Difference between revisions of "Mapping SNPs HEXA"

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(Mutations annotated only in SNP-DB)
(Mutations annotated only in SNP-DB)
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'''Graphical representation:'''<br>
 
'''Graphical representation:'''<br>
The following visualisation displays the corresponding mutations which are only in DBSNP and non-silent. Therefore there is of course no silent mutation marked while some wrong annotated amino acids exist.
+
The following visualisation displays the corresponding mutations which are only in DBSNP and non-silent. Therefore there is of course no silent mutation marked while some wrong annotated amino acids exist. <br><br>
<br>
 
   
 
MTSSRLWFSLLLAAAFAGRATALWPWPQ<font color=red>N</font>FQTSDQRYVLYPNNFQFQYDVSSAAQPGCSVLD<br> MTSSRLWFSLLLAAAFAGRATALWPWPQ<font color=red>S</font>FQTSDQRYVLYPNNFQFQYDVSSAAQPGCSVLD<br> <br> <br> EAFQRYRDLLFGSGSWPRPYLTGKRHTLEKNVLVVSVVTPGCNQLPTLESVENYTLTINDD<br> EAFQRYRDLLFGSGSWPRPYLTGKRHTLEKNVLVVSVVTPGCNQLPTLESVENYTLTINDD<br> <br> <br> QCLLLSETVWGALRGLETFSQLVWKSAEGTFFINKTEIEDFPRFPHRGLLLDTSR<font color=red>H</font>YLPLS<br> QCLLLSETVWGALRGLETFSQLVWKSAEGTFFINKTEIEDFPRFPHRGLLLDTSR<font color=red>D</font>YLPLS<br> <br> <br> SILDTLDVMAYNKLNVFHWHLVD<font color=blue>D</font>PSFPYESFTFPELMRKGSYNPVTHIYTAQDVKEVIEY<br> SILDTLDVMAYNKLNVFHWHLVD<font color=blue>D</font>PSFPYESFTFPELMRKGSYNPVTHIYTAQDVKEVIEY<br> <br> <br> AR<font color=red>L</font>RGIRVLAEFDTPGHTLSWGPGIPGLLTPCYSGSEPSGTFGPVNP<font color=red>S</font>LNNTYEFMSTFFL<br> AR<font color=red>F</font>RGIRVLAEFDTPGHTLSWGPGIPGLLTPCYSGSEPSGTFGPVNP<font color=red>I</font>LNNTYEFMSTFFL<br> <br> <br> EVSSVFPDFYLHLGGDEVDFTCWKSNPEIQDFMRKKGFGEDFKQLESFYIQTLLDIVSSYG<br> EVSSVFPDFYLHLGGDEVDFTCWKSNPEIQDFMRKKGFGEDFKQLESFYIQTLLDIVSSYG<br> <br> <br> KGYVVWQEVFDNKVKIQPDTIIQVWREDIPV<font color=red>N</font>YMKELELVTKAGFRALLSAPWYLNRISYG<br> KGYVVWQEVFDNKVKIQPDTIIQVWREDIPV<font color=red>D</font>YMKELELVTKAGFRALLSAPWYLNRISYG<br> <br> <br> PDWKDFY<font color=red>I</font>VEPLAFEGTPEQKALVIGG<font color=blue>E</font>ACMWGEYVDNTNLVPRLWPRAGAVAERLWSNKL<br> PDWKDFY<font color=red>V</font>VEPLAFEGTPEQKALVIGG<font color=blue>S</font>ACMWGEYVDNTNLVPRLWPRAGAVAERLWSNKL<br> <br> <br> TSDLTFAYERLSHFRCELLRRGVQAQPLNVGFCEQEFEQT
 
