- AUTHOR - Pedro M. Gomez-Fabre
Bio::PopGen::HtSNP.pm- Select htSNP from a haplotype set
use Bio::PopGen::HtSNP; my $obj = Bio::PopGen::HtSNP->new($hap,$snp,$pop);
Select the minimal set of SNP that contains the full information about the haplotype without redundancies.
Take as input the followin values:
- - the haplotype block (array of array).
- - the snp id (array).
- - family information and frequency (array of array).
The final haplotype is generated in a numerical format and the SNP's sets can be retrieve from the module.
- If you force to include a family with indetermination, the SNP's with indetermination will be removed from the analysis, so consider before to place your data set what do you really want to do.
- If two families have the same information (identical haplotype), one of them will be removed and the removed files will be stored classify as removed.
- Only are accepted for calculation A, C, G, T and - (as deletion) and their combinations. Any other value as n or ? will be considered as degenerations due to lack of information.
On a haplotype set is expected that some of the SNP and their variations contribute in the same way to the haplotype. Eliminating redundancies will produce a minimal set of SNP's that can be used as input for a taging selection process. On the process SNP's with the same variation are clustered on the same group.
The idea is that because the tagging haplotype process is exponential. All redundant information we could eliminate on the tagging process will help to find a quick result.
my $obj = Bio::PopGen::HtSNP->new (-haplotype_block => \@haplotype_patterns, -snp_ids => \@snp_ids, -pattern_freq => \@pattern_name_and_freq);
where $hap, $snp and $pop are in the format:
my $hap = [ 'acgt', 'agtc', 'cgtc' ]; # haplotype patterns' id my $snp = [qw/s1 s2 s3 s4/]; # snps' Id's my $pop = [ [qw/ uno 0.20/], [qw/ dos 0.20/], [qw/ tres 0.15/], ]; # haplotype_pattern_id Frequency
See Below for more detailed summaries.
Let's begin with one general example of the code.
acgtcca-t cggtagtgc cccccgtgc cgctcgtgc
The first thing to to is to split the haplotype into characters.
a c g t c c a - t c g g t a g t g c c c c c c g t g c c g c t c g t g c
Now we have to convert the haplotype to Upercase. This will produce the same SNP if we have input a or A.
A C G T C C A - T C G G T A G T G C C C C C C G T G C C G C T C G T G C
The program admit as values any combination of ACTG and - (deletions). The haplotype is converted to number, considering the first variation as zero and the alternate value as 1 (see expanded description below).
0 0 0 0 0 0 0 0 0 1 1 0 0 1 1 1 1 1 1 0 1 1 0 1 1 1 1 1 1 1 0 0 1 1 1 1
Once we have the haplotype converted to numbers we have to generate the snp type information for the haplotype.
SNP code = SUM ( value * multiplicity ^ position );
where: SUM is the sum of the values for the SNP value is the SNP number code (0 [generally for the mayor allele], 1 [for the minor allele]. position is the position on the block.
For this example the code is:
0 0 0 0 0 0 0 0 0 1 1 0 0 1 1 1 1 1 1 0 1 1 0 1 1 1 1 1 1 1 0 0 1 1 1 1 ------------------------------------------------------------------ 14 10 12 4 2 14 14 14 14 14 = 0*2^0 + 1*2^1 + 1*2^2 + 1*2^3 12 = 0*2^0 + 1*2^1 + 0*2^2 + 1*2^3 ....
Once we have the families classify. We will take just the SNP's not redundant.
14 10 12 4 2
This information will be passed to the tag module is you want to tag the htSNP.
Whatever it happens to one SNPs of a class will happen to a SNP of the same class. Therefore you don't need to scan redundancies
This module is designed to work with fuzzy data. As the source of the haplotype is diverse. The program assume that some haplotypes can be generated using different values. If there is any indetermination (? or n) or any other degenerated value or invalid. The program will take away This SNP and will leave that for a further analysis.
On a complex situation:
a c g t ? c a c t a c g t ? c a - t c g ? t a g ? g c c a c t c g t g c c g c t c g t g c c g g t a g ? g c a c ? t ? c a c t
On this haplotype everything is happening. We have a multialelic variance. We have indeterminations. We have deletions and we have even one SNP which is not a real SNP.
The buiding process will be the same on this situation.
Convert the haplotype to uppercase.
