### [Quick Start and Tutorial for Web-Based MatchMiner]{.underline}

Overview

Using MatchMiner

> Interactive LookUp
>
> Batch LookUp
>
> Batch Merge

Additional Help and Information

> Hints
>
> Selecting algorithms
>
> Identifiers and Data Sources

**[Overview:]{.underline}**

MatchMiner is a freely available tool for the navigation among gene and
gene product Identifiers. It has two functions: 1) LookUp: translates
from one type of Identifier to another, either interactively or in
batch; and 2) Merge: Identifies and outputs the one-to-one, one-to-many,
and many-to-many relationships between two lists of Identifiers of
either the same or different types. This is done by translating the
input into an internal gene index and then retrieving the requested
information linked to that index.

**[Using MatchMiner:]{.underline}**

The homepage for MatchMiner looks as follows:

# Figure 1: MatchMiner Home Page

![](media/image2.png){width="5.9944444444444445in"
height="4.503472222222222in"}

By clicking on the buttons, the user can chose the appropriate searches
described in detail below. Examples are provided as well. Before
proceeding, please download the example files located under Help to your
home machine. Keep track of where you save them.

***Interactive Lookup:***

## 

The Interactive LookUp permits the input of a single Identifier for
quick querying.

**Figure 2: Interactive LookUp
Screen**![](media/image4.png){width="5.9944444444444445in"
height="4.495833333333334in"}

1.  Specify the type of Identifier you will input. The current choices
    are Chromosome Location (1p36.3, 1p36, 1p, etc.), Name (gene symbol,
    alias, or descriptive name), GenBank Accession number, Id (currently
    restricted to UniGene cluster, but will include LocusLink, OMIM, and
    others), FISH clone, and IMAGE clone Id. *Example: Name*

2.  Choose what search strategy you want to use to match your input to a
    gene index (see Table 1 in Helpful Hints). *Example: All(HUGO,
    Alias)*

3.  Enter your Identifier. *Example: p53*

4.  Choose the type of output you want. Currently, you can request
    Cytogenetic Location (1p36.3, 1p36, 1p, etc.), Name (symbol, alias,
    or descriptive name), GenBank Accession number, UniGene cluster Id,
    FISH clone, IMAGE clone Id, and Sequence Location Number (in bp).
    *Example: IMAGE clone*

5.  Choose the algorithm for returning the output type you want for the
    matching gene index (Table 1 in Helpful Hints). *Example: UniGene
    (this will be the only choice)*

6.  Choose the output format, either HTML, text, or Excel (use text or
    Excel if you wish to save your results locally). The Excel format
    will put a space in front of text entries. The text format has no
    such extra characters. In Excel, you can save the file by choosing
    "Save." *Example: HTML*

7.  Optional: Check the "Filter Data Source Details" button to suppress
    the meta-details for the match.

8.  Click the "Get Result" button.

Figure 3a: LookUp Result (HTML) Summary

![](media/image6.png){width="5.9944444444444445in"
height="4.495833333333334in"}

# Figure 3b: LookUp Results Table (HTML) ![](media/image8.png){width="5.9944444444444445in" height="4.495833333333334in"}

The LookUp Result Page begins with a description of the parameters for
the search, followed by a summary of the number of hits. This is then
followed by a table indicating the type of output, the input
Identifiers, the matching output Identifier, the internal gene index,
and a summary of the data source in which the input Identifier is found,
followed by a summary of the output Identifier data sources. These
details are important because they allow the user to determine how the
matches are made. As seen in figure 3, the input Identifier "p53" is
found in LocusLink and OMIM, but not UCSC or UniGene. The IMAGE clone
Ids corresponding to the p53 gene index are found in UniGene. This
represents a case where a match is made strictly by association through
the gene index and is not present explicitly in the database.