MTSSRLWFSLLLAAAFAGRATALWPWPQ<font color=red>N</font>FQTSDQRYVLYPNNFQFQYDVSSAAQPGCSVLD<br> MTSSRLWFSLLLAAAFAGRATALWPWPQ<font color=red>S</font>FQTSDQRYVLYPNNFQFQYDVSSAAQPGCSVLD<br> <br> <br> EAFQRYRDLLFGSGSWPRPYLTGKRHTLEKNVLVVSVVTPGCNQLPTLESVENYTLTINDD<br> EAFQRYRDLLFGSGSWPRPYLTGKRHTLEKNVLVVSVVTPGCNQLPTLESVENYTLTINDD<br> <br> <br> QCLLLSETVWGALRGLETFSQLVWKSAEGTFFINKTEIEDFPRFPHRGLLLDTSR<font color=red>H</font>YLPLS<br> QCLLLSETVWGALRGLETFSQLVWKSAEGTFFINKTEIEDFPRFPHRGLLLDTSR<font color=red>D</font>YLPLS<br> <br> <br> SILDTLDVMAYNKLNVFHWHLVD<font color=blue>D</font>PSFPYESFTFPELMRKGSYNPVTHIYTAQDVKEVIEY<br> SILDTLDVMAYNKLNVFHWHLVD<font color=blue>D</font>PSFPYESFTFPELMRKGSYNPVTHIYTAQDVKEVIEY<br> <br> <br> AR<font color=red>L</font>RGIRVLAEFDTPGHTLSWGPGIPGLLTPCYSGSEPSGTFGPVNP<font color=red>S</font>LNNTYEFMSTFFL<br> AR<font color=red>F</font>RGIRVLAEFDTPGHTLSWGPGIPGLLTPCYSGSEPSGTFGPVNP<font color=red>I</font>LNNTYEFMSTFFL<br> <br> <br> EVSSVFPDFYLHLGGDEVDFTCWKSNPEIQDFMRKKGFGEDFKQLESFYIQTLLDIVSSYG<br> EVSSVFPDFYLHLGGDEVDFTCWKSNPEIQDFMRKKGFGEDFKQLESFYIQTLLDIVSSYG<br> <br> <br> KGYVVWQEVFDNKVKIQPDTIIQVWREDIPV<font color=red>N</font>YMKELELVTKAGFRALLSAPWYLNRISYG<br> KGYVVWQEVFDNKVKIQPDTIIQVWREDIPV<font color=red>D</font>YMKELELVTKAGFRALLSAPWYLNRISYG<br> <br> <br> PDWKDFY<font color=red>I</font>VEPLAFEGTPEQKALVIGG<font color=blue>E</font>ACMWGEYVDNTNLVPRLWPRAGAVAERLWSNKL<br> PDWKDFY<font color=red>V</font>VEPLAFEGTPEQKALVIGG<font color=blue>S</font>ACMWGEYVDNTNLVPRLWPRAGAVAERLWSNKL<br> <br> <br> TSDLTFAYERLSHFRCELLRRGVQAQPLNVGFCEQEFEQT

Revision as of 11:40, 18 June 2011

Methods

First of all, we had to parse the HGMD database and the DB-SNP database.

HGMD

We logged us in and searched for Tay-Sachs diseases and chose one entry of HEXA. In our case there were two entries with identical content. We only looked at the missense/nonsense mutations, which are 68 annotated in HGMD. We just copied the webpage in a textfile and than wrote a short parser, which parse the codon change, amino acid change and codon number.

DBSNP

It was more complicated to parse the DBSNP output, than the output of HGMD. First of all, we search for HEXA in this database and chose only the SNPs which occur in human. We used the grapical output and again copied and pasted the page in a textfile. An entry in DBSNP has following structure: First of all there is the name of the SNP. Next the sequence and the graphical representation of the sequence. In the next line, there are the allel origin, the clinical relevance and last the annotations of the mutation. TBA...

Comparison of mutations in HGMD and DBSNP

For the comparison of the mutations in HGMD and DBSNP we made table with some importent informations. First of all we extraced the DBSNP-id which makes it easy to look after this SNP if necessary. Next we looked up the codonposition which displays where the mutation takes place in the sequence. Furthermore we also extraced the mutation position which corresponds to the position in the triplet where the mutation takes place. The next two entries displays the mutations for the amino acids and codon which means it shows detailed which amino acid is replaced by another and how the codon is changed. Afterwards we create descriptive representation for the mutation by showing the sequence and coloring the correspondig kind of mutation. Following tables and descriptive visualisations are for different cases which are described below. Furthermore a detailed summary of the different cases and a comparision of them can be seen below at 'statistical comparison of HGMD and DBSNP'.

