QMUL SBC322 Eco evo genomics Peer review concepts & blogging science setup Difficulties of genomics with emerging model organisms

1. Peer Review
y.wurm@qmul.ac.uk
SBC322

2. Peer review process
• In academia:
• For funding
• For publication
!
• Outside academia

3. Elsevier’s
standard official
process

4. Do ItYourself.
• See & feel value of peer review process
• Improve writing skills
• Improve critical reading skills
• Construct your online profile
• credit as author, as reviewer, as editor.

5. Plan?
• 8 papers - 1 blog post per paper
• 100-500 words
• 2 authors per blog post
• from “other theme”
• mix up groups
# needed in role # of reviews to do
Normal person everyone else 2
Web person 2 1
Editor responsible
for 4 blog posts
2 0

6. Some details: http://goo.gl/U0LlIK

8. Todos
• Decide your groups for authoring
• (must pair with different people than presentation!)
• cannot present and blog as part of same "theme"
• https://etherpad.mozilla.org/obVAlZUq5D
• Editors
• determine who is responsible for which papers
• alert authors when their stuff is due
• determine who receives which review task when
• Web people need to decide on platform (e.g. tumblr & color
scheme etc), name, potential guidelines, and set up…

9. Some implementation
tips/resources

10. Writing a good blog post
• Respect basic writing rules :)
• Similar to “New Scientist” article?
• Lots of online resources. e.g.:
http://scienceofblogging.com/how-to-write-a-good-research-blog-post/

11. Reviewing
• Mention strengths
• Most important:
• Potential for improvement!!
• Major themes
• Constructive suggestions if possible:
• structure / wording
• clarification / elimination
• Structuring a review:
• General statement
• Numbered list of specific points that need to be addressed.

12. Responding to a review
• Fix main text
• Specifically reply to each point raised by reviewers!

14. Todos
• Decide your groups for authoring
• (must pair with different people than presentation!)
• cannot present and blog as part of same "theme"
• https://etherpad.mozilla.org/obVAlZUq5D
• Editors
• determine who is responsible for which papers
• alert authors when their stuff is due
• determine who receives which review task when
• Web people need to decide on platform (e.g. tumblr & color
scheme etc), name, potential guidelines, and set up…

16. Genomics on emerging model
organisms

17. Genomes of emerging
model organisms
y.wurm@qmul.ac.uk
SBC322

18. So you want to do sequence a
genome…
• Sampling?
• algorithms prefer low diversity
• Sequencing approach?
• paired end?
• which sequencer?
• what is needed for scaffolding?

19. Scaffolding

20. So you want to do sequence a
genome…
• Sampling?
• algorithms prefer low diversity
• Sequencing approach?
• paired end?
• which sequencer?
• what is needed for scaffolding?
• input data Q/A?
• sequencer statistics
• fastqc
• bio-relevant measurements? (e.g. % mapping to known data)
Unable to detect all errors!

21. • trimming/deduplicating/filtering
• removing excess/redundant data
• removing errors
• Which assembler?
• used by others? (publications/ online list/ forum/
assemblathon)
• something new?
!
• assembly result QA
• sequence statistics (e.g., QUAST)
• bio-relevant measures (e.g. ,CEGMA)
So you want to do sequence a
genome…

22. Perfect parameters
• Instead: need to test many combinations
• of trimming
• of filtering
• different assembly software

