Automated assemblies are one thing, good assemblies are another! This presentation covers the basic concepts of using paired-end and mate pair read data to identify mis-assemblies. It also covers some of the tools for visualising and correcting mis-assemblies. An attempt is made to rate these tools on their feature set and scalability beyond small (<15MBase) genomes and provides some closing remakes about what the ideal genome assembly editing tool should have in terms of features.

1. Genome Assembly Forensics and
Visualisation
Nathan S. Watson-Haigh
Fri 11th May 2012, ACPFG Journal Club
Schatz, M.C. et al., 2007. Hawkeye: an interactive visual analytics tool for genome assemblies. Genome Biology, 8(3), p.R34.
Phillippy, A.M., Schatz, M.C. & Pop, M., 2008. Genome assembly forensics: finding the elusive mis-assembly. Genome
Biology, 9(3), p.R55.
Schatz, M.C. et al., 2011. Hawkeye and AMOS: Visualizing and Assessing the Quality of Genome Assemblies. Briefings in
Bioinformatics. Available at: http://bib.oxfordjournals.org/content/early/2011/12/23/bib.bbr074.

2. Overview
• Genome Assembly
• N50/N90/N95
• Paired-end and Matepair Reads
• Mis-assembly Signatures
• Assembly Validation and Manual Editing

3. Genome Assembly – Shotgun Reads
DNA being sequenced
aligned shotgun reads

4. Genome Assembly – Repeats

5. Genome Assembly – Repeats

6. Genome Assembly – Repeats
reads from different
double coverage
repeats can’t be
resolved

7. Genome Assembly – Repeats

8. Genome Assembly – Diploid

9. Assembly Metrics – N50
• The N50 is the most widely reported metric for de
novo assemblies
• It is a single measure of the contig length size
distribution of an assembly
– If contigs are sorted into descending length order, the
n50 is the size of the contig above which the assembly
contains at least 50% of the total length of all the
contigs
– Commonly reported with the N90 and N95

10. Assembly Metrics – N50
+ = N50
+ = N90
+ = N95

11. Assembly Metrics – N50
• The N50 is the most widely reported metric for de
novo assemblies
• It is a single measure of the contig length size
distribution of an assembly
– If contigs are sorted into descending length order, the
n50 is the size of the contig above which the assembly
contains at least 50% of the total length of all the
contigs
– Commonly reported with the N90 and N95
• These stats DO NOT imply anything about
assembly quality
– Could simply concatenate contigs together to get a
better N50!!

12. Paired-end Reads

13. Matepair Reads

14. Paired-end and Matepair Reads
Paired-end Matepair
reverse
compliment

15. So, Why are Pairs so Useful?

16. So, Why are Pairs so Useful?

17. Pairs are Useful – Orientation and
Separation

18. Pairs are Useful – Orientation and
Separation

19. Pairs are Useful – Orientation and
Separation

20. Pairs are Useful – Orientation and
Separation

21. Pairs are Useful – Orientation and
Separation
Incorrect orientation
Incorrect distance

22. Mis-assembly Signatures –
Collapsed Tandem Repeat
Correct alignment
Incorrect alignment

23. Mis-assembly Signatures –
Collapsed Tandem Repeat
Correct assembly
Mis-assembly

24. Mis-assembly Signatures –
Collapsed (small) Tandem Repeat
Correct assembly
Mis-assembly

25. Mis-assembly Signatures –
Collapsed Repeat
Correct assembly
Mis-assembly

26. Mis-assembly Signatures –
Rearrangement
Correct assembly
Mis-assembly

27. Automated Assemblies Are One
Thing, Good Assemblies Are Another
• Given the computer resources you can generate
an automated assembly in a few weeks
– Not necessarily good
– Need to optimise assembly parameters
• For small organisms (< ~15Mbases)
– Commodity hardware
– OLC assemblers
• For larger genomes
– More RAM (10-100’s Gbytes) for OLC assemblers
– De Bruijin Graph assemblers
– Read Mapping step to generate contig read alignments

28. Automated Assemblies Are One
Thing, Good Assemblies Are Another
• Automated assemblies need to be checked for
mis-assemblies
– Need paired-end/matepair reads
– Need viewers to visualise paired-end data
– Need editors to break/join/reassemble parts of the
assembly deemed to be inconsistent with read pair info
– Need enough computer hardware to allow all this data to
be loaded – especially with large volumes of Illumina
paired-end data

29. Automated Assemblies Are One
Thing, Good Assemblies Are Another
• Very time consuming and laborious to check/edit
– Small assemblies (< ~15Mbases)
• Several weeks/few months to move 1 scaffold/contig at a
time
– Large assemblies need a team to do the same thing
• Need enough RAM to load all the paired-end data
• Need ways to identify regions requiring closer inspection
• identify possible mis-assemblies
• Major hurdles
– Software inadequacies
– Time
– File formats! Grrrr!

