These data file formats allow an experimenter to display data values at base
positions.
The data values an experiment generates are a decision made by the experiment.
The files are merely
the delivery mechanism to get the data values into the genome browser. The
data values have
no meaning without reference to the experiment that produced them. When you
are viewing
one of these data tracks the data values are graphed along the genome at their
respective
positions. To discover the meaning behind the graph, examine the description
page
for the track to see what the experiment is graphing. See also:
http://genomewiki.ucsc.edu/index.php/Selecting_a_graphing_track_data_format
--Hiram
----- Original Message -----
From: "Radhouane Aniba" <[email protected]>
To: "Genome List" <[email protected]>
Sent: Saturday, January 14, 2012 8:25:37 PM
Subject: [Genome] Wig, bigwig, bedgraph, in depth documentation
Hello everyone,
All of us, at least people working on NGS data analysis, are familiar with
these three data types, and we are refering to UCSC documentation to understand
their content and meaning. That's nice, but still there is some black boxes not
necessary clear especially these questions :
how comes that these files generated for the same experiment by different
programs, create different values and different distribution
a question that is more related to these programs now, how are these files
created from reads alignments ? What algorithm is behind these files ?
documentation on the format are clear enough, but significance and meaning of
the scores inside each file are not explained, what are these values referring
to ?
look at this sentence from UCSC " The BedGraph format allows display of
continuous-valued data in track format. This display type is useful for
probability scores and transcriptome data" : probability score ? Of what ? How ?
I hope i am not merging a lot of questions in a single post, they are all
related and i think it is worth mentionning them in block so that we can
discuss them in the same time.
Thanks for all.
Rad
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https://lists.soe.ucsc.edu/mailman/listinfo/genome
