary
Bruce Deagle - Opening Plenary
 
Ralph Imondi - Opening Plenary
Ralph Imondi - Opening PlenaryRalph Imondi - Opening Plenary
Ralph Imondi - Opening Plenary
 
Damon Little - Opening Plenary
Damon Little - Opening PlenaryDamon Little - Opening Plenary
Damon Little - Opening Plenary
 
Natasha de Vere - Plants Plenary
Natasha de Vere - Plants PlenaryNatasha de Vere - Plants Plenary
Natasha de Vere - Plants Plenary
 
Robert Hanner - Closing Plenary
Robert Hanner - Closing PlenaryRobert Hanner - Closing Plenary
Robert Hanner - Closing Plenary
 
Paul Hebert - Saturday Closing Plenary
Paul Hebert - Saturday Closing PlenaryPaul Hebert - Saturday Closing Plenary
Paul Hebert - Saturday Closing Plenary
 
Conrad Schoch - Saturday Closing Plenary
Conrad Schoch - Saturday Closing PlenaryConrad Schoch - Saturday Closing Plenary
Conrad Schoch - Saturday Closing Plenary
 
Xin Zhou - Saturday Closing Plenary
Xin Zhou - Saturday Closing PlenaryXin Zhou - Saturday Closing Plenary
Xin Zhou - Saturday Closing Plenary
 
Pierre Taberlet - Saturday Closing Plenary
Pierre Taberlet - Saturday Closing PlenaryPierre Taberlet - Saturday Closing Plenary
Pierre Taberlet - Saturday Closing Plenary
 
Stoeckle - All Birds Barcoding Initiative
Stoeckle - All Birds Barcoding Initiative Stoeckle - All Birds Barcoding Initiative
Stoeckle - All Birds Barcoding Initiative
 
Weiland Meyer - Algae, Protists & Fungi Plenary
Weiland Meyer - Algae, Protists & Fungi PlenaryWeiland Meyer - Algae, Protists & Fungi Plenary
Weiland Meyer - Algae, Protists & Fungi Plenary
 
Alain Franc - Algae, Protists & Fungi Plenary
Alain Franc - Algae, Protists & Fungi PlenaryAlain Franc - Algae, Protists & Fungi Plenary
Alain Franc - Algae, Protists & Fungi Plenary
 
Marieka Gryzenhout - Algae, Protists & Fungi Plenary
Marieka Gryzenhout - Algae, Protists & Fungi PlenaryMarieka Gryzenhout - Algae, Protists & Fungi Plenary
Marieka Gryzenhout - Algae, Protists & Fungi Plenary
 
John La Salle - Opening Plenary
John La Salle - Opening PlenaryJohn La Salle - Opening Plenary
John La Salle - Opening Plenary
 

Dernier

Making and Justifying Mathematical Decisions.pdf
Making and Justifying Mathematical Decisions.pdfMaking and Justifying Mathematical Decisions.pdf
Making and Justifying Mathematical Decisions.pdf
Chris Hunter
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdf
QucHHunhnh
 
Seal of Good Local Governance (SGLG) 2024Final.pptx
Seal of Good Local Governance (SGLG) 2024Final.pptxSeal of Good Local Governance (SGLG) 2024Final.pptx
Seal of Good Local Governance (SGLG) 2024Final.pptx
negromaestrong
 

Dernier (20)

microwave assisted reaction. General introduction
microwave assisted reaction. General introductionmicrowave assisted reaction. General introduction
microwave assisted reaction. General introduction
 
Making and Justifying Mathematical Decisions.pdf
Making and Justifying Mathematical Decisions.pdfMaking and Justifying Mathematical Decisions.pdf
Making and Justifying Mathematical Decisions.pdf
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdf
 
Unit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptxUnit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptx
 
Unit-IV; Professional Sales Representative (PSR).pptx
Unit-IV; Professional Sales Representative (PSR).pptxUnit-IV; Professional Sales Representative (PSR).pptx
Unit-IV; Professional Sales Representative (PSR).pptx
 
Class 11th Physics NEET formula sheet pdf
Class 11th Physics NEET formula sheet pdfClass 11th Physics NEET formula sheet pdf
Class 11th Physics NEET formula sheet pdf
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and Mode
 
Micro-Scholarship, What it is, How can it help me.pdf
Micro-Scholarship, What it is, How can it help me.pdfMicro-Scholarship, What it is, How can it help me.pdf
Micro-Scholarship, What it is, How can it help me.pdf
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The Basics
 
On National Teacher Day, meet the 2024-25 Kenan Fellows
On National Teacher Day, meet the 2024-25 Kenan FellowsOn National Teacher Day, meet the 2024-25 Kenan Fellows
On National Teacher Day, meet the 2024-25 Kenan Fellows
 
Seal of Good Local Governance (SGLG) 2024Final.pptx
Seal of Good Local Governance (SGLG) 2024Final.pptxSeal of Good Local Governance (SGLG) 2024Final.pptx
Seal of Good Local Governance (SGLG) 2024Final.pptx
 
Application orientated numerical on hev.ppt
Application orientated numerical on hev.pptApplication orientated numerical on hev.ppt
Application orientated numerical on hev.ppt
 
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
 
Python Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docxPython Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docx
 
This PowerPoint helps students to consider the concept of infinity.
This PowerPoint helps students to consider the concept of infinity.This PowerPoint helps students to consider the concept of infinity.
This PowerPoint helps students to consider the concept of infinity.
 
