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Create a Custom Parser

1. File Type

2. Detecting Headers

3. Extracting Records

4. Try It

Tell us about your file.

Custom File Type Genomics File Type

How is it delimited?

What's the structure of your file?

What type of genomics file?

Tell us about your file's headers.

My file has headers (and I don't need to change them)

Headers

Comma-separated list of headers.

My file has a "preamble" of non-header rows before the relevant content

How do we know what to skip?

Value

What's the identifying information for a record?

Your file likely has many fields, but only a few that uniquely identify a record when looking for matches in another file. We call these "match keys", and use them as the basis for any match-based accuracy statistics.

Auto-populate Fields

Use the button below to automatically grab the header of your file (based on the previous steps) to configure your data model. Get columns from file

Configure Fields

Match Key Columns

List of columns that uniquely identify a record when looking for matches in another file. For example, 'chr,pos,ref,alt'.

Match Key Columns

Comma-separated list of columns that uniquely identify a record when looking for matches in another file. For example, 'chr,pos,ref,alt'.

If matrixed file, the x-column name will be automatically added to this.

X Column Name

What you want to call the entity described in the horizontally expanded columns, e.g. 'sample'

Value Name

What you want to call the value in the matrixed cells, e.g. 'frequency'

How should we handle compound-name columns?

How is the entity name separated from the value column name?

Column header will be split into two by the first occurrence of this value.

In what order are the entity (x-column) and value-column names?

E.g. S1_VAF would be colname{delimiter}entity, where the sample is called S1 and the column is VAF.

Value Column Names

Comma-separated list of column suffixes (e.g. 'VAF,Dp' for columns like 'S1_VAF,S1_Dp,S2_VAF,S2_Dp' or 'VAF_S1,Dp_S1,VAF_S2,Dp_S2'. Please do not leave spaces between comma-separated items unless they are actually part of the suffix.

Should we explicitly include or exclude particular columns?

Get Columns

Comma-separated list of columns to be included

Skip Columns

Comma-separated list of columns to be skipped

Advanced

Filters

Filters are passed in an array and evaluated consecutively. They should reference column names in your parsed dataset and be prefixed by $ (e.g. "$vaf"). When comparing against strings, make sure to quote the left side of the expression in single quotes. For example: ["'$vaf' != 'NA'", "$vaf > 0"].

Check Results on Your File

Parse file

Advanced

Total Results

First 5 shown below

Look good? Continue on to explore this and other files.

Select a Parser

Parser

OR Add Custom Parser

Modify Match Columns

Configure Match Keys

Use arrow and tab keys to select from remaining columns. Click and drag column names to re-order.

Configure Fields

Numeric Columns Non-Numeric Columns Excluded Columns Need more customization to get the results you want? Create a custom parser. Open the File Settings menu under Workspace Files.

Fill me up!

You need files to work with! Add files using the Quickstart panel on the left to use the comparison tool.

Generating Report...

Want to see more metrics here? Return to the Report view and add "Stat" widgets.

Quickstart

Using Benchtop, you can benchmark and compare all sorts of bioinformatics output files, from VCF to CSV, TSV, and text tabular outputs to custom file types.

Add your comparison files below, and when you're ready:

Upload Google Cloud Storage AWS S3

Click the button below to create a private folder for your comparison files.

Create Folder

To compare your results, they need to be accessible. Enter the cloud bucket and internal location of this folder.

Bucket

Dir Key

Join today to start analyzing your own data.

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