Download Lec-GenomeAllignment2010

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts

Tag SNP wikipedia , lookup

Short interspersed nuclear elements (SINEs) wikipedia , lookup

Genomic imprinting wikipedia , lookup

Zinc finger nuclease wikipedia , lookup

Genetic engineering wikipedia , lookup

RNA-Seq wikipedia , lookup

Gene desert wikipedia , lookup

Adeno-associated virus wikipedia , lookup

DNA virus wikipedia , lookup

Gene wikipedia , lookup

Polyploid wikipedia , lookup

Designer baby wikipedia , lookup

Human genetic variation wikipedia , lookup

Copy-number variation wikipedia , lookup

Oncogenomics wikipedia , lookup

Artificial gene synthesis wikipedia , lookup

Mitochondrial DNA wikipedia , lookup

History of genetic engineering wikipedia , lookup

Genome (book) wikipedia , lookup

Segmental Duplication on the Human Y Chromosome wikipedia , lookup

Metagenomics wikipedia , lookup

Transposable element wikipedia , lookup

No-SCAR (Scarless Cas9 Assisted Recombineering) Genome Editing wikipedia , lookup

Public health genomics wikipedia , lookup

Site-specific recombinase technology wikipedia , lookup

NUMT wikipedia , lookup

Non-coding DNA wikipedia , lookup

ENCODE wikipedia , lookup

Smith–Waterman algorithm wikipedia , lookup

Pathogenomics wikipedia , lookup

Helitron (biology) wikipedia , lookup

Sequence alignment wikipedia , lookup

Human genome wikipedia , lookup

Genomic library wikipedia , lookup

Minimal genome wikipedia , lookup

Genomics wikipedia , lookup

Whole genome sequencing wikipedia , lookup

Genome editing wikipedia , lookup

Multiple sequence alignment wikipedia , lookup

Human Genome Project wikipedia , lookup

Genome evolution wikipedia , lookup

Transcript
Genome Alignment
Alignment Methods
• Needleman-Wunsch (global) and SmithWaterman (local) use dynamic programming
• Guaranteed to find an optimal alignment
given a particular scoring function
• Too computationally intensive for genome
alignment, especially multiple genomes
Genome Alignment
• Depending on level of similarity, genome
alignments may need to contend with
rearrangements and large-scale duplications
and deletions
• Draft or partial genomes can both benefit
from and confound alignment
• Need to visualize results in summary form
Genome Alignment
• Pair-wise
– Align two genomes
– Example: MUMmer
• Multiple or complex samples and a reference genome
– All of one genome plus whatever parts match from the other
genome(s)
– Example: PIPs
• Multiple alignment
– All of all the genomes
– Example: Mauve
Some aligners
http://mummer.sourceforge.net/
http://www.ebi.ac.uk/~bjp/pecan/
http://asap.ahabs.wisc.edu/mauve/index.php
MUMmer
Pecan
Mauve
MUMmer (Maximal Unique Match)
http://mummer.sourceforge.net/
• Fast pair-wise comparison of draft or
complete genomes using nucleotide or 6frame translated sequences
• MUMmer 3.0 can find all 20-basepair or
longer exact matches between a pair of 5megabase genomes in 13.7 seconds, using
78 MB of memory, on a 2.4 GHz Linux
desktop computer
Suffix Tree
Delcher et al. Fast algorithms for large-scale genome alignment and
comparison. Nucleic Acids Res. 2002 Jun 1;30(11):2478-83.
Genome 2
MUMMER plot
Genome 1
5 Campylobacter
PROmer analysis
Fouts et al. Major structural differences and novel
potential virulence mechanisms from the genomes of
multiple campylobacter species. PLoS Biol. 2005
Jan;3(1):e15.
• One genome is used as the x-axis
for all four pair-wise comparisons
• X-shape characteristic of
collinearity interrupted by inversions
around the origin or terminus of
replication
• Loss of collinearity in more distant
comparisons
Human Gut
metagenome
Percent Identity Plot (PIP)
of random shotgun reads
to a complete
Bifidobacterium genome
and a good quality draft
Methanobrevibacter
genome
Gill et al. Metagenomic
analysis of the human distal
gut microbiome. Science.
2006 Jun 2; 312(5778):
1355-9.
Mauve Multiple Genome Aligner
• Able to identify and align collinear
regions of multiple genomes even in
the presence of rearrangements
• Find and extend seed matches
• Group into locally collinear blocks
• Align intervening regions
Darling et al. Genome Res. 2004
Jul;14(7):1394-403.
Progressive Mauve alignment
of 12 E. coli genome
Aaron Darling
2006 Ph.D. thesis,
http://gel.ahabs.wisc.edu/~darling/
darling_thesis.pdf
Figure 1. The difference between positional
homology alignment and glocal alignment.
Three example linear genomes are broken into
genes labeled A,B,C,D, and R. R is a multicopy (repetitive) gene, with different copies
labeled using numeric subscripts. Each copy of
R is assumed to be identical in sequence, so
that orthology/paralogy is unknowable from
nucleotide substitution (as is often the case with
mobile DNA repeat elements). Genes shifted
downward in a given genome are inverted
(reverse complement) relative to the reference
genome. The positional homology alignment
would ideally create two local alignment blocks
where each block has exactly one alignment
row for each genome. Only positionallyconserved copies of the repetitive gene family
R become aligned to each other. The glocal
alignment would ideally create four local
alignment blocks wherein all copies of the
repetitive gene family become aligned to each
other.
Progressive Genome
Alignment similar to
CLUSTAL (next week)
with integrated synteny
mapping and positional
homology
and anchored alignment
Performance Metrics
Accuracy – Proportion correct
TN+TP/total
TPR (Recall) – Proportion of
predicted positives that are correct
actual \
predicted
negative
positive
TN
FP
FN
TP
TP/FP+TP
Negative
Sensitivity – Proportion of positives
correctly predicted
TP/FN+TP
Specificity – Proportion of negatives
correctly predicted
TN/TN+FP
Positive
For nucleotide pairs, a
TP is a pair aligned in
both the calculated and
correct alignments. A FP
is a nucleotide pair in
the calculated alignment
that is absent from the
correct alignment.
Likewise, a FN is a pair
in the correct alignment
not present in the
calculated alignment.
Sensitivity
Positive Predictive Value (PPV)
We do not quantify True
Negative (TN)
alignments as the
number of TN
possibilities is extremely
large, growing with the
product of sequence
lengths.
ENCODE project
• Goal = to identify all functional elements
in the human genome
• Margulies et al. 2007 reports results of
the pilot project to analyze 1% of the
genome using genome alignment to
detect which regions of the sequence
are evolutionarily constrained.
• 4 aligners
–
–
–
–
MAVID
MLAGAN
TBA
PECAN
• 23 mammalian
species
• 30 Mb; 44
regions
Alignment Breakpoints
Alignment Coverage
•
•
•
•
•
For example, vs. armadillo:
MAVID
27.4%
MLAGAN
42.4%
TBA
41.2%
PECAN
40.1%
• 17.4% covered by all 4 aligners
• Of which 66.1% are aligned identically
Performance Metrics
• Sensitivity –
• coverage of protein coding regions and
ancestral repeats
• Specificity –
• primate specific repeats (Alu) and periodicity
of substitutions in protein coding regions