23. ACGACACGGCGCGTCGAGCGTGCACAGAGAAGTTGAATTATCGAGGGaGAAAAAGGGCGCGAGGGAGGGGCAGGACGGTCAAACACTGAGAAAGCAGGCAACATCCGCGAACCCGTAAATTAATTAGGGCCAACATAATAG
CTGGGAATGGCTGGTAGTGGTGGTTCGTCTTCGTGGTCCAGCTTGCGGTTCCCGAGTGCCCTCGCAGTTCGCGCGGTCATGCCTCGGAAACTACACGATACACCTTGCGTCATCCTTACACGAGGATACCTGTTTGCGATC
CCCTGAGGTATTAACGAGCGTATAAGCAGACTCAAAGTACGAACACACTGCTAGTTTCGCGTGCATGTTGCTCGTCGCCGTGCAGACGAGTTAGTACTGTCGACAAAGTAGTCGTAAAGTACGTAAGAGTCTTCCTCTAGT
AGCGAGGACTAATCTCCCGGTACATTAATCTATGTATATTTTATGATATACACACCTGTATTTATCGAAAGTTTATGTTTATCTCGAAAATTAACGTTAATTTTCGAGGACGCAAAAGCTGTCGCAAGTTTaTTTAATTTT
GTTTGtATTTTTTTTTCTTGCTCATTTTTATTTCGAAGTATGCAAATTGAATCTCTTGGTGGCATAACGAGAATTTTCGAAGCTTAAAGGGATCTGCGTTGGCGCGAAGAGAATGGGACTTGTTTTAAACTTTTCTTTCCA
ACGAACACCGTTTCCTTCATTGTAACGTAAAAATGGTGAGCTTCTGCGGCGCGATTGGTCTCATCTTTCCTCTCGTATCGTTCGTCATTTTGTCCGAGAGCGTGTAGATATTGTACCCGATAGAACGGAGACGGAATCACG
CTATACGGTTCCCTCCCAAATGTTCGTTCCTCACGGGCAAAAGTACAAGTAAAAGTAGGAGGGTCCGACTTTATGACCCTACGAGGCACAATAAAGGTTGATGACTACTAAACGTAGAAGAACACGTATACAGTCCGACGT
AAAGTTATTTTTCAATTCCGCGGTCCTCCGCCGCAGTCGTTTTGCCTTGACGTGGAAAAGGAAATTTCCCGGGTTCTAGTCGTCCGGTCTTCTTTtCGTTCTACTGACAATACCATAtTTTCGACATAGATCGATCTCCTT
TtCTCTTtCTCTCTCTCTCTCTCTCTCTCTCTTGAAAATGAAAGCGCGGAAGAGCCGGATCGTGCAACGCACAATGCGAGGCCGCTTTGTACGAGGTACGAGGAGTCCGTCATGCGCCGTAAAACGCCGGAATATGCAATA
CTACTTTCGCAGCGACGGGGCTTGCACGAAGTAATATCGTGAAACGTAGAACCGTTCTTTTCATACGGATATGCGGGAGAAGTTGCTCGTCCGCCCTCCGGCGCATACACGTCGCGCGAGAGTATCGTGCATCCGAAACTC
TGAGATGAAACTCTTCTGTAGTCGATATTCGTCGCGATAAATAGATAAGTCTCGGATAAGGTAGAGACATCGATAATTCCGTTACGAGAATACTCGAGAATAAGATCCAAGTGAAGTGATCACGCTCCATATGGTTTCAGA
TTAATCTCCAATCGGCTGACGAAGGAGGATCATCCTTTTACCGGTGGAAAATAGGGTGGATTGGCGGAGCAAGAAGGCTAAACAGAGAATAAACAGGAGCTATAGCCGAACGAGGGAGAAGGTAAGTAGATGCCTCGGAGA
ACGTGAGCGAAAAAAGGAAACGGGTACGAGAGAAAAAGAAACGGACGGAATAGCGGCTCGGGATTCGCATCCCAAGGAAAACCAAGGCTATACCGGGGTCTTGGATTATTCGAGGCACGACGACGATCTTCGAGTCAGCCG
ACTGTCTGTACCGTGAAAGTGGCACGTATCGATCGCACGGCTGGATTATCTTCCACTTCGATCTACGACGATTACTTCCGCCATCGTATATCCGGGCTTTGCACTAGCGAGGCTATTTAAAAATCTGCGCTCAGTAACTAC
TTATGATTTTTCCATCAGAAACGATTGTGGAGAGAAAAGAGGGAAAAAAAGAGATAGACAGCCTCTGGCTCGAAATGCTAATTTCGCAATCGAGAATTAAAATGCACTTCTTTGTATCTAAATTTTCGTAGAATTAAAATA
AAATTGAATAAAGCAATGAATAAATTGAATAAACTAAAATATAGCTAAATATTTTTTCCTCTATACAAGGTGAATATAATTATCAAATATTTAAGTATGTAGATTGAATTTAAACAGCCTCGGAAGAGAAAAGAATCGGAT
AAACGAAATGCTTTTGCCTCTATTTTCAAGCACGTGACGAATAAAATCTAGCAAAGCTTTTCGACACAATATGTCGACGCAAATGTGGTCTATTTTGGCTAATGATTATTACCGGGAGTCCCGGGCACGGTGTGTCCGCGG
CGCGATAAATTAGAGCGCGAATCGACTTCCACGGCCGTTGTAGAAGGTACTTTGGCAAACGTTATTTCTTCCTGTCTCGAAGGAAGCGCCACTCGAAAACTTGGAAAAGTTCGGCCAGCTGCACGCACCGCGATCTCGGGT