30. Software Inadequacies
Software Contig Scaffold Editing Reassemble Clipping Other
View View Info
SeqMan 9 9 6 6 6 $$, buggy, not for
Pro large assemblies
(32bit), 1 template size
Gap5 6 NA 9 NA 8 Free, join editor, contig
comparator, poor visual
support for many
contigs, shuffle pads,
ACE, multiple template
sizes
Consed 6 6 5 9 6 Free/US$2500/US$10k
, poor visual support
for many contigs,
multiple templates
sizes
Hawkeye 9 9 NA NA 7 Leverages AMOS,
automated detection of
mis-assemblies, large
assemblies, modular

31. SeqMan Pro – Strategy View

32. SeqMan Pro

33. Software Inadequacies
Software Contig Scaffold Editing Reassemble Clipping Other
View View Info
SeqMan 9 9 6 6 6 $$, buggy, not for
Pro large assemblies
(32bit), 1 template size
Gap5 6 NA 9 NA 8 Free, join editor, contig
comparator, poor visual
support for many
contigs, shuffle pads,
ACE, multiple template
sizes
Consed 6 6 5 9 6 Free/US$2500/US$10k
, poor visual support
for many contigs,
multiple templates
sizes
Hawkeye 9 9 NA NA 7 Leverages AMOS,
automated detection of
mis-assemblies, large
assemblies, modular

34. Gap5 – Template View

35. Gap5 – Contig Comparator

36. Gap5 – Join Editor

37. Gap5 – Contig Editor

38. Software Inadequacies
Software Contig Scaffold Editing Reassemble Clipping Other
View View Info
SeqMan 9 9 6 6 6 $$, buggy, not for
Pro large assemblies
(32bit), 1 template size
Gap5 6 NA 9 NA 8 Free, join editor, contig
comparator, poor visual
support for many
contigs, shuffle pads,
ACE, multiple template
sizes
Consed 6 6 5 9 6 Free/US$2500/US$10k
, poor visual support
for many contigs,
multiple templates
sizes
Hawkeye 9 9 NA NA 7 Leverages AMOS,
automated detection of
mis-assemblies, large
assemblies, modular

39. Consed – Assembly View

40. Consed – Contig Viewer/Editor

41. Software Inadequacies
Software Contig Scaffold Editing Reassemble Clipping Other
View View Info
SeqMan 9 9 6 6 6 $$, buggy, not for
Pro large assemblies
(32bit), 1 template size
Gap5 6 NA 9 NA 8 Free, join editor, contig
comparator, poor visual
support for many
contigs, shuffle pads,
ACE, multiple template
sizes
Consed 6 6 5 9 6 Free/US$2500/US$10k
, poor visual support
for many contigs,
multiple templates
sizes
Hawkeye 9 9 NA NA 7 Leverages AMOS,
automated detection of
mis-assemblies, large
assemblies, modular

48. Scaffold/Contig Length Distribution

49. Library Stats

50. Compression-Expansion (CE)
Statistic
• A measure of the
deviation of local
distribution of insert sizes
to the global distribution
of insert sizes
– 0 indicates no deviation
– ≤ 3 indicates much
compression
– ≥3 indicates much
expansion

51. Insert Coverage Read Coverage

52. 500bp inserts 3kb inserts
20kb inserts

53. AMOSvalidate
• An assembly analysis pipeline to identify possible
mis-assemblies
– Paired-end data
• CE stats
• Incorrect orientation
• Missing mate
– Coverage
– SNP density
– Singletons

55. Hawkeye Cons
• Poor support for correcting mis-assemblies once
detected

56. Software Inadequacies
Software Contig Scaffold Editing Reassemble Clipping Other
View View Info
SeqMan 9 9 6 6 6 $$, buggy, not for
Pro large assemblies
(32bit), 1 template size
Gap5 6 NA 9 NA 8 Free, join editor, contig
comparator, poor visual
support for many
contigs, shuffle pads,
ACE, multiple template
sizes
Consed 6 6 5 9 6 Free/US$2500/US$10k
, poor visual support
for many contigs,
multiple templates
sizes
Hawkeye 9 9 NA NA 7 Leverages AMOS,
automated detection of
mis-assemblies, large
assemblies, modular

57. Closing Remarks
• Software exist to allow manual editing of
assemblies
– Time consuming
– Different tools have different features
– Most fall over with assemblies > ~15Mbases or with
many contigs/scaffolds (10k-100k)

58. Closing Remarks
• Ideal Tool
– Contig/scaffold viewer capable of displaying
compressed/expanded mates, which contigs mates map
to when they are off contig/scaffold (like SeqMan Pro
and Hawkeye)

61. Closing Remarks
• Ideal Tool
– Contig/scaffold viewer capable of displaying
compressed/expanded mates, which contigs mates map
to when they are off contig/scaffold (like SeqMan Pro
and Hawkeye)
– Contig join editor for manual alignment and editing of
contigs (like Gap5)

62. Gap5 – Join Editor

63. Closing Remarks
• Ideal Tool
– Contig/scaffold viewer capable of displaying
compressed/expanded mates, which contigs mates map
to when they are off contig/scaffold (like SeqMan Pro
and Hawkeye)
– Contig join editor for manual alignment and editing of
contigs (like Gap5)
– Visualise clipped regions with consensus mismatches
(like Gap5)

64. Gap5 – Contig Editor

65. Closing Remarks
• Ideal Tool
– Contig/scaffold viewer capable of displaying
compressed/expanded mates, which contigs mates map
to when they are off contig/scaffold (like SeqMan Pro
and Hawkeye)
– Contig join editor for manual alignment and editing of
contigs (like Gap5)
– Visualise clipped regions with consensus mismatches
(like Gap5)
– Automated analysis of assembly to identify regions
requiring attention (like AMOSvalidate) and a way to
navigate to those regions for editing
– Minimise mouse-clicks and keyboard presses!!

67. Newbler Plant Genome Assemblies
• Pretty conservative in contig construction
• Seems to split out repetitive regions into their
own contigs pretty well
• Heterozygsity issues
– SNP alignment issues
– Indels break contigs
– Hidden in clipped regions
– Manual joining of neighbouring contigs can reduce
scaffolded contig numbers by 60-70%
– Many unscaffolded contigs have high sequence similarity
to scaffolded contigs – could collapse these and reduce
the number of unscaffolded contigs by 50%

68. Gap5 – Contig Editor