Mutations annotated in both databases

First of all we compared the mutations which are annotated in both databases. These mutations are not silent and cause all a certain phenotype. The reason therefore is that HGMD contains no silent mutations. Here we found 33 annotated mutations where some them take place in different mutationpositions in the triplet. Besides, in some case two different named mutation take places at the same codon position.

SNP-DB Identifier Codonposition Mutationposition Amino Acids Codons
rs121907964 26 3 Trp -> TER TGGc -> TGA
rs121907979 39 2 Leu -> Arg CTT -> CGT
rs121907975 127 1 Leu -> Phe aCTC -> TTC
2 Leu -> Arg CTC -> CGC
rs121907962 137 1 Arg -> TER cCGA -> TGA
rs121907972 170 1 Arg -> Trp cCGG -> TGG
rs121907957 2 Arg -> Gln CGG -> CAG
 rs28941770 178 2 Arg -> His CGC -> CAC
2 Arg -> Leu CGC -> CTC
rs121907953 1 Arg -> Cys tCGC -> TGC
rs121907969 180 3 Tyr -> TER TACc -> TAG
rs28941771 1 Tyr -> His tTAC -> CAC
rs121907973 197 2 Lys -> Thr AAA -> ACA
rs1800429 200 1 Val -> Met cGTG -> ATG
rs121907976 204 2 His -> Arg CAT -> CGT
rs121907961 210 2 Ser -> Phe TCC -> TTC
rs121907974 211 2 Phe -> Ser TTC -> TCC
rs121907970 247 1 Arg -> Trp aCGG -> TGG
rs121907959 250 1 Gly -> Ser gGGT -> AGT
2 Gly -> Asp GGT -> GAT
2 Gly -> Val GGT -> GTT
rs121907971 258 1 Asp -> His tGAC -> CAC
rs121907954 269 1 Gly -> Ser aGGT -> AGT
2 Gly -> Asp GGT -> GAT
rs121907977 301 2 Met -> Arg ATG -> AGG
rs121907967 329 2 Trp -> TER TGG -> TAG
rs121907963 393 1 Arg -> TER gCGA -> TGA
 rs121907958 420 3 Trp -> Cys TGGt -> TGC
3 Trp -> Cys TGGt -> TGT
rs28940871 451 1 Leu -> Val tCTG -> GTG
 rs121907978 454 2 Gly -> Asp GGT -> GAT
1 Gly -> Ser tGGT -> AGT
rs121907981 474 3 Trp -> Cys TGGc -> TGC
rs121907952 482 1 Glu -> Lys cGAA -> AAA
rs121907968 485 1 Trp -> Arg gTGG -> CGG
rs121907966 499 1 Arg -> Cys aCGT -> TGT
rs121907956 2 Arg -> His CGT -> CAT
rs28942071 504 1 Arg -> Cys cCGC -> TGC
rs121907955 2 Arg -> His CGC -> CAC
 rs4777502  506 3 Glu -> Asp GAA -> GAC
3 Glu -> Asp GAA -> GAT


Graphical representation:
The graphical representation shows at which position a certain mutation takes places. In this case onla non-silent mutations are marked. The reason is that in HGMD only non-silent mutations are annotated and therefore the results which agree in both databases are also non-silent. Furthermore there are no amino acids which are wrong annotated.

 MTSSRLWFSLLLAAAFAGRATALWPWPQNFQTSDQRYVLYPNNFQFQYDVSSAAQPGCSVLD
MTSSRLWFSLLLAAAFAGRATALWP!PQNFQTSDQRYVRYPNNFQFQYDVSSAAQPGCSVLD


EAFQRYRDLLFGSGSWPRPYLTGKRHTLEKNVLVVSVVTPGCNQLPTLESVENYTLTINDD
EAFQRYRDLLFGSGSWPRPYLTGKRHTLEKNVLVVSVVTPGCNQLPTLESVENYTLTINDD


QCLLLSETVWGALRGLETFSQLVWKSAEGTFFINKTEIEDFPRFPHRGLLLDTSRHYLPLS
QCLFLSETVWGAL!GLETFSQLVWKSAEGTFFINKTEIEDFPRFPHWGLLLDTSHH!LPLS


SILDTLDVMAYNKLNVFHWHLVDDPSFPYESFTFPELMRKGSYNPVTHIYTAQDVKEVIEY
SILDTLDVMAYNTLNMFHWRLVDDPFSPYESFTFPELMRKGSYNPVTHIYTAQDVKEVIEY


