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Overview:
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The
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first
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step
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to
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begin
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processing
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raw
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data
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from
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16S
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Illumina
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libraries
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is
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to
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split
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the
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multiplexed
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libraries,
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trim
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the
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sequences
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to
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the
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same
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length
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and
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filter
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for
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quality.
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I've
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found
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that
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trimming
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to
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the
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same
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length
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is
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best,
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because
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the
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same
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sequence
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might
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cluster
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differently
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depending
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on
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what
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length
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it
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is.
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I've
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also
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included
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the
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parameters
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things
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that
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I've
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found
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most
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useful. This also makes a first pass OTU classification at 97% to a reference database (closed-reference OTU picking). This is a good for taking a first pass look at your data.
Process:
The easiest way to process fastq files from 16S Illumina data is to use Qiime. Follow the link for a tutorial:
http://http://qiime.org/tutorials/tutorial.html
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This
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is
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installed
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on
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the
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darwin
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cluster
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(beagle)
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through
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the
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command:
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module
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add
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qiime-default
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Only
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the
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dependencies
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required
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for
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the
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default
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Qiime
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pipeline
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are
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loaded.
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Other
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tools
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might
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not
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be
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available.
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To
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process
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the
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data,
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I've
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written
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a
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script
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that
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can
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automate
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the
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process.
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The
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script
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needs
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to
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be
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edited
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to
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include
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the
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path
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to
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the
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solexa
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file
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etc.
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This
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can
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be
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submitted
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to
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the
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cluster
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with
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the
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following
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command
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(the
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RunQiime.csh
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file
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should
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be
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attached):
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qsub
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-cwd
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Below
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I've
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elaborated
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on
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what
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each
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of
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the
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variables
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mean:
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#define
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your
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file
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paths
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#where
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is
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the
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fastq
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file
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you
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want
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to
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process
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SOLFILEF=
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This
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is
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the
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path
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to
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your
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solexa
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file
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as
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a
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fastq
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file.
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#Where
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it
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the
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associated
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mapping
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file
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MAPFILE=
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The
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mapping
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file
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is
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expanded
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on
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in
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the
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Qiime
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webpage
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tutorial
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above.
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#the
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oligo
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file
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OLIGO=
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This
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is
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a
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file
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required
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by
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mothur
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to
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remove
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the
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primer
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and
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diversity
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region
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from
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the
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library
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construct.
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Mothur
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looks
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for
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the
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exact
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sequence,
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and
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only
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keeps
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sequences
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when
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the
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primer
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sequence
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is
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found.
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As
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a
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note,
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if
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you
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are
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using
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Phusion
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or
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another
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proof-reading
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polymerase,
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mismatches
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in
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the
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primer
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site
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within
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4
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bases
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from
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the
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3'
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end
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are
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reverted
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to
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the
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template
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sequence
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(actually,
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NEB
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says
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that
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it
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will
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change
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anything
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within
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10
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bps
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of
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the
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3'
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end),
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which
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would
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then
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be
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consequently
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discarded
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at
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the
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trim.seqs
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step.
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I
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typically
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change
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the
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last 4 from the 3'
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end
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of
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the
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primer
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to
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N's
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to
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be
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safe.
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Filtering
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sequences
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that
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don't
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match
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the
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primer
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sequence
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has
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been
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shown
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to
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improve
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the
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quality
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of
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the
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data
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(
...
...
).
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#where
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the
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programs
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are
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called
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from
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BIN=/data/spacocha/bin
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This
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is
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a
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folder
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where
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you
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should
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put
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the
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following
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files:
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...
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#where
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you
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want
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to
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put
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the
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output
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of
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the
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analysis
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UNIQUE=
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It's
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a
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unique
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name
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for
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this
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analysis.
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It
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can
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include
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folders
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(which
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must
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exits),
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but
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the
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final
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extention
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is
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a
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pre-fix
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for
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all
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files.
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#reference
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fasta
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file
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(latest
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greengenes
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OTUs)
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REFERENCEFA=
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These
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can
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be
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downloaded
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from
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the
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top-right
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corner
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of
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the
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#reference taxonomies
REFERENCETAX=
This will be in the same download as above, only in the taxonomy folder.
Output:
The output files that are created are the following (where the UNIQUE would be replaced by the variable defined above):
UNIQUE_output/ucrC/seqs_otus.mat
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-This
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is
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a
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matrix
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of
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your
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OTUs,
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mapped
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to
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the
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reference
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UNIQUE
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_output/seqs.trim.names.fasta
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-These
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are
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the
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trimmed,
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cleaned
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fasta
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sequences
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that
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were
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clustered.
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UNIQUE
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_output/split_library_log.txt
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-This
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contains
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stats
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about
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how
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your
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libraries
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are
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processed
Additional Notes:
Please let me know if there is anything that you don't understand about this process. I am happy to help. I think everything that you need is there, but I might have missed something.