User guide for Haplotracker  

     Kijeong Kim, M.D., Ph.D. (kimkj@cau.ac.kr)


 

   Mitochondrial DNA (mtDNA) haplogrouping is widely used in genetics, anthropology, forensics, and medical research. However, DNA is often degraded in forensic and human remains, generally found as tiny fragments in limited amounts, which makes haplogrouping infeasible. Current haplogrouping servers do not provide flexible options for tracking haplogroups (HGs) from degraded DNA samples. Here, we developed Haplotracker as a highly accurate, efficient system for tracking HGs from degraded DNA samples. Haplotracker can classify HG using a full-length mitochondiral genome (mtGenome) DNA sequence. Haplotracker also provides options to use short sequence fragments in the control region (CR) and searches the closest-ranked HGs using algorithms based on Phylotree Build 17 (Phylotree) definitions and our large haplotype database (n=118,869). It narrows the HGs and identifies their differential variants to verify the top-ranked HG or to track sub-haplogroups. It provides a conserved region mapping tool for PCR primer design for targeted HGs, which is essential for further tracking using degraded DNA samples. Haplotracker showed high HG prediction power using 8,216 CR sequences of mtGenomes from Phylotree. Using Phylotree-defined HGs, Haplotracker predicted the top-ranking HGs with the highest agreement rate (56.6%, p<0.0001) with Phylotree HG assignments; MitoTool (29.4%), and HaploGrep 2 (33.9%). Further evaluation using 46,322 CR sequences from GenBank mtGenomes also resulted in significantly higher accuracy with Haplotracker. Free access: https://haplotracker.cau.ac.kr


Browser compatibility

 OS

 Version(s)

 Chrome

 Firefox

 Safari

 Microsoft Edge

 Linux

 CentOS 7, Ubuntu 18

 78.0

 70.0

 

 

 MacOS

 Mojave

 78.0

 70.0

 12.1

 

 Windows

 7, 10

 78.0

 70.0

 

Jan 2020

 

 Contents

    Main tools

    Accessory tools

    References

 

 

1. HG tracking by fragment sequences or a complete mtGenome sequence (Track by Sequences)

    This is the representative tool of Haplotracker and is for HG tracking with multiple small mtDNA sequence fragments from degraded DNA samples, from which PCR amplification of large fragments is difficult. The fragmented sequences obtained from the same sample DNA can be simultaneously inputted. You can also input a complete mtGenome sequence.

     

    Input of sequences

      See the screen capture (Fig. 1a) as an example.

      Sample name field: sample name is a necessary option to avoid confusion during multiple analyses. The sample name is shown on result windows as well as on the browser tab.

      Rank group level (selector, 1-4): Rank group level was for restricting the lowest level of the HG rank group to be displayed. The rank group is determined by variant identity that is produced by the comparison of the sample variants with Phylotree-defined HGs (Phylotree-HGs) and their variant profiles. Users can choose a numeric value from 1 to 4. The default value is 2. In most cases, this field doesn't need to be changed in the beginning.

      DNA sequence field(s): Sequence fragments or a complete mtGenome sequence can be used. For the complete mtGenome sequence, enter the entier sequence into Field 1 and just press submit button. The sequence(s) can be copied from other sources and pasted into the field(s). DNA sequences should be capital letters, For multiple sequence fragments, click button    +   or   +3   for addition and   -   or   -3   for removal  below the field. All the sequences should be originated from the same sample. Each field should contain a fragment of sequence. The IUPAC nucleotide codes can be used including 'N'. 'D' is interpreted as 'A, G, or T' not as deletion. The button  Clear  or  Clear all  empties the sequence contents only.   Reset all  button initializes this window.   Submit button starts HG tracking processes.

      Batch intput of sequences: multiple sequence fragments can be conveniently entered into field 1 with the format as follows. Region of the mtDNA sequence first should be specified as 'CR;' for control region, and 'DR;' for coding region for each sequence. Fragments should be separated by line feed. See the exapme below.