***Batch LookUp:***

Batch LookUp is operationally similar to the Interactive LookUp except
that instead of entering a single Identifier, you input a text file with
a list of Identifiers. The input file should be formatted as plain text
with one Identifier per line (see the example file). To use the Batch
LookUp:

### Figure 4: Batch LookUp Screen

### ![](media/image9.png){width="5.9944444444444445in" height="4.495833333333334in"}

1.  Specify the type of Identifier your input file contains. The current
    choices are Chromosome Location (1p36.3, 1p36, 1p, etc.), Gene Name
    (symbol, alias, or descriptive name), GenBank Accession number,
    UniGene cluster Id, FISH clone, and IMAGE clone Id. *Example: IMAGE
    Clone*

2.  Choose what search strategy you want to use to match your input to a
    gene index (see Table 1 in Helpful Hints). *Example: UniGene (note:
    this will be the only choice available)*

3.  Enter the filename of your input file. Clicking on the "Browse"
    button will allow you to browse to your file. *Example: Use the file
    called "top100cdnaclids.txt"*

4.  Choose the type of output you want. Currently, you can request
    Cytogenetic Location (1p36.3, 1p36, 1p, etc.), Gene Name (symbol,
    alias, or descriptive name), GenBank Accession number, UniGene
    cluster Id, FISH clone, IMAGE clone Id, and Sequence Location Number
    (in bp). *Example: Name*

5.  Choose the algorithm for returning the output type you want for the
    matching gene index (Table 1 in Helpful Hints). *Example: ALL(HUGO,
    Alias)*

6.  Choose the output format, either HTML, Excel or text (use Excel or
    text if you wish to save your results locally).

7.  Optional: Check the "Filter Data Source Details" button to suppress
    the meta-details for the match.

8.  Click the "Get Result" button.

# 

# 

The results will be returned as with the Interactive LookUp. There will
be a summary of the choices made to generate the output, a summary of
number hits and misses, and the table with the results. There is one
additional column, entitled "Position" which indicates the position of
the input identifier in the input file. Sorting using this column will
reorder the results to match in the input order. (Note: This function
only works if the files are saved locally as text and manipulated in
another program such as Excel.) Figure 5 shows what the results would
look like after importing to Excel. Excel as the file format will do two
things: \[1\] all text will be preceded with a space and \[2\] if Excel
is installed on your machine, the results will be displayed in Excel
automatically. To save the file, simply click save and give the file a
name.

# 

# Figure 5: Batch LookUp results in text file format

# ![](media/image12.png){width="5.9944444444444445in" height="4.495833333333334in"}

**[Batch Merge]{.underline}**:

The Batch Merge function is designed to Identify all of the one-to-one,
one-to-many, and many-to-many relationships between two lists of
Identifiers. These lists can have the same type of Identifier or
different types of Identifiers. The resulting output will consist of a
summary of the search parameters, as well as a summary of the items
matched, unmatched but in the database, and items missing from the
database. A table follows, giving all of the possible matches between
the two lists, with Identifiers with ambiguous assignments to gene
indexes flagged. Currently, the results are sorted by those items that
match between the lists, followed by items unmatched but present in the
database sorted by file, and items not found in the database, again
sorted by file. Two columns indicate the original order of the input
files entries and can be used to resort the data appropriately. (Note:
This function only works if the files are saved locally as text and
manipulated in another program such as Excel)

**Figure 6: Merge Function Screen**

![](media/image13.png){width="5.9944444444444445in"
height="4.495833333333334in"}

To perform a Batch Merge:

1.  Specify the type of Identifier your first input file contains. The
    current choices are Chromosome Location (1p36.3, 1p36, 1p, etc.),
    Gene Name (symbol, alias, or descriptive name), GenBank Accession
    number, UniGene cluster Id, FISH clone, and IMAGE clone Id.
    *Example: IMAGE Clone*

2.  Choose what search strategy you want to use to match your first
    input file to a gene index (see Table 1 in Helpful Hints). *Example:
    UniGene (note: this will be the only choice available)*

3.  Enter the filename of your first input file. Clicking on the
    "Browse" button will allow you to browse to your file. *Example: Use
    the file* *"top100cdnaclids.txt"*

4.  Specify the Identifier type of the second file. Currently, you can
    request Cytogenetic Location (1p36.3, 1p36, 1p, etc.), Gene Name
    (symbol, alias, or descriptive name), GenBank Accession number,
    UniGene cluster Id, FISH clone, and IMAGE clone Id. *Example:
    GenBank Accession Number*

5.  Choose what search strategy you want to use to match your second
    input file to a gene index (see Table 1 in Helpful Hints).
    *Example:* *GenBank(All)*

6.  Enter the filename of your second input file. Clicking on the
    "Browse" button will allow you to browse to your file. *Example: Use
    the file "top100oligoacid.txt"*

7.  Choose the output format, either HTML, Excel, or text (use Excel or
    text if you wish to save your results locally).