ARLRGIRVLAEFDTPGHTLSWGPGIPGLLTPCYSGSEPSGTFGPVNPSLNNTYEFMSTFFL
AWLRSIRVLAEFHTPGHTLSWGPSIPGLLTPCYSGSEPSGTFGPVNPSLNNTYEFRSTFFL


EVSSVFPDFYLHLGGDEVDFTCWKSNPEIQDFMRKKGFGEDFKQLESFYIQTLLDIVSSYG
EVSSVFPDFYLHLGGDEVDFTC!KSNPEIQDFMRKKGFGEDFKQLESFYIQTLLDIVSSYG


KGYVVWQEVFDNKVKIQPDTIIQVWREDIPVNYMKELELVTKAGFRALLSAPWYLNRISYG
KGYVVWQEVFDNKVKIQPDTIIQVW!EDIPVNYMKELELVTKAGFRALLSAPCYLNRISYG


PDWKDFYIVEPLAFEGTPEQKALVIGGEACMWGEYVDNTNLVPRLWPRAGAVAERLWSNKL
PDWKDFYIVEPLAFEGTPEQKAVVIDGEACMWGEYVDNTNLVPRLCPRAGAVAKRLRSNKL


TSDLTFAYERLSHFRCELLRRGVQAQPLNVGFCEQEFEQT TSDLTFAYECLSHFCCDLLRRGVQAQPLNVGFCEQEFEQT Non-silent mutation Silent mutation Wrong AA in mutation annotation


Mutations annotated only in HGMD

We also looked for mutations which are annotated only in HGMD, but we had not found any of them.

Mutations annotated only in SNP-DB

Here we listed all mutations which are annotated only in the DBSNP and which are not silent. Some of these mutations have a high detailed NP annotation while others are not as detailed annotated. Therefore we had to map these mutations. The detailed list of the mutations, which we mapped can be found [here]. Finally, 8 non-silent mutations could be found which have only one possible mutationposition and codonposition.

SNP-DB Identifier Codonposition Mutationposition Amino Acids Codons
rs4777505 29 2 Asn -> Ser AAC -> AGC
rs61731240 179 1 His -> Asp CAT -> GAT
rs3743230 208 1 Asn -> Asp AAC -> GAC
rs61747114 248 1 Leu -> Phe CTT -> TTT
rs1054374 293 2 Ser -> Ile AGT -> ATT
rs1800430 399 1 Asn -> Asp AAC -> GAC
rs1800431 436 1 Ile -> Val ATA -> GTA
rs121907982 456 2 Tyr -> Ser TAT -> TCT


Graphical representation:
The following visualisation displays the corresponding mutations which are only in DBSNP and non-silent. Therefore there is of course no silent mutation marked while some wrong annotated amino acids exist.

 MTSSRLWFSLLLAAAFAGRATALWPWPQNFQTSDQRYVLYPNNFQFQYDVSSAAQPGCSVLD
MTSSRLWFSLLLAAAFAGRATALWPWPQSFQTSDQRYVLYPNNFQFQYDVSSAAQPGCSVLD


EAFQRYRDLLFGSGSWPRPYLTGKRHTLEKNVLVVSVVTPGCNQLPTLESVENYTLTINDD
EAFQRYRDLLFGSGSWPRPYLTGKRHTLEKNVLVVSVVTPGCNQLPTLESVENYTLTINDD


QCLLLSETVWGALRGLETFSQLVWKSAEGTFFINKTEIEDFPRFPHRGLLLDTSRHYLPLS
QCLLLSETVWGALRGLETFSQLVWKSAEGTFFINKTEIEDFPRFPHRGLLLDTSRDYLPLS


SILDTLDVMAYNKLNVFHWHLVDDPSFPYESFTFPELMRKGSYNPVTHIYTAQDVKEVIEY
SILDTLDVMAYNKLNVFHWHLVDDPSFPYESFTFPELMRKGSYNPVTHIYTAQDVKEVIEY