       

        CR;TTAAACTATTCTCTGTTCTTTCATGGGGAAGCAGATTTGGGTACCACCCAAGTATTGACTCACC

        CR;ATCAACCTTCAACTATCACACATCAACTGCAACTCCAAAGCCACCCCTCACCCACTAGGATACCAACAAACCTACCTACC

        CR;CTTAACAGTACATAGTACATAAAGCCATTTACCGTACATAGCACATTACAGTCAAATCCCTTCTCGTCCCCATGGATGA

        CR;GGTATTTTCGTCTGGGGGGTGTGCACGCGATAGCATTGCGAGACGCTGGAGCCGGAGCACCCTATGTCGCAGTATCT

        CR;GCGAGCATATCTACTAAAGCGTATTAATTAATTAATGCTTGTAGGACATAATAATAACAATTGAATGTCTGCACAGCCG

        DR;GCCCATGAGGTGGCAAGAAATGGGCTACATTTTCTACCCCAGAAAACTACGATAGCCCTTATGAAACCTAAGGGTC

        DR;CTAGCCGCAGACCTCCTCATTCTAACCTGAATCGGAGGACAACCAGTAAGCTACCCCTTTACCATCATTGGACAA

       

      Accept 'N' in sequences (selector, 'N' accept?): Default is 'No', interpreted as 'not sequenced' (no matching and no missing variants during HG tracking processes). If the DNA sequences carry 'N' and users want to consider this as 'A, C, G or T', select 'Yes'. Tandemly repeated 'N's more than four are interpreted as 'not sequenced'.

      Control / coding region (buttons): This is important. If the sequence fragment is mainly of control region even with partly carrying sequences of the coding region, the button "Control" should be ticked (default). Likewise, "Coding" should be ticked if the sequence is (mainly) of the coding region.

      Sequence examples (hyperlink):  Example sample sequences are provided.

       

            *An example

              Try Example run  (under menu Guide at homepage).

         

        [Actions]

        - Click the menu Track by Sequence  
        - Enter  "JQ245759"  in Sample name field (without quotation marks).
        - Click the hyperlink Sequence examples. Example window is opened in a new tab (Fig. 1b)
        - Copy the DNA sequence of fragment 1 of Example 1.
        - Go to the sequence input window (S1 tab of the browser) and paste it into the field of fragment 1. Ensure fragment region is "Control" as default.
        - Click   +   button just beneath the field of fragment 1. A blank field for fragment 2 is opened.
        - Go to the Examples window again and copy the sequence of fragment of Example 1.
        - Go to the sequence input window and paste it into the field of fragment 2.  Ensure fragment region is "Control" as default.
        - Click   +   button. A blank field for fragment 3 is opened.
        - Go to the Examples window again and copy the sequence of fragment 3 of Example 1.
        - Go to the sequence input window and paste it into the field of fragment 3. Ensure fragment region is "Control" as default.
        - Click  Submit  button.

       

       Output

      See the captured figure below for an example (Fig. 1c).

      The sample name is shown on the window and the browser tab.

      The results window shows variant information and tracked HGs.

      The variant information includes fragment No., length(s), length(s), range(s), and variants obtained from (an) individual fragment(s) compared with rCRS, and all variants re-aligned based on PhyloTree Build 17 policy.  

      The tracked HGs (boldface) are first divided in order of rank group with their most recent common ancestor (MRCA) (the first column), which is determined by their variant identity (the third column) as mentioned above, and in each rank group, HGs are listed (the second column) in order of rank (shown in parentheses to the right of HGs) that is determined by their scores (shown in bracket left to the HG). In the figure, for example, there are twelve tracked HGs in rank group 1 and twenty-one, in rank group 2. HG W9 is top-ranked with the score value 0.192; HG W9 is predicted the highest for the given sample sequences.

       

     Tracking for verification of top-ranked HG 'W9' above.

      [Actions]

      (Continued with the example above)

      - Click the button Narrow:  Rank Group 1  at the bottom of the current window (Tab S1●JQ245759). The window with "Narrowed Rank group 1" is opened in a new tab (Fig. 1d).
      - Click button HGs with scores to select HGs with scores larger than zero. Three upper-ranked HGs are selected (Fig. 1e).
      - Click button
      Differentiate btw HGs to search differential variants between these HGs. The results show HG W9 has differential variant 14097 and W5, 6528, or 15775 (Fig. 1f). The figure shows the variant 14097  is W9-specific, and 15775, W5-specific.
      - Go to the sequence input window named "Sx●JQ245759" on the browser tab (just to the left of current window).
      - Click the button
      Add (a) fragment(s) at the bottom.  The second sequence input window will be opened in a new tab. The window has previously inputted sequences in control region.
      - Click   +   button. A blank field for fragment 4 is opened. Click button "Coding" for this fragment.
      - Go to the Examples window labeled as "Examples (seq) on the browser tab that is on the far right.
      - Copy the DNA sequence of fragment 4 of Example 1 to input the fragment containing  np 14097 of the variant.
      - Go back to the sequence input window (the second one) and paste it into the field of fragment 4.
      - Click   +   button. A blank field for fragment 5 is opened.  Check the fragment region is "Coding".
      - Go to the Examples window again and copy the sequence of fragment of Example 1 to input the fragment containing  np 15775 of the variant.. 
      - Go back to the sequence input window (the second one) and paste it into the field of fragment 5.
      - Click  Submit  button (Fig. 1g).