8.  Optional: Check the "Filter Data Source Details" button to suppress
    the meta-details for the match.

9.  Click the "Get Result" button.

# 

# 

### Figure 7a: Merge Results Summary

![](media/image15.png){width="5.9944444444444445in"
height="4.495833333333334in"}

**Figure 7b: Merge Results Table**

![](media/image18.png){width="5.9944444444444445in"
height="4.495833333333334in"}

#### Additional Help and Information

#### 

#### *Hints*

1.  A record marked "No Gene Index Found" indicates that the entry could
    not be mapped to a gene index. Either the entry isn't in the
    database or there has been a mismatch between entry identifier type
    and search algorithm.

2.  Currently, files can contain only one type of identifier. Files with
    mixed identifier types will be processed but will return "No Gene
    Index Found" for those entries that are of a different identifier
    class than the specified search.

#### *Selecting Search Algorithms*

#### 

#### The variety of both identifier classes and potential database sources requires specifying how matches should be made. This decision is influenced by several factors including type of identifiers, primary and secondary data sources that contain the identifier, and the context in which the identifiers will be used. In MatchMiner, selecting algorithms for identifier translation has been divided into a two step process. The first step is to tell the program how to match the input to an internal gene index. For example, if the input is a file containing gene symbols, MatchMiner can either match the entries to gene indexes assuming all entries are HUGO (official) names or it can perform a broader search that matches all entries possible to HUGO names first and then goes back to the entries that were not matches and re-scans the list for matches to aliases. The second step selects the way the program should retrieve the requested information. Several of the data sources have similar but not the same information (e.g. cytogenetic location). The information retrieved will be dependent on how that information is going to be used. For instance, if the task is to look up the cytogenetic location of UniGene clusters, one might want to make sure that the locations returned are those from UniGene. However, suppose the list of UniGene clusters was restricted initially to "known" genes. Then, instead of wanting what matched UniGene, a user might want to have a more precise location based on sequence to cytogenetic map translation from UCSC.

#### 

#### Table 1 gives a description of the various algorithms associated with different identifier classes. Additional algorithms are in the works and suggestions are always welcome. 

