Date: Fri, 29 Mar 2024 15:29:32 +0700 (NOVT)
Message-ID: <1597554615.88952.1711700972676@ugene.net>
Subject: Exported From Confluence
MIME-Version: 1.0
Content-Type: multipart/related;
boundary="----=_Part_88951_1291384619.1711700972675"
------=_Part_88951_1291384619.1711700972675
Content-Type: text/html; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
Content-Location: file:///C:/exported.html
FASTQ Trimmer
FASTQ Trimmer
The workflow scans each input sequence from the end to find the =
first position where the quality is greater or equal to the minimum quality=
threshold. Then it trims the sequence to that position. If a the whole seq=
uence has quality less than the threshold or the length of the output seque=
nce less than the minimum length threshold then the sequence is skipped.
Workflow Sample Location
The workflow sample "FASTQ Trimmer" can be found in the "Custom Ele=
ments" section of the Workflow Designer samples.
Workflow Image
The workflow looks as follows:
=20
=20
=
=20
=20
------=_Part_88951_1291384619.1711700972675
Content-Type: image/png
Content-Transfer-Encoding: base64
Content-Location: file:///C:/cf9d4fe16972959ec49f5047a61c9120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=
------=_Part_88951_1291384619.1711700972675--