        Interpretation of results (Fig. 1h)

        You can see five fragments were tested, as shown in the upper table.
        Fragment 4 has the variant 14097 but not 15775.
        The HG of this sample was verified as "W9" based on the following results:
              1) W9 has the coding region variant 14097 which is W9-specific (upper table).
              2) W9 is top-ranked (lower table).
              3) There is only W9 in Rank group 1 (lower table).

     

    Quality control (QC)

      This result window shows further detailed information concerning score details and sample quality control, including  mean of the number of missing variants in the database, mean of the number of extra variants in the database, frequency of missing variant(s), frequency of extra variant(s), reported phantom variant hot spots, and number of variants found in other HGs that can suggest the potential artificial recombination.

      See the screen capture (Fig. 1i) below that resulted from Example variants 4.

      Score values are produced by the sum of frequency rates of missing variants and extra variants of the HG found in the built-in haplotype database (n=118,869). Results show the frequencies of missing variants and extra variants.

      The server provides the following notices to evaluate sample quality control,

      1) Variant identity

        Variant identity (%) presents the total quality level of the sample. If it is >= 90%, good (in black, boldface); >= 80 and < 90, moderate (in blue); < 80, poor (in red)

      2) The number of missing variants of top-ranked HG with its mean value of the number of missing variants found in the database.

        It alarms too many missing variants (alarmed in red) when the count is over mean + SD of the number of missing variants of the HG in the database.

      3) Comparison of the total number of extra variants of top-ranked HG with its mean value of the number of extra variants found in the database.

        It alarms too many extra variants (alarmed in red) when the count is over mean + SD of the number of missing variants of the HG in the database

      4) Reported phantom variants are shown in lime (Yao et al., 2009; Bandelt et al., 2012)  or in aqua (Brandstatter et al., 2005) and  rare variants not found in PhyloTree Build 17 in gray in the columns of missing and extra variant frequency of the table.

      5) Artificial recombination can be suspected by checking the presence of variants in other HGs in the rightmost column of the table. The server uses the same method as the one of HaploGrep 2.

 

 

Fig. 1a. Screen capture of sequence input window.

 

 

 

Fig. 1b. Screen capture of  Sequence examples.

 

 

 


 
Fig. 1c. Screen capture of the results window of HG tracking.

  

 

 


Fig. 1d. Screen capture of the HGs of narrowed Rank group 1.

 

 

 

 

Fig. 1e. Screen capture of the selection of HGs with scores.

 

 

 

Fig. 1f. Screen capture of the differential variants of selected HGs.

 

 

 

Fig. 1g. Screen capture of the second round of sequence input window.

 

 

 

Fig. 1h. Screen capture of the confirmation of top-ranked HG, W9 resulted from the previous tracking with control region sequences.

 

 

 

  

 Fig. 1i. Screen capture of the analysis (score details and QC).

 

 

 

 



 

2. HG tracking by fragment variant profiles (Track by Variant)

    This tool is for HG tracking with "variant profiles". The variants are originally acquired from the sequence (Guide No. 1). Once "variants" and their fragment "ranges" on rCRS are in hand, "variants" instead of sequences can be used for the same purpose.  Multiple variant profiles of the same sample DNA can be simultaneously inputted

     

    Input of variants

      See the screen capture (Fig. 2) as an example.

      Sample name: The same as above in Guide No. 1.

      Rank group level: The same as above in Guide No. 1.

      Variant profile field(s): Variants in any format of PhyloTree, MitoTool, HaploGrep 2, or EMPOP can be inputted. The variant format is automatically converted to the one of PhyloTree. The variant profiles can be copied from other sources and pasted into the field(s). For multiple fragments, click button  +   or   +3   for addition or   -   or   -3   for removal  below the field. All the fragments should be originated from the same sample. Each field should contain "variants" of a fragment of sequence. The IUPAC codes can be used, including 'N'. 'D' is interpreted as 'A, G, or T' not as deletion. The button  Clear  or  Clear all  empties the variant contents only.   Reset all  button initializes this window.   Submit  button starts HG tracking processes.