CCGTTCTGGCTCGGTGGCGTGCGCAGGACGGTTGTGAGACGAGAGAAAGAGAGAAAGGAGGATAGAGCGCGAGAGGGAAAGAAGAGGGAACATCCGCGTGCGTGGTTGTATATGGCGTTAATGGCGGCGAGCATAAAGCAT
CCCCGcGCCTGCACGCTCGACCACGGTCGTTTACAGTGCCACTATTTATGTTGATAACTTCGGAATGGAGTCAGATACACGGTACCGAGTGCCGGCGGTTCGGCGGTGGTCCGGCAGCGGTCTGGTAGCACTTGCAAAGTA
TGGGAGAAGAAGGGGGATGGTGGATTCGCGGATCTTTTTGGTCGTGCAAGGAAGGCGGGTCGGTTAGGGTAGGTAGAGAGGAGACGAGCCGAGTCGAGAACAAGATTCAAGCGGAAAGTTTTGCGAGTTAATGGTGCGGAG
GTAATGCCGCGGCCGCAACAGCAACAGCCATCCCCCTGCTTGTGTGTTCGCTCGCTCGCTCACTtCTTCCGTTCTCTCCTCTTCGCGCTAGTTCTCTCTCTCTCTCTCTCTCTCTCTCTGtCTTTCTTGGAATAGCCGTAG
AAAAAaGGAAAAGAAAGAGAGAGAAAGAACGAGACTCCTTTCTCCCCACGAATTCTCTCCTCTCTTTAAGCACACTCTCTCTTCCTGCaccCCCCCCCcTCcTCTCTCTCTCTTTCTCTCTCTATTTTCTTGTCTTCCTCA
CTTGCATCATCCCTCGTCCATTTCCcTCTGGAGAACGTGCCACGTTCTCACTTCCTCGTTCGTCGCTACTTTTTTTCTTCTTTAGTTGTCTCCTCTCACACCCTCGAGACGGCCCGATCTTTTCCTCGTACAGCTCCTATC
ACGAACAGTCGCTAACAAGTGCATCGAATGCAAGTTGCCGACAAACTTCTTCCACCGATTTGTGCTTGTTCTCTGTGCATGCGCGGGCATGTATATCTCTATTAGGCGACATCTGCTCTCAGCTTTTTCATAACGAGGTAG
CGCGGATTCGCGCTCCGAGAGACTTCACGAAGCACTTCCGATCTCGCTACAGTAGAATGCGTATTGTATTTTCTTGTCTCTCTCATTTACTCTTTTCTATCTTTCGTATCTAGCGTGAATACTCCCATGAGGAATGTAGAA
ACCAGATTTTGAAACGGCTTCTTCGTATCTAAATTTTCTTAACTATTTGTTCCTCAAAGTCCATTTTGACGTTATAAATTTTTATTTTTTAATGAGAATGTTTTTATGTGGAGAAGAAAAGTACAACTTTTTTCAAAATGC
AATTAAATTTATACAAGACTACTAAGATAAAAAAAGATGCAAATAATAATGTTCAACTTACTAACTGCTATATTATTAAGGCCAAGTTAAATTACAGATTTATGATGTTGCAGAATATAATAGAAAAGTTTCAAGAAAAAA
aCATTTTAAAGCTTAAAGAGTTTGTTTTCAAACCCATCAAATTTTTTtCTCTGGCAGTGCTGCTGCTCTGCGACGTCATTTTCAAGTCGATCAATGCAAAGTTAACAAAAGTATTTCAACTTTAAAATCATGCAGAAAGTT
GGGAAAAATTTGTTTTCAATTTTACTTAAATTTTAGTTACATTTTTTCTAAAAGCTTAAAATCTCCTCTTTAAAATATGTCTTTAAAAATTGAGCTATGATTTTTCTTCACCGAGTTATCGTAATTTGAAATGGCCAATCG
ACGTTTTCTTTTCATCACTAGGAATAATGCCGGCGGATTTAAGCTTTCAGAAGATTCCAAGCAAAGTTGAAAACAATTTGTTTGAATTCCGCATGATCTCAAAGTTGAAGCTAAAAAAATTTCACAAGACTTTAAAAGACA
AAAAGTCAATGTTGCACAATCGACTTGGAAATAACGCCACTTGGAGCAGAGAAGTATTGCCGAGAAAAAGCTTCGACCGGGTTTGAAAGCAGGATCTATAGGCTTCCAAACTTTTTTTTtGAAAAATGGAGCTTTAAGGTT
ACTTTTCACGAAATTGTATAAATTGTGTTTTGTTGtTTTTATCATCGATTCGAAATGATCCTTTCATTTTGTTCAAGAATGTATCATTAACTTAATGCAATGATATCTTTTAATAATTCAATACTTCTTACTAATTAGATT
TAGAAAAGTTTCATGAACAATTTTAGAACGGTTATTGCTAATTATTCGCCAAAAACAGACGCCTTTCTTCGAGGAGTAACAACTCAAGCTGCATTCGCGGTTGACGGCTTTCCGCGGCGCGTCGCGGTAATATGGCTCCTA
TTTAATTACCCGGTCCTTTGGGAGCTTAAACCAGCCAGAGCTGGAACGGCTGCGCCGTTATTCTATCTAGACTCCTTTGCTTTCTCAAGCAGGCGCGCGATCAAACCTTCTCGCATAAAAGACAATCGCAGCTGGCAGTCG
ACGACGCGcGGGACAGTCGAATCATGACCCGCTCCTCTCTAGTTACCGCCGTCAGTCTGCTCTACTTCCAGACGCCGCGCGTAATCTATTCGACATTAGTTGCTTGATTGCACCGTAAAATGCGACGGCGACGTGAACGAG
AACGACGACGACGACGACGACGACGACAACGACGACGACAATGACAACGACGACGACGACAAGAGTGGGTTCGTCGGTGCTCGATGGCGCCTCCGATTTCAACCGCAGCACGATGCAAGCCCATTACTATCGCCCGGAGCT