ARLRGIRVLAEFDTPGHTLSWGPGIPGLLTPCYSGSEPSGTFGPVNPSLNNTYEFMSTFFL
ARFRGIRVLAEFDTPGHTLSWGPGIPGLLTPCYSGSEPSGTFGPVNPILNNTYEFMSTFFL


EVSSVFPDFYLHLGGDEVDFTCWKSNPEIQDFMRKKGFGEDFKQLESFYIQTLLDIVSSYG
EVSSVFPDFYLHLGGDEVDFTCWKSNPEIQDFMRKKGFGEDFKQLESFYIQTLLDIVSSYG


KGYVVWQEVFDNKVKIQPDTIIQVWREDIPVNYMKELELVTKAGFRALLSAPWYLNRISYG
KGYVVWQEVFDNKVKIQPDTIIQVWREDIPVDYMKELELVTKAGFRALLSAPWYLNRISYG


PDWKDFYIVEPLAFEGTPEQKALVIGGEACMWGEYVDNTNLVPRLWPRAGAVAERLWSNKL
PDWKDFYVVEPLAFEGTPEQKALVIGGSACMWGEYVDNTNLVPRLWPRAGAVAERLWSNKL


TSDLTFAYERLSHFRCELLRRGVQAQPLNVGFCEQEFEQT TSDLTFAYERLSHFRCELLRRGVQAQPLNVGFCEQEFEQT Non-silent mutation Silent mutation Wrong AA in mutation annotation

Silent Mutations

Because this mutations are not annotated in the HGMD database, the mutations have to be silent and do not lead to a phenotype.
This mutations are badly annotated in the SNP-DB. Therefore we rotated the found codons, because the original codon has to code for the amino acid which occur in the protein sequence. Therefore we used the codon with the mutation at position one, position two and position three. Next we also reverse it and made the complemetary sequence of both. The detailed result can be seen [here]

If we found more than one nucleotide combination which code for the amino acid in the protein sequence, we list all of them in the following table, if they are silent mutations. Otherwise, we also listed all mutations which are not silent, if there do not exist any other possible mutation for this postition.

Here is the result, which combinations are possible:

SPN-DB Identifier Codonposition Mutationposition Amino Acids Codons translation
rs1800428 3 3 Ser -> Ser AGC -> AGT Forward
rs11551324 109 3 Thr -> Thr ACC -> ACT forward
rs28942072  324 3 Val -> Val GTT -> GGA Forward
rs28942072 Val -> Val GTC -> GTT Forward
rs34085965 446 1 Pro -> Pro CCT -> CCC complemantry reverse
rs4777502 506 3 Glu -> Glu GAG -> GAA Forward

Graphical representation:

 MTSSRLWFSLLLAAAFAGRATALWPWPQNFQTSDQRYVLYPNNFQFQYDVSSAAQPGCSVLD
MTSSRLWFSLLLAAAFAGRATALWPWPQNFQTSDQRYVLYPNNFQFQYDVSSAAQPGCSVLD


EAFQRYRDLLFGSGSWPRPYLTGKRHTLEKNVLVVSVVTPGCNQLPTLESVENYTLTINDD
EAFQRYRDLLFGSGSWPRPYLTGKRHTLEKNVLVVSVVTPGCNQLPTLESVENYTLTINDD


QCLLLSETVWGALRGLETFSQLVWKSAEGTFFINKTEIEDFPRFPHRGLLLDTSRHYLPLS
QCLLLSETVWGALRGLETFSQLVWKSAEGTFFINKTEIEDFPRFPHRGLLLDTSRHYLPLS


SILDTLDVMAYNKLNVFHWHLVDDPSFPYESFTFPELMRKGSYNPVTHIYTAQDVKEVIEY
SILDTLDVMAYNKLNVFHWHLVDDPSFPYESFTFPELMRKGSYNPVTHIYTAQDVKEVIEY


ARLRGIRVLAEFDTPGHTLSWGPGIPGLLTPCYSGSEPSGTFGPVNPSLNNTYEFMSTFFL
ARLRGIRVLAEFDTPGHTLSWGPGIPGLLTPCYSGSEPSGTFGPVNPSLNNTYEFMSTFFL


EVSSVFPDFYLHLGGDEVDFTCWKSNPEIQDFMRKKGFGEDFKQLESFYIQTLLDIVSSYG
EVSSVFPDFYLHLGGDEVDFTCWKSNPEIQDFMRKKGFGEDFKQLESFYIQTLLDIVSSYG