        Variants format

          PhyloTree
          Please refer to PhyloTree.org.
          Nucleotide position numbers are relative to the rCRS. Mutations are transitions unless an exact base change is specified
          Deletion at the single position is written as the position and  'd' (e.g., 249d)
          Deletion of a range is written as the range and 'd' (e.g., 290-291d)
          Insertions are written as the position before the insertion and:
               '.1' and the inserted nucleotide for a single nucleotide insertion (e.g., 291.1A)
               '.' and the number of repeats and the nucleotide for the insertion of repeats of a nucleotide (e.g., 573.3C)
               '.1' and the nucleotides for the insertion of nucleotides that are not repeats of a nucleotide (e.g., 292.1AT)

          Examples of variant profiles in different formats
          PhlyoTree: 73 152 182 186A 189C 247 249d 263 292.1AT 316 573.3C 16129 16189 16192-16193d 16215 16223 16278 16294 16311 16360
          HaploGrep 2: 73G 152C 182T 186A 189C 247A 249d 263G 292.1AT 316A 573.1CCC 16129A 16189C 16192d 16193d 16215G 16223T 16278T 16294T 16311C 16360T
          EMPOP: 73G 152C 182T 186A 189C 247A 249del 263G 292.1A 292.2T 316A 573.1C 573.2C 573.3C 16129A 16189C 16192del 16193del 16215G 16223T 16278T 16294T 16311C 16360T
          MitoTool: 73, 152, 182, 186A, 189C, 247, 249d, 263, 292+AT, 316, 573+XC, 16129, 16189, 16192-16193d, 16215, 16223, 16278, 16294, 16311, 16360

      Accept 'N' in sequences (checkbox): The same as above.

      Enter  the range of the fragment: This is important. The correct range (corresponding to positions of rCRS) of the fragment variants is important for accurate prediction.

      Batch intput of variant profiles: multiple variant profiles can be conveniently entered into Field 1 with the format as follows. Input the range (position numbers separated by a hyphen with no space) and variants separated by a single space for each fragment (just input the range for no variants in the specified range). Fragments should be separated by line feed. See the example below.

       

        16009-16167  

        16216-16295 16223 16292

        16296-16384  

        53-172 73

        185-291 189 194 195 204 207 263

        1339-1467 1406 1438

        15728-15901 15784 15884C

       

      Examples of variant profiles (hyperlink):  Examples variant of profiles are provided. The link can be found just above the fragment 1 field.

       

 

 

Fig. 2. Screen capture of variants input window.

 

 

 

 

3. Conserved region search for primer design (Conserved Region Map)

    This tool helps users find conserved regions for the primer design to obtain additional fragments by PCR, which are required for further tracking of HGs with differential variants. The fragments of DNA across the variant positions are amplified by PCR. Well-designed primers are essential for successful PCR. Primers should be perfectly hybridized on the template DNA of the sample for the successful PCR, particularly for degraded DNAs present in a small amount. The finding of conserved regions for primer binding is one of the essential factors to be considered. Our server provides the tool to find these regions. With a given range and specified HGs, this tool searches the conserved regions in the range. Users can design the primers even with degenerated sequences relying on the information of the variants suggested by this tool, even if there are no conserved regions found under the given conditions and inevitably no other options. Under the given range with or without HG(s) restriction, this tool finds all variants present in the range and shows those graphically and the HG(s) on every variant. The conserved regions are displayed by dots.

     

    Field/checkbox description

      Enter a region (np) for PCR:

        A short-range (preferably < 300bp) around the variant of interest is necessary due to the degraded DNA.
        A position instead of a range can be inputted to find the HGs carrying the variant at the position.

      (Optional) unfold all subgroups checkbox:

        If this checkbox is ticked, the server returns all subgroup details.

      HG target(s) for PCR:

        Enter HGs separated by space (e.g., C Z D E G Q). Case sensitive.
        Each HG name should contain no space. Instead, use an underscore if it is required (e.g., U4b1+146_152).
        For the design of primers for the control region, it is recommended not to specify HGs.