A C G T ? C A C T A C G T ? C A - T C G ? T A G ? G C C A C T C G T G C C G C T C G T G C C G G T A G ? G C A C ? T ? C A C T
All columns that present indeterminations will be removed from the analysis on this Step.
hapotype after remove columns:
A C T C C T A C T C - T C G T G G C C A T G G C C G T G G C C G T G G C A C T C C T
All changes made on the haplotype matrix, will be also made on the SNP list.
snp_id_1 snp_id_2 snp_id_4 snp_id_6 snp_id_8 snp_id_9
now the SNP that is not one SNP will be removed from the analysis. SNP with Id snp_id_4 (the one with all T's).
because of the removing. Some of the families will become the same and will be clustered. A posteriori analysis will diference these families. but because of the indetermination can not be distinguish.
A C C C T A C C - T C G G G C C A G G C C G G G C C G G G C A C C C T
The result of the mergering will go like:
A C C C T A C C - T C G G G C C A G G C
Once again the changes made on the families and we merge the frequency (to be implemented)
Before to convert the haplotype into numbers we consider how many variations we have on the set. On this case the variations are 3.
The control code will use on this situation base three as mutiplicity
0 0 0 0 0 0 0 0 1 0 1 1 1 2 1 1 2 1 2 1 ----------------------------------- 36 63 36 75 36
And the minimal set for this combination is
0 0 0 0 0 1 1 1 2 1 2 2
NOTE: this second example is a remote example an on normal conditions. This conditions makes no sense, but as the haplotypes, can come from many sources we have to be ready for all kind of combinations.
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The rest of the documentation details each of the object methods. Internal methods are usually preceded with a _
Title : new Function: constructor of the class. Usage : $obj-> Bio::PopGen::HtSNP->new(-haplotype_block -snp_ids -pattern_freq) Returns : self hash Args : input haplotype (array of array) snp_ids (array) pop_freq (array of array) Status : public
Title : haplotype_block Usage : my $haplotype_block = $HtSNP->haplotype_block(); Function: Get the haplotype block for a haplotype tagging selection Returns : reference of array Args : reference of array with haplotype pattern
Title : snp_ids Usage : my $snp_ids = $HtSNP->$snp_ids(); Function: Get the ids for a haplotype tagging selection Returns : reference of array Args : reference of array with SNP ids
Title : pattern_freq Usage : my $pattern_freq = $HtSNP->pattern_freq(); Function: Get the pattern id and frequency for a haplotype tagging selection Returns : reference of array Args : reference of array with SNP ids
Title : _check_input Usage : _check_input($self) Function: check for errors on the input Returns : self hash Args : self Status : internal
Title : _haplotype_length_error Usage : _haplotype_length_error($self) Function: check if the haplotype length is the same that the one on the SNP id list. If not break and exit Returns : self hash Args : self Status : internal
Title : _population_error Usage : _population_error($self) Function: use input_block and pop_freq test if the number of elements match. If doesn't break and quit. Returns : self hash Args : self Status : internal
Title : _do_it Usage : _do_it($self) Function: Process the input generating the results. Returns : self hash Args : self Status : internal
Title : input_block Usage : $obj->input_block() Function: returns input block Returns : reference to array of array Args : none Status : public
Title : hap_length Usage : $obj->hap_length() Function: get numbers of SNP on the haplotype Returns : scalar Args : none Status : public
Title : pop_freq Usage : $obj->pop_freq() Function: returns population frequency Returns : reference to array Args : none Status : public
Title : deg_snp Usage : $obj->deg_snp() Function: returns snp_removes due to indetermination on their values Returns : reference to array Args : none Status : public
Title : snp_type Usage : $obj->snp_type() Function: returns hash with SNP type Returns : reference to hash Args : none Status : public
Title : silent_snp Usage : $obj->silent_snp() Function: some SNP's are silent (not contibuting to the haplotype) and are not considering for this analysis Returns : reference to a array Args : none Status : public
Title : useful_snp Usage : $obj->useful_snp() Function: returns list of SNP's that are can be used as htSNP. Some of them can produce the same information. But this is not considered here. Returns : reference to a array Args : none Status : public
Title : ht_type Usage : $obj->ht_type() Function: every useful SNP has a numeric code dependending of its value and position. For a better description see description of the module. Returns : reference to a array Args : none Status : public
Title : ht_set Usage : $obj->ht_set() Function: returns the minimal haplotype in numerical format. This haplotype contains the maximal information about the haplotype variations but with no redundancies. It's the minimal set that describes the haplotype. Returns : reference to an array of arrays Args : none Status : public
