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Searching a Gene
Back to top 1. To search for a particular gene, enter the Gene Name or Gene Symbol at
the
Gene Finder page and click "Submit".
2. iHAP will query our local mirror of the UCSC genome browser
and return a list of chromosomal locations. Select your required chromosomal
location; this will bring you to iHAP's Job setup page.
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Setting up a job
Back to top 1. To set up a job based on your selected chromosomal location, first enter
your name, email and institute. In this page, explanations for the fields
can be found by moving the cursor over the help icon ( ).
After choosing all the required parameters for your job, click on the "Submit"
button at the bottom of the page.
2.Select the human population (HapMap)
for the polymorphism data.
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3. iHAP allows you to change the nucleotide positions to
include regions upstream and downstream of the gene.
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4. Select the maximum number of SNPs that a block can extend. This is a parameter
required for the HapBlock program.
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4. Select the cut-off value for allele frequency; SNPs with minor allele
frequency less than this value will be excluded from the analysis. This
is a parameter required for the HapBlock program.
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5. Choose the algorithm for haplotype block partitioning.
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- Minimize total number of tag SNPs
- Block Partition with a Fixed Genome Coverage (FGC) :
This algorithm requires an input for the parameter μ (0<μ<1);
the fraction of the genome covered by blocks.
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- Block Partition with a Fixed Number of Tag SNPs (FTSNP) :
This algorithm requires an input for the parameter m; the number of tag
SNPs that can be genotyped; m must be a positive integer.
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6. Choose the type of input data for the HapBlock program.
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- Genotype Data (unrelated individuals) - most likely haplotype
pairs identified from PL-EM :
The most-likely haplotype pairs identified from the PL-EM algorithm
will be used for block partitioning. Note that as the CEU and YRI poulations
contain pedigree (trios) genotype data, genotype data for these populations
belonging to the child of each trio will be filtered off to retain only
data from unrelated individuals.
- Genotype Data (unrelated individuals) - haplotypes and frequencies
from PL-EM :
The haplotypes and their frequencies estimated from the PL-EM algorithm
will be employed in block partitioning. Note that as the CEU and YRI poulations
contain pedigree (trios) genotype data, genotype data for these populations
belonging to the child of each trio will be filtered off to retain only
data from unrelated individuals.
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- Genotype data from general pedigrees :
This option assumes that there is no recombination within each block
and the haplotypes and their frequencies are inferred by logic-rules
and PL-EM
algorithm. Note that only the CEU and YRI populations contain pedigree
(trios) genotype data; by selecting this option, genotype data from all
trios within the population will be used for haplotype and block inference.
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7. Choose the method for block definitions.
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- Common haplotypes :
This method requires the input of 2 parameters. α is
the minimum percentage of all the observed haplotypes that a block
can
account
for and 0<α<1 with default value 0.8. β defines
the threshold of common haplotype, and 0<β<1 with
default value 0.05.
- LD measure D’ : This
method requires the input of 2 parameters. α is the minimum
percentage of all SNP pairs that the SNP pairs with strong D’ defined
in a block can account for and 0<α<1 with default value
0.95. β defines the threshold for strong D’, and 0<β<1 with
default value 0.8.
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- Four-Gamete test : This
method requires the input of a parameter β, which defines
the threshold for common haplotypes. However, mis-specified β will
result in unreasonable long blocks. Therefore, β should
be set to very small value or equal to 0, especially when using haplotype
data.
Default value is 0.01.
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8. Choose the method for tag SNP definitions.
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- Fraction of common haplotypes distinguished by tag SNPs :
This method requires the input of 2 parameters. α defines the fraction of distinguished common haplotypes by the tag SNPs and 0<α<1 with default value 0.8. This fraction must not be greater than the coverage of common haplotypes specified in the block definition. β defines threshold for common haplotype in tag SNP selection and 0<β<1 with default value 0.05. It must not be greater than the common haplotype threshold specified in the block definition.
- All common haplotypes : This method requires
the input of a parameter β, which defines threshold for
common haplotype in tag SNP selection and 0<β<1 with default
value 0.05.
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- Haplotype diversity : This
method requires the input of 2 parameters. α defines the fraction of haplotype diversity explained by tag SNPs and 0<α<1 with default value 0.9. β defines threshold for common haplotype and 0<β<1 with default value 0.05. β will not be used for tag SNPs calculation but for calculation of some statistics for a set of tag SNPs in the output.
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- Haplotype entropy : This
method requires the input of 2 parameters. α defines the fraction of haplotype entropy explained by tag SNPs and 0<α<1 with default value 0.8. β defines threshold for common haplotype and 0<β<1 with default value 0.05. β will not be used for tag SNPs calculation but for calculation of some statistics for a set of tag SNPs in the output.
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- Haplotype determination coefficient :
This method requires the input of 2 parameters. α defines the threshold for prediction power and 0<α<1 with default value 0.9. β defines threshold for common haplotype and 0<β<1 with default value 0.05.
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- LD measure r2 :
This method requires the input of 2 parameters. α defines the threshold for prediction power and 0<α<1 with default value 0.8. β defines threshold for common haplotype and 0<β<1 with default value 0.05. β will not be used for tag SNPs calculation but for calculation of some statistics for a set of tag SNPs in the output.
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- All common haplotypes (at most k missing SNPs
for each common haplotype) :
This method requires the input of 2 parameters. β defines threshold
for common haplotype and 0<β<1 with default value
0.05. k defines the maximum number of missing SNPs for each
common haplotypes and k > 0 with default value of 2.
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- Minimum number of blocks :
By selecting this option, the number of tag SNPs is always set to 1,
resulting in minimum number of blocks.
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8. Select the number of permutation tests for
the HapBlock program.
By default, no permutation test is performed. Note that the more permutation
tests you perform, the longer the job will take.
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Results
You can download the output text files from HapBlock at the bottom of
the page. The result files will be kept on the server for 24 hours. 1. Job Summary : In the results page, the summary
of the HapBlock job is displayed for your reference.
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2. Block Overview : In the results page,
the block overview gives a graphical representation of blocks in the selected
chromosomal location. The SNPs are marked by blue vertical bars ( )
and tag SNPs are represented by inverted triangles ( ).
Haplotype blocks are represented as yellow boxes. Introns are represented
as grey boxes ( )
and genetic loci are marked belows the main axis with their gene symbols
(eg. ).
Clicking on the SNP () or
tag SNP () icons
will bring you to their respective entries in the HapMap site.
Clicking on the introns () or
the gene symbols (eg.) will
bring you to their respective entries in the UCSC
genome browser.
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3. Detailed Block Definitions : In the results
page, the detailed block definitions gives a detailed graphical listing of
the haplotype patterns and their haplotype frequencies within each block.
Haplotype blocks are represented as yellow boxes tag SNPs are represented
by inverted triangles ().
Each of the SNP IDs are shown above the SNP nucleotides. Clicking on the
tag SNP () icons
will bring you to their respective entries in the HapMap site.
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