AAACGGCACCCGGAGCTCGTGCCATTAAGGGAATCTAGGGTCCGATCCACCTCATTGAATTCCGTTcAATTGCGATTATGATAATGCGTGAACGATCGCCGTGGACGTGAGCTACGGaCAACgAGGGTGTTCGTTCTCGGC
TCAGAGAAACGCAGCGATAAAATTATCAGTGACAGCTTCATTTTTGTTACATTTGACGTTGAAAAATTTGCGAAAGAAATGTGCATTATTCAACTACATTGACAATTGTAAATCTTACATGACCTTTTATTAATATACATA
TATGTAAGATATATGTTCCATCTCTAGTCTCGTTCGATAATGAAGAAATTATAGCTGCAACATAGACGCCGGATTATTCGCGGGGGAAACCGTTGATTATTTGGACTCCGTGGGCTCGGGGTCTGGTTTACTTCTTCCCTT
ATGTCCGGAGATAATGGACACTATTACCTTAACGAGGCCCCAGTCTCTTAGCCGGTAATTGCTTCGAGATATCCGAGAGAGCTCCGGCGTACGTTGCCGCCTGGTGTTGCAGGCAGAGAACCCaGACGGTATTATTGCCGC
CGAGGCTACTCGCCCGTTTCATGGTGGTTATTGTTATGGGCCTGCGGCATTAAGATGTACACCGCACTCTCATACGGGACCCACCACCCCATATACGAGCTGCATATATACTTATGCGGGGAGGATTTCATTACGCCGCTT
CATAACTGGCGGTCTTCAAAATCGCGATAAATCGGGATTGTCTTCCTTGTTAAATCAGCTCCCGTTCCCCTTCCTCATATCGCTGACGAAGCCAACGAGACGGATTAATCTGCGCGATTGAATGGCCTCTATGACGTAAGC
GCACCGTTTACTGGCACGGCTCCTCGTGTTCACGTGAAACGATTTGCGTCGTAAATATTTTATTTTAACATCGCAACATCAAGACAGACGAGGATCGGCTATTGCCTCGTGATCCTAAAAGGGAGATTCTCAAGGCGGAAT
CGGGGTAACGCGTTCGTTGATCTCGCCAAACTACGGCATCTTGAGGACTAGTCTTAGaGGAAAAAAAGACGACGAGGAGACACGGTGAGCATTAGATGAGAAAGAGACGGCGCGGCGCGGTGCGGCGGAGCGAGACGGAAA
GAGATCAAATCTGGATATCAGGATTAGGGTGGGTACGTAATCCGCAGGACGACGGGTGGTAGGAACGGTGGATCCGTCGGCAGATCTCATCGCGCGGAGGAACTCTGCGGGTACTTCGCCCGGCCAAATACGACAAGAGCA
GCAGCCTAACTCGAGTAGAGCCGCCGAGATGGTTTACGGCTCGTCGCAAGTTGGTGAAATTTAAGAGCGCATTTAAAACTGGTTTGGCGCGATGCCCTGCGCCTCCCTGCAGCAGGTACTGCCGGCGAGAGATACCGCTGG
GCTCCGACAGGAGTTTATCGCCCTAACATTCTTGGAAAGCTTCGGATGGATTTCCCTCCTCAACCCATTTCTTCCGGCAGCACCTCAAATCGTCGCTTCTTTCGAGCTCCCTGTGTCGTCCGTTCTTTCCCCTTGCCACGA
AAATTCTTCCAACAGACTCGACACCAAATCGTCACGACGATCATCGGTCAAGATACCCGGAGAAACGTCGCGGACGATGTTACCGTCAGATCGGACGCTTTTAGCTCCGCATTGGAGCTTTTTCCTCGACCGTCTCGGAGG
AGATTTAGCGGACCGACAACAAATGAAGGTCATCTTTCGCGCGAGAAAGCGTCTCACCTTGATTTCCGTCTCGTTTCTCCGGAAATTGGATATCAACCGGACGAACTGTAATGTGTACGTTAAATTGCCAATTATATATAT
AATGTAACAGCTGATTATCTCAAGTGTCCTAAAAACCATTATACTCTTAATTTCTGTGAAAAATGGCGAAAATAAAAAAGAAACCGATCTTAATAAAGATATTCTTCCTGATAGATGCCATGACCCACGTGGAAAACTTTT
TAGTTTTGTACAGTGGTATTATACGTTATCTTCCGCTGAACGTAAGACGTGCCTATCGCGCAATTTCATCGCGACGTCGTCGTATAGCGATTATGGCTACTCCATTAAAAATGAATTTTATAAAGGCAATCTTTCCAAGCG
ATCGTTGTAGGAGAAAAAGGCGAAAGCCGGAGCCAAAGGGGATGAGGCCACTACCTTTGGCTGATCCACTTCGAATGATAATCACCTCTAGGAGACTCAATTTCGCCCTGCTCCGCGTCCTTACCCGTTCCTATCTTCGGA
AGGTTCAACGCCGCAGCGGACTGCATCTTTCACTCCCTTCGTCACCACCGCCCTATTCCTATCGCCCTCCGCGCGCCTACCGCCCCTATATCCTTCCCTTCCTTCACtCCTAGACTATTCTGAACGACCTCTTCCCCCATT
CGCCAACGCTCACTCCTAACTGATTGGAGTACCAATCAATGCGGCATTCAGGCGGCCGTGCTGAAaCTTTAGGAAATTAACTATTCACTCTCTGGAAATGGTTATTTGGAAGGCCGGAAAGGCAGTCGGGACTACGTTACG
But making it
useable is hard.
Sequencing a genome is
now cheap & easy.