Title : snp_type_code Usage : $obj->snp_type_code() Function: returns the numeric code of the SNPs that need to be tagged that correspond to the SNP's considered in ht_set. Returns : reference to an array Args : none Status : public
Title : snp_and_code Usage : $obj->snp_and_code() Function: Returns the full list of SNP's and the code associate to them. If the SNP belongs to the group useful_snp it keep this code. If the SNP is silent the code is 0. And if the SNP is degenerated the code is -1. Returns : reference to an array of array Args : none Status : public
Title : deg_pattern Usage : $obj->deg_pattern() Function: Returns the a list with the degenerated haplotype. Sometimes due to degeneration some haplotypes looks the same and if we don't remove them it won't find any tag. Returns : reference to a hash of array Args : none Status : public
Title : split_hap Usage : $obj->split_hap() Function: simple representation of the haplotype base by base Same information that input haplotype but base based. Returns : reference to an array of array Args : none Status : public
Title : _split_haplo Usage : _split_haplo($self) Function: Take a haplotype and split it into bases Returns : self Args : none Status : internal
Title : _to_upper_case Usage : _to_upper_case() Function: make SNP or in-dels Upper case Returns : self Args : an AoA ref Status : private
Title : _remove_deg Usage : _remove_deg() Function: when have a indetermination or strange value this SNP is removed Returns : haplotype family set and degeneration list Args : ref to an AoA and a ref to an array Status : internal
Title : _rem_silent_snp Usage : _rem_silent_snp() Function: there is the remote possibilty that one SNP won't be a real SNP on this situation we have to remove this SNP, otherwise the program won't find any tag Returns : nonthing Args : ref to an AoA and a ref to an array Status : internal
Title : _find_silent_snps Usage : Function: list of snps that are not SNPs. All values for that SNPs on the set is the same one. Look stupid but can happend and if this happend you will not find any tag Returns : nothing Args : Status :
Title : _find_indet Usage : Function: find column (SNP) with invalid or degenerated values and store this values into the second parameter supplied. Returns : nothing Args : ref to AoA and ref to an array Status : internal
Title : _remove_col Usage : Function: remove columns contained on the second array from the first arr Returns : nothing Args : array of array reference and array reference Status : internal
Title : _remove_snp_id Usage : Function: remove columns contained on the second array from the first arr Returns : nothing Args : array of array reference and array reference Status : internal
Title : _find_deg_pattern Usage : Function: create a list with the degenerated patterns Returns : @array Args : a ref to AoA Status : public
Title : _keep_these_patterns Usage : Function: this is a basic approach, take a LoL and a list, keep just the columns included on the list Returns : nothing Args : an AoA and an array Status : public
Title : compare_arrays Usage : Function: take two arrays and compare their values Returns : 1 if the two values are the same 0 if the values are different Args : an AoA and an array Status : public
Title : _convert_to_numbers Usage : _convert_to_numbers() Function: tranform the haplotype into numbers. before to do that we have to consider the variation on the set. Returns : nonthing Args : ref to an AoA and a ref to an array Status : internal
Title : _snp_type_code Usage : Function: we have to create the snp type code for each version. The way the snp type is created is the following: we take the number value for every SNP and do the following calculation let be a SNP set as follow: 0 0 1 1 1 2 and multiplicity 3 on this case the situation is: sum (value * multiplicity ^ position) for each SNP 0 * 3 ^ 0 + 1 * 3 ^ 1 + 1 * 3 ^ 2 = 12 0 * 3 ^ 0 + 1 * 3 ^ 1 + 2 * 3 ^ 2 = 21 Returns : nothing Args : $self Status : private
Title : _alleles_number Usage : Function: calculate the max number of alleles for a haplotype and if the number. For each SNP the number is stored and the max number of alleles for a SNP on the set is returned Returns : max number of alleles (a scalar storing a number) Args : ref to AoA Status : public
Title : _htSNP Usage : _htSNP() Function: calculate the minimal set that contains all information of the haplotype. Returns : nonthing Args : ref to an AoA and a ref to an array Status : internal
Title : _snp_and_code_summary Usage : _snp_and_code_summary() Function: compile on a list all SNP and the code for each. This information can be also obtained combining snp_type and snp_type_code but on these results the information about the rest of SNP's are not compiled as table. 0 will be silent SNPs -1 are degenerated SNPs and the rest of positive values are the code for useful SNP Returns : nonthing Args : ref to an AoA and a ref to an array Status : internal