#### 

#### 

#### Table 1: MatchMiner Lookup Search Options

+-----------------------+-----------------------+-----------------------+
| # Identifier Type     | **Input Algorithm**   | **Output Algorithm**  |
+=======================+=======================+=======================+
| **Name** (Gene        | **ALL (HUGO, Alias)** | **ALL (HUGO, Alias)** |
| Symbol, alias, or     |                       |                       |
| descriptive name)     | Starts with HUGO. If  | Returns the HUGO      |
|                       | not found, proceeds   | name. If no name is   |
|                       | through all other     | flagged as HUGO,      |
|                       | sources until a       | returns all aliases.  |
|                       | matching alias is     |                       |
|                       | found.                |                       |
+-----------------------+-----------------------+-----------------------+
|                       | # Official            | # Official            |
|                       |                       |                       |
|                       | Searches all data     | Returns the HUGO      |
|                       | sources for match as  | name. If not found,   |
|                       | the HUGO name.        | nothing is returned.  |
+-----------------------+-----------------------+-----------------------+
|                       | # Long                | # Long                |
|                       |                       |                       |
|                       | Searches all data     | Returns all           |
|                       | sources for           | descriptive names     |
|                       | descriptive name      |                       |
+-----------------------+-----------------------+-----------------------+
| **GenBank Accession   | # GenBank (ALL)       | # GenBank (ALL)       |
| Number**              |                       |                       |
|                       | Searches all data     | Returns accession     |
|                       | sources starting with | number from UCSC      |
|                       | UCSC known genes,     | known genes. If not   |
|                       | then LocusLink,       | found, proceeds       |
|                       | UniGene, and UCSC     | through UniGene then  |
|                       | ESTs until match      | UCSC EST              |
|                       | found.                |                       |
+-----------------------+-----------------------+-----------------------+
|                       | #                     | #                     |
|                       |  Data Source Specific |  Data Source Specific |
|                       |                       |                       |
|                       | Lookup input in a     | Returns accession     |
|                       | specific data source  | numbers found in a    |
|                       |                       | particular data       |
|                       |                       | source                |
+-----------------------+-----------------------+-----------------------+
| # IMAGE clone Id      | # UniGene             | # UniGene             |
|                       |                       |                       |
|                       | Only data source with | Returns all IMAGE     |
|                       | IMAGE clone Ids       | clone Ids associated  |
|                       |                       | with the UniGene      |
|                       |                       | Cluster corresponding |
|                       |                       | to the matching gene  |
+-----------------------+-----------------------+-----------------------+
| #                     | # ALL                 | # ALL                 |
|  Cytogenetic Location |                       |                       |
|                       | Searches all gene     | Returns chromosome    |
| #                     | indexes for matching  | band from UCSC        |
|                       | chromosome band       | sequence to band      |
| #                     |                       | translation. If not   |
|                       |                       | found, proceeds       |
| #                     |                       | through all other     |
|                       |                       | sources with multiple |
| #                     |                       | bands listed          |
|                       |                       | separately.           |
| #                     |                       |                       |
|                       |                       |                       |
| #                     |                       |                       |
|                       |                       |                       |
| #                     |                       |                       |
|                       |                       |                       |
| #                     |                       |                       |
|                       |                       |                       |
| #                     |                       |                       |
|                       |                       |                       |
| #                     |                       |                       |
|                       |                       |                       |
| #                     |                       |                       |
|                       |                       |                       |
| #                     |                       |                       |
|                       |                       |                       |
| #                     |                       |                       |
|                       |                       |                       |
| #                     |                       |                       |
+-----------------------+-----------------------+-----------------------+
|                       |                       | # UCSC                |
|                       |                       |                       |
|                       |                       | Returns chromosome    |
|                       |                       | band from UCSC        |
|                       |                       | sequence to band      |
|                       |                       | translation.          |
+-----------------------+-----------------------+-----------------------+
| # Database Id         | # UniGene             | # UniGene             |
|                       |                       |                       |
|                       | Searches gene index   | Returns UniGene Id.   |
|                       | for matching UniGene  |                       |
|                       | Id                    |                       |
+-----------------------+-----------------------+-----------------------+
| **Sequence Location   | Not Implemented       | # Transcription Start |
| Number** (BP)         |                       |                       |
|                       |                       | Returns transcription |
|                       |                       | start from UCSC Known |
|                       |                       | Genes. If not found,  |
|                       |                       | proceeds to UCSC EST  |
+-----------------------+-----------------------+-----------------------+
| **FISH Clone**        | # UCSC                | # UCSC                |
|                       |                       |                       |
|                       | Searches UCSC FISH    | Returns FISH clone    |
|                       | clones for match to   | Id.                   |
|                       | gene index based on   |                       |
|                       | sequence position     |                       |
|                       | overlap with UCSC     |                       |
|                       | known genes.          |                       |
+-----------------------+-----------------------+-----------------------+

#####  Identifiers and Data Sources

The ability to obtain meaningful results with MatchMiner is greatly
enhanced by understanding what types of identifiers can be encountered,
where they are used in public databases, and how they relate to one
another. The identifiers classes encountered in omic research refer to
genes at several levels of resolution from sequence to function to all
information about the gene.