TỔNG ÔN TẬP THI VÀO LỚP 10 MÔN TIẾNG ANH NĂM HỌC 2023 - 2024 CÓ ĐÁP ÁN (NGỮ Â...
TỔNG ÔN TẬP THI VÀO LỚP 10 MÔN TIẾNG ANH NĂM HỌC 2023 - 2024 CÓ ĐÁP ÁN (NGỮ Â...TỔNG ÔN TẬP THI VÀO LỚP 10 MÔN TIẾNG ANH NĂM HỌC 2023 - 2024 CÓ ĐÁP ÁN (NGỮ Â...
TỔNG ÔN TẬP THI VÀO LỚP 10 MÔN TIẾNG ANH NĂM HỌC 2023 - 2024 CÓ ĐÁP ÁN (NGỮ Â...
 
psychiatric nursing HISTORY COLLECTION .docx
psychiatric  nursing HISTORY  COLLECTION  .docxpsychiatric  nursing HISTORY  COLLECTION  .docx
psychiatric nursing HISTORY COLLECTION .docx
 
Z Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphZ Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot Graph
 
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
 
Unit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptxUnit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptx
 

Michelle Van der Bank - Front-end processing

  • 1. Pre-lab (front-end) processing Different collections have different standards Challenge is to transform this into a standard lab-compatible format Core labs operate in 96-well plate format which require compatible front-end solutions If this is not addressed collection processing may become the bottleneck in the analytical chain which could hamper large-scale barcoding projects.
  • 2. Logistical problems: lots and specimens Barcoding – Specimen based BATCH 09/10/2010 Multiple taxa from the same collecting event Unique voucher number Single collection voucher with data link to the original batch number
  • 3. Unique voucher number Label with voucher nr. OM2035
  • 4. Pre-lab (front-end) processing 1. Arraying Unprocessed Formatted specimens 2. Databasing data records Labeling 4 Main steps required to transform specimen collections into lab-ready 3. Imaging 96-well microplates Formatted images 4. Sampling/ Subsampling Lab-ready 96 well microplate Core lab procedure LIMS BOLD Systems (www.boldsystems.org) LIMS – Lab information management system Pre-conference Short Course on DNA Barcoding Methods
  • 5. SAMPLING KITS Dispatched by core analytical facilities; To streamline sample submission 1. Sampling plates 2. Sampling instructions 3. CD with templates for data entry 4. BMTA & Data Policy Agreement (iBOL)
  • 6. Specimen arraying + sampling CONCEPT: Grouping of specimens in an arrangement that is compatible with a 96-well format used by most labs Specimen aggregate matching plate map 12 x 8 format 95 samples + 1 negative control Arraying Databasing Imaging Sampling
  • 7. Specimen/sample arraying: Examples Direct sampling Subsample right amount of tissue 1drop/30μl 95- 100% ethanol  Specimens order to match plate map Work sterile!  Excessive tissue might inhibit DNA extraction Enter corresponding sample ID in CCDB record Ensure all cap strips are firmly into the wells Arraying Databasing Imaging Sampling
  • 8. Specimen/sample arraying: Examples A1 H 12 Plant box Tissue sampling – line-up the samples Correct (1 & 2) and incorrect (3 & 4) tissue sampling Arraying Databasing Imaging Sampling
  • 9. Field data Transferred to specimen data sheet Measurements Compulsory fields Include if available Collecting number Genus Date of collection Species Country/province GPS Field identification Family Field observations Total length Picture numbers Collectors Measurements Weight Sex Fork length Arraying Databasing Imaging Sampling
  • 10. Data collection: BOLD requirements Arraying Databasing Imaging Sampling
  • 11. Data collection: BOLD requirements Arraying Databasing Imaging Sampling
  • 12. BOLD specimen data spreadsheet MS Exel based – 4 tabs/pages Voucher Information Arraying Databasing Imaging Sampling
  • 13. BOLD specimen data spreadsheet Taxonomy Arraying Databasing Imaging Sampling
  • 14. BOLD specimen data spreadsheet Specimen details Arraying Databasing Imaging Sampling
  • 15. BOLD specimen data spreadsheet Collection Data Arraying Databasing Imaging Sampling
  • 16. Specimen Imaging Important in the barcoding process – can serve as an electronic voucher • .jpg format • High resolution pictures up to 20 megapixels • Maximum of 10 images per specimen Arraying Databasing Imaging Sampling
  • 17. Specimen Imaging Framing/Orientation Display maximum diagnostic characters • Leave as little margins as possible Flower/Bud Fruit Stem and spines • Do not cut off parts of specimen • Scale bar can be useful Background • BOLD allows batch comparison– orientation must be the same Colour backgrounds are impractical Arraying Databasing Imaging Sampling
  • 18. Key stages of front-end processing 1 2 3 Sampling & Field data 4 NEXT STEP IN THE PIPELINE PCR Sequencing