    Results:

      Variants map

        The beginning position and end position of the range are shown in brackets.
        Conserved regions for "all the specified HGs" are marked by dots.
            Primers can be designed in these regions between the variants
        Variant positions are shown in numbers, and specified HGs, in brackets beside the variant position

      Variants table

        HG details at the variant positions are shown in the table.

    An example of the use of this tool: (Fig. 3)

      Click Conserved Region Map

      Input "5000-5400" in the field of 'Enter a region (np) for PCR'.
      Input "D G" in the field of 'Specify HGs'.
      Press 'Enter' button.

      Dotted area can be used for primer design for both D and G because they are conserved.

      HGs D and G have the same variant profile of the control region, as shown below (See Guide No. 5. Differentiation between HGs). A demonstration of the presence of the variant 5178A is additionally required to determine D and 5108, G. The figure below shows the conserved regions of the candidate primers for the variants 5178A and 5108.  The range was set small because the sample is degraded. HGs D and G were input in the field of 'Specify haplogroup(s)' to avoid all the variant positions of the both because the HG is not determined yet.

     

 

 

Fig. 3. Screen capture of the result of conserved region search for primer design.

 

 

 

 

 Accessory tools

 

 

 

 

4. HG database

    This tool helps users to explore an HG and its subgroups and their differential variants. A HG of question is entered in HG field, and the lowest number of subgroup level for HGs to be listed is specified. The server then returns all the HGs from the HG entered to the lowest level of its subgroups, with HG-definition by PhyloTree Build 17, HG-differential variants, HG-specific variants, highly specific variants, and non-conserved variants.

     

    Input fields description

            HG
                Enter only one HG (case sensitive)
                HG name should contain no space. Instead, use an underscore if it is required (e.g., U4b1+146_152). 

            Subgroup level: enter the number of the lowest level of the subgroup to be seen.

     

    Interpretation of results

       See the screen capture (Fig. 4) below as an example.
      It shows HG T with the lowest subgroup level 1.
      There are HGs of T and its three subgroups, T1, T2, and T3.

      Variants description

        Variants of each HG are shown in the column of variants.

        Variants of control region are shown in blue;  HG-specific, in maroon; highly specific, in teal; non-conserved variants, gray; differentiable variants, in boldface.
        The specificity described here is based on the HG variants defined by PhyloTree build 17
        The 1st column:
        numbers in brackets [ ] beside HGs are the total number of subgroups of the HG carries.
        The 2nd column: HG-definition by PhyloTree Build 17
        The 3rd column: HG-differential variants
        The 4th column: numbers in brackets [ ] of highly specific variants in coding region are the number of cross-presenting HGs
        The 5th column: numbers in brackets [ ] of non-conserved variants in coding region are the number of the non-conserved  HGs within the corresponding HG.

        HG-specific variants of an HG mean that the variants are found only in the HG and if any, its subgroup(s).

        Highly specific variants of an HG mean that the variants are found in the HG but are also found in a small number of other HG(s).

          These variants are listed in the separated column with the number of cross-presenting HGs in brackets (the smaller, the more specific).

        Non-conserved variants of an HG mean that there is(are) its subgroup(s) that do(es) not have the variants.

          These variants are listed in the separated column with the number of (a) non-conserved subgroup(s) in brackets (the higher, the less conserved).

        HG-differential variants of an HG mean that the variants can be used to differentiate between the listed HGs

       Haplogroup selection checkboxes

        These are for selection options for differentiation between HG selections.

         

    *An example of the use of this tool

      The goal of this tool is to see subgroups belonging to the given HG and HG-differential variants between the subgroups.

      Click HG database

      Input "T" in the 'HG' field.
      Select "1" in 'Subgroup level'.
      Press 'Enter' button.

      See Fig. 4 below.

      The presence of one of the variants 12633A, 16163, and 16189 in the variants of the sample HG T1 can be checked to confirm the HG T1 among T, T1, T2, and T3, but 12633A is preferable because it is HG-specific.

      Likewise, the highly specific differentiable variants are
      11812 and 14233 for the HG T2. However, the variant 11812 is not preferable because this variant belongs to the non-conserved variants. So, the variant 14233 is recommended to use for the confirmation of the HG.

      Selection and differentiation between HGs are highly recommended to secure highly specific differential variants between them.

       

 

 



 Fig. 4. Screen capture of the result of HG database.

 

 

 

 

 

5. Differentiation between HGs (HG differentiation)

    This tool is for differentiation between HGs user inputted. It has an interface and functions similar to the ones of the HG database tool, but multiple independent HGs can be inputted by users.