GenBank is the repository for sequence information maintained and
curated by the NCBI (Benson et al. 2002). It is one of three databases
involved in the International Nucleotide Sequence Database
Collaboration; the European Molecular Biology Laboratory (EMBL) data
library and the DNA Data Bank of Japan (DDBJ) are the other partners.
Each of these databases share a standardized record format that permits
daily alignment of data between them so that any sequence is available
through any of the databases. A sequence record in GenBank is identified
by two numbers: a GenBank accession number and a gi number (Benson et
al. 2002). The accession number is unique and fixed. It always
references a particular sequence record. The GI number, in contrast, is
a unique number that references a particular edited state of the
sequence. As the sequence in the record is changed, the gi number will
also change. An indication of how many times this has taken place in a
given record is indicated by the "accession number.version" that appears
on the same line as the gi number. The distinction between gi number and
accession number is important to keep in mind when working with these
records as it will influence the ease by which an analysis or mapping
can be retraced in the future.

Certain classes of sequences carry a stereotypical GenBank accession
number. RefSeq is the most prominent of these classes and represents an
attempt to define a "canonical" sequence for reference to describe
various genes (Pruitt and Maglott 2001). These records are denoted by
NG\_ , NT\_, and NC\_ for genomic sequences, NM\_ and XM\_ for mRNA
sequence, and NP\_ and XP\_ for protein. RefSeq records are derived from
both computational and curated methods. As such, they carry a tag
indicating the quality of the sequence ranging from genome annotation
corresponding to modeled contigs, mRNA, and proteins, to reviewed
records which have been curated by NCBI staff (see (Pruitt and Maglott
2001) or <http://www.ncbi.nlm.nih.gov/LocusLink/RSfaq.html> for an in
depth description).

The association of one sequence from a gene with all other sequences
from that gene, especially at the mRNA level is the purpose of UniGene
(Wheeler et al. 2002). A UniGene cluster is a non-redundant grouping
mRNA and EST sequences that have been clustered together by virtue of
sequence similarity. This permits grouping of non-overlapping sequences
that span the length of a gene's mRNA. These records, denoted by a
unique UniGene cluster id, include all mRNA and EST GenBank sequence
records mapping to the cluster as well as the RefSeq GenBank accession
number for the protein of product of the cluster. These records also
carry the official name for the gene if it has been assigned and a
chromosomal location if known.

LocusLink is a non-redundant repository of annotated gene information
including descriptions of function, mappings in the GeneOntology™ as
provided by Proteome Inc., chromosomal location, and STS and other
sequence variations (Wheeler et al. 2002). In addition, there are
entries for the official gene name, or in its absence a provisional
name, aliases including common names and alternative gene symbols, and
cross-references to UniGene cluster ids, RefSeq GenBank accession
numbers, and OMIM records.

The cataloging of syndromes and their genetic etiology is the focus of
OMIM. These highly curated records contain descriptions of identified
genetic mutations and the resulting phenotypes as well as syndromes with
as of yet unidentified genetic components. All entries are highly
referenced to primary literature. As such, OMIM is an excellent source
of gene aliases and common names.

Not all sequences in an omic-level project are gene based. STS sequences
are useful because they precisely locate a particular region of DNA to a
location in the genomic contig. Such non-coding sequences can be
particularly useful in gaining information at the DNA level about
regulatory regions. The human genome sequence builds available from
University of California Santa Cruz (Cheung et al. 2001; Lander et al.
2001; McPherson et al. 2001) give access to STS and their aliases along
with their genomic location. In addition, this resource also encompasses
other types of records from GenBank and contains curated links back to
UniGene, LocusLink, and OMIM. NCBI also provides a build of the human
genome with similar data.

References

1\. Benson DA et al (2002) GenBank. *Nucleic Acids Res* 30 (1):17-20.

2\. Cheung VG et al (2001) Integration of cytogenetic landmarks into the
draft sequence of the human genome. *Nature* 409 (6822):953-958.

3\. Lander ES et al (2001) Initial sequencing and analysis of the human
genome. *Nature* 409 (6822):860-921.

4\. McPherson JD et al (2001) A physical map of the human genome.
*Nature* 409 (6822):934-941.

5\. Pruitt KD and Maglott DR (2001) RefSeq and LocusLink: NCBI
gene-centered resources. *Nucleic Acids Res* 29 (1):137-140.

6\. Wheeler DL et al (2002) Database resources of the National Center
for Biotechnology Information: 2002 update. *Nucleic Acids Res* 30
(1):13-16.