KGYVVWQEVFDNKVKIQPDTIIQVWREDIPVNYMKELELVTKAGFRALLSAPWYLNRISYG
KGYVVWQEVFDNKVKIQPDTIIQVWREDIPVNYMKELELVTKAGFRALLSAPWYLNRISYG


PDWKDFYIVEPLAFEGTPEQKALVIGGEACMWGEYVDNTNLVPRLWPRAGAVAERLWSNKL
PDWKDFYIVEPLAFEGTPEQKALVIGGEACMWGEYVDNTNLVPRLWPRAGAVAERLWSNKL


TSDLTFAYERLSHFRCELLRRGVQAQPLNVGFCEQEFEQT TSDLTFAYERLSHFRCELLRRGVQAQPLNVGFCEQEFEQT Non-silent mutation Silent mutation Wrong AA in mutation annotation

Summary

Graphical representation:

Here we combined all graphical representations of the different cases. This means this visualisation displays all possible mutations which are found in HGMD and DBSNP. Therefore we can see non-silent mutations as well as silent mutations. Furthermore the wrong annotated amino acids are marked as well.

 MTSSRLWFSLLLAAAFAGRATALWPWPQNFQTSDQRYVLYPNNFQFQYDVSSAAQPGCSVLD
MTSSRLWFSLLLAAAFAGRATALWP!PQSFQTSDQRYVRYPNNFQFQYDVSSAAQPGCSVLD


EAFQRYRDLLFGSGSWPRPYLTGKRHTLEKNVLVVSVVTPGCNQLPTLESVENYTLTINDD
EAFQRYRDLLFGSGSWPRPYLTGKRHTLEKNVLVVSVVTPGCNQLPTLESVENYTLTINDD


QCLLLSETVWGALRGLETFSQLVWKSAEGTFFINKTEIEDFPRFPHRGLLLDTSRHYLPLS
QCLFLSETVWGAL!GLETFSQLVWKSAEGTFFINKTEIEDFPRFPHWGLLLDTSHD!LPLS


SILDTLDVMAYNKLNVFHWHLVDDPSFPYESFTFPELMRKGSYNPVTHIYTAQDVKEVIEY
SILDTLDVMAYNTLNMFHWRLVDDPFSPYESFTFPELMRKGSYNPVTHIYTAQDVKEVIEY


ARLRGIRVLAEFDTPGHTLSWGPGIPGLLTPCYSGSEPSGTFGPVNPSLNNTYEFMSTFFL
AWFRSIRVLAEFHTPGHTLSWGPSIPGLLTPCYSGSEPSGTFGPVNPILNNTYEFRSTFFL


EVSSVFPDFYLHLGGDEVDFTCWKSNPEIQDFMRKKGFGEDFKQLESFYIQTLLDIVSSYG
EVSSVFPDFYLHLGGDEVDFTC!KSNPEIQDFMRKKGFGEDFKQLESFYIQTLLDIVSSYG


KGYVVWQEVFDNKVKIQPDTIIQVWREDIPVNYMKELELVTKAGFRALLSAPWYLNRISYG
KGYVVWQEVFDNKVKIQPDTIIQVW!EDIPVDYMKELELVTKAGFRALLSAPCYLNRISYG


PDWKDFYIVEPLAFEGTPEQKALVIGGEACMWGEYVDNTNLVPRLWPRAGAVAERLWSNKL
PDWKDFYVVEPLAFEGTPEQKAVVIDGSACMWGEYVDNTNLVPRLCPRAGAVAKRLRSNKL


TSDLTFAYERLSHFRCELLRRGVQAQPLNVGFCEQEFEQT TSDLTFAYECLSHFCCELLRRGVQAQPLNVGFCEQEFEQT Non-silent mutation Silent mutation Wrong AA in mutation annotation

Statistical comparison of HGMD and DBSNP

For the analysis of the two different database results we decided to do some statistical comparison.

First of all we compared the different resulting tables (see above) according to their mutationposition in the triplet. Therefore we created a barplot which shows the precentage of the frequency for the corresponding mutationposition.