24. Gene prediction
Dozens of software algorithms: dozens of predictions
Yandell&Ence2013NRG
TTTTtACCTGTTTTtGAAAAGGTAATTTTCTTTAGATATATACAGTTTGTAATaTTAGGTATTTTATAAACAGTGTGTATATTTCTTACAATATAAAAGACACAATTGCAAACTAGCATGATTGTAAACAATTGCTAAACGGATCAATATAAATTAAAATTGTAATATTAAGTATCAAACCGATAATTTTT
Evidence
Why?

25. Gene prediction
Dozens of software algorithms: dozens of predictions
20% failure rate:
•missing pieces
•extra pieces
•incorrect merging
•incorrect splitting
Visual inspection... and
manual fixing required.
1 gene = 20 minutes to 3 days
Yandell&Ence2013NRG
TTTTtACCTGTTTTtGAAAAGGTAATTTTCTTTAGATATATACAGTTTGTAATaTTAGGTATTTTATAAACAGTGTGTATATTTCTTACAATATAAAAGACACAATTGCAAACTAGCATGATTGTAAACAATTGCTAAACGGATCAATATAAATTAAAATTGTAATATTAAGTATCAAACCGATAATTTTT
Evidence
Consensus:

26. Annotation in practice
• Annotation software (in google chrome):Afra Login
• http://afra.sbcs.qmul.ac.uk/#login
• Your task:
• work through 3 examples
• 5 additional gene annotations (through “Curate” button)