    Input field description

            HGs:
                Enter HGs separated by space (e.g., C Z D E G Q)
                Each HG name is case sensitive and should contain no space. Instead, use an underscore if it is required (e.g.,
                U4b1+146_152).
                

    Interpretation of results: the same as above.

    An example of the use of this tool: the same as above.

      Click HG differentiation
      Input "D G" in the field of 'Haplogroups'.

      See Fig. 5 below.
      HGs D and G were differentiated.
      These HGs have the same variant profiles of the control region each other: 73 263 489 16223 16362
      HG D has two differential variants:
      4883 5178A
         The variant
      5178A  is HG-specific, so it is recommended to use for differentiation between the HGs D and G.
      HG G has four differential variants:
      5108 4833[1] 14569[1] 709[11]
         The variant
      5108  is recommended to use for differentiation between the HGs D and G. It is a higher differential than the others that are shared by D subgroups; 4833 by D4i2, 14569 by D1d1, and 709 by 11 subgroups of D (D1g2a, D1i2, D4g1c, D6, D6a, D6a1, D6a1a, D6a2, D6c, D6c1, and D6c1a). The variant 4833 is not conserved in HG G (G1a3, G2a1d2, and G2a1d2a).

       

 

 

Fig. 5. Screen capture of  the result of differetiation between HGs D and G.

 

 

 

 

 

6. Analysis of phantom mutants in a dataset (Phantom mutants)

This tool helps users find possible phantom variants (systematic artifacts) in a data set among the extra variants which are not used for HG definition by PhyloTree Build 17. It follows the rules proposed by HaploGrep 2.  At least two samples are required.  Before doing this analysis, haplogrouping of the samples should be done first using the HG tracking tools of this server. Variants that are re-aligned based on PhyloTree Build 17 should be used for this tool. The server keeps the sample name and variants re-aligned based on PhyloTree Build 17.

Field description

    Multiple samples of at least two that were previously haplogrouped should be input.

    The sample name and variants (re-aligned based on PhyloTree Build 17) should be delimited with the 'Tab' key. Input copied from the data in Excel is an easy option.

    Example: (Fig. 6a)

Results

    Possible phantom vairants are listed following the rules proposed by HaploGrep 2; the extra variants with a Soares score <3 are considered, occurring in at least two different samples.  

    Example: (Fig. 6b)

 

 

Fig. 6a. Screen capture of input data for the analysis of possible phantom variants for an example.

 

 

 

Fig. 6b. Screen capture of the analysis of possible phantom variants for an example.

 

 

7. Variant Format Conversion

    This tool is for the conversion of a variant format to the other one between PhyloTree and haplogrouping servers (MitoTools, HaploGrep 2, and EMPOP)
    Please note that variant profiles acquired from sequences can be web server-specific, so it can not be fully interchangeable between them for haplogrouping; instead, sequences should be used for it.

    The variants obtained by a certain web server are valid only for it and can be used for haplogrouping instead of sequences by the same server only.

    Refer to Guide No. 2 (Variants input guide for 'HG tracking by fragment variant profiles') for details.

    Convert to PhyloTree : this converts any variant format of HaploGrep 2, EMPOP, and MitoTool to PhyloTree format.
    Convert from PhyloTree to HaploGrep 2
    Convert from PhyloTree to EMPOP
    Convert from PhyloTree to MitoTool

 

8. Major HG-specific variants

    This tool shows major HGs, and their specific variants of PhyloTree Build 17.

     

References

    Haplotracker: DOI:10.1101/2020.04.23.057646

    PhyloTree Build 17: https://www.phylotree.org/

    HaploGrep 2: https://haplogrep.i-med.ac.at/

    EMPOP: https://empop.online/

    MitoTool: http://www.mitotool.org/index.html

     

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    van Oven,M. (2015) PhyloTree Build 17: growing the human mitochondrial DNA tree. Forensic Sci. Int. Genet. Suppl. Ser., 5, 392–394.

    Weissensteiner H, Pacher D, Kloss-Brandstätter A, Forer L, Specht G, Bandelt HJ, Kronenberg F, Salas A, Schönherr S. (2016) HaploGrep 2: mitochondrial haplogroup classification in the era of high-throughput sequencing. Nucleic Acids Res. 44, W58-W63.

    Parson W, Dür A. (2007) EMPOP—a forensic mtDNA database. Forensic Sci. Int. Genet. 1, 88–92.

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