SpHPP Bioinformatics.3rd CHr-16 Workshop. Miraflores de la SierraDecember, 10th-11th 2012 Alberto Medina

Summary

1. Logistics2. Activities and meetings3. Data Analysis pipeline

1. Shotgun2. MRM

4. Sharing data5. Viewing data6. Conclusions

Summary

1. Logistics2. Activities and meetings3. Data Analysis pipeline

1. Shotgun2. MRM

4. Sharing data5. Viewing data6. Conclusions

Logistics

• Logistics:• FTP. Public FTP for exchanging “regular” files. A new

system should be developed for high throughput instruments.• Mailing list. Different lists grouping by working

groups • Wiki space: http://community.uv.es/mediawiki/• Web site: http://hpp-sp.com• Google code site:

https://code.google.com/p/s-chpp/Webex teleconference

Website (http://hpp-sp.com)

Website. Consortium introduction

Website.WG introduction

Website. BD page

Website CHPP

C-HPP Wiki

Summary

1. Logistics2. Activities and meetings3. Data Analysis pipeline

1. Shotgun2. MRM

4. Sharing data5. Viewing data6. Conclusions

Activities and metings

9/3rd: Follow-up teleconference.9/19th: Follow-up teleconference.10/3rd: Follow-up teleconference.10/17th: Follow-up teleconference.10/31st: Follow-up teleconference.11/21st: Follow-up teleconference.

Summary

1. Logistics2. Activities and meetings3. Data Analysis pipeline

1. Shotgun2. MRM

4. Sharing data5. Viewing data6. Conclusions

Summary

1. Logistics2. Activities and meetings3. Data Analysis pipeline

1. Shotgun2. MRM

4. Sharing data5. Viewing data6. Conclusions

Data Analysis Pipeline. Shotgun

Data Analysis Pipeline. Shotgun

We are growing!

Main improvements

• Some bugs have been fixed

• Data Analysis could be directly done by end-users

• Sequest has been included.

• Protein Inference – Protein Grouping.

Data Analysis. Protein Grouping

Main improvements

• Some bugs have been fixed

• Data Analysis could be directly done by end-users

• Sequest has been included.

• Protein Inference – Protein Grouping.

• Mascot Server

• Curated experiments

Curated experiments

Summary

1. Logistics2. Activities and meetings3. Data Analysis pipeline

1. Shotgun2. MRM

4. Sharing data5. Viewing data6. Conclusions

Data Analysis. MRM

Data Analysis. MRM

Data Analysis. Proteotipic?

Summary

1. Logistics2. Activities and meetings3. Data Analysis pipeline

1. Shotgun2. MRM

4. Sharing data5. Viewing data6. Conclusions

Sharing Data

Sharing Data

Sharing Data

Summary

1. Logistics2. Activities and meetings3. Data Analysis pipeline

1. Shotgun2. MRM

4. Sharing data5. Viewing data6. Conclusions

Public Data

Viewing Data

Viewing Data

Viewing Data

Viewing other “data”

Summary

1. Logistics2. Activities and meetings3. Data Analysis pipeline

1. Shotgun2. MRM

4. Sharing data5. Viewing data6. Conclusions

Conclusions

• Website should be filled. WG description ASAP.

• Continuous activities and meetings.

• Data Analysis.

• Shotgun analysis is great!

• MRM DB

• Data submission pipeline. Sequest is “active”.

• Interaction with C-HPP and other chromosomes (TPB).

Acknowledges • CIMA:• Victor Segura• Fernando Corrales

• UCM:• Vital Vialas

• IIBB/CSIC:• Óscar Gallardo

• Ibermática• Aitor Moreno

• UPV:• Gorka Prieto• Kerman Aloria.• Jesús M. Arizmendi.

• UV:• Manuel S. Pino• Javi Órtiz

• CNB/CSIC:• Salvador Martínez

de Bartolomé.• Juan Pablo Albar

Discussion

• Submission pipeline.

• Protein Inference. Resubmit the data.

• Sequence BDs.

• MRM queries.

• Logo and name.