For the first case where the overlapping results of both databases. One can see here that there are as much mutations at the first postion as at the second position. The occurance of a mutation on the third position deviates from the others which means it is much rarer. The reason for this ist that the database HGMD contains no silent mutations which means that the overlap of both databases do not contain them as well. The third position of a triplet often causes a silent mutation and there for only a few mutations on the third position result in an amino acid change. Therefore this explains why the third position is as rare while the other positions are equal frequent.

The second case displays the position frequency of the corresponding mutations which are only resulting in DBSNP. Here one can see that mutations at position one are more frequent than at position two and that there are no mutations at position three. The resulting mutations only for DBSNP are not silent which can explain why there is no mutation at position three: mutations at the third position of a triplet are very often silent. Besides there is probably no special reason why the first position is more common than the second one for a mutation.

The third case shows the resulting silent mutations of DBSNP. Here the most frequent mutation position is the third one while the other ones are same common. This is the opposite behaviour comparing to the other cases and has similar explantion: mutations at the third position of a triplet often result in a silent mutation where contrary silent mutations at the other position are very rare.

The last case represents the total distribution of the mutationpositions. Here the first position is the most common for a mutation followed by the second position which is almost same common. The third position is the least frequent one. This is the expected result corresponding to the other three cases: the first and the second position are almost always the most frequent ones and the third the rarest. In the third case there is an exception which is the reason why the difference is not so high in the total distribution.

In summary, the barplot of the different tables/cases correspond to the expectation and can be all explained logically.

Figure 1: Barplot of the mutationposition for the different tables

As a next step we looked up which amino acid mutates most often for each table. Therefore we create a barplot where the frequency for a mutation of a certain amino acid is displayed for each table. The different colors correspond to the differnt tables and the total distribution. Furthermore we ploted not the absolute values, but the relative ratio of the amino acid exchange within one table (in percent).

Looking at the overlaping result of both database we can see that almost every amino acid mutation occures. The only amino acids which do not mutate are Alanine, Asparagine, Cystein, Glutamine and Threonine. Three of these amino acid (Ala, Cys, Gln) do not occure in the other tables as well. One possible reason is that this amino acid were encoded only by very little possible triplets which means that they probably occure less often. Asparagine has probably the same reason which means that only few triplets encodes it. Threonine does probably never mutate by accident, because it can be encoded by an higher number of triplets. The amino acids that mutate most common in the overlapping result of both databases are Arginine and Glycine. A possible reason for this is that Arginine can be encoded by many possible triplets as well as Glycine which has as result that they are probably more common amino acids.

Looking at the DBSNP result which were not in HGMD we can see that there are many amino acids which do not mutate. A reason for this is that the number of found mutations which are only in SNPDB and which are not silent is very low and therefore not really significant. The most common mutated amino acid is here Asparagine. A possible reason can be that this amino acid is encoded by less triplets and in relation to the other tables it occures here very often by chance.

For the silent mutations we also extract the amino acid where a nucleotide exchange takes places. Most strikingly are Serine and Valine which have the highest percentage for silent mutations. This can be explained by the fact that these amino acids were encoded by a high number of different triplets. The reason is that a silent mutation is more usually when a amino acid is encoded by many triplets.

At last we ploted the total result of all tables together. In this case the most commonst amino acid exchange is for Arginine followed by Glycine, Serine and Tryptophan. This corresponds to the overlapping results of both databases, because it has highest number of results. The only excpetion is Serine which mutates a lot in the other two cases. Furthermore these result agrees also with the explanation that these amino acids excepted Tryptophan were encoded by many different triplets. This means that they occure probably more often in sequences. Tryptophan is probably occuring so often by chance, because it is encoded only by one specific triplet. The rest of the amino acid mutation rates correspond mostly the result of both databases as well.

All in all, the barplot result agrees often with the number of triplets that encodes a certain amino acid. The amino acids that are encoded by many triplet are probably more common amino acids while amino acids that are encoded only by few triplets are rare. However this is not really true in biology but it agrees partly. Furthermore the silent mutations are more common in amino acids that were encoded by many triplets which is logical and can be explained well. Besides the results are not really significant because they are very small. For a really statistic evidence more informations are necessary. However, this barplot gives a good overview for the amino acid mutation rate for this special case.

Figure 1: Barplot for the frequency of a certain amino acid mutation for the different tables