leading or trailing characters trimmer.py -a -f $input1 -c $col -s $start -e $end -i $ignore $fastq > $out_file1 No Yes > @ + < * - = | ? $ . : & % ^ #

**What it does** Trims specified number of characters from a dataset or its field (if dataset is tab-delimited). ----- **Example 1** Trimming this dataset:: 1234567890 abcdefghijk by setting **Trim from the beginning to this position** to *2* and **Remove everything from this position to the end** to *6* will produce:: 23456 bcdef ----- **Eaxmple 2** Trimming column 2 of this dataset:: bcde 12345 fghij 67890 fghij 67890 abcde 12345 by setting **Trim content of this column only** to *2*, **Trim from the beginning to this position** to *2*, and **Remove everything from this position to the end** to *4* will produce:: abcde 234 fghij 67890 fghij 789 abcde 12345 ----- **Trimming FASTQ datasets** This tool can be used to trim sequences and quality strings in fastq datasets. This is done by selected *Yes* from the **Is input dataset in fastq format?** dropdown. If set to *Yes*, the tool will skip all even numbered lines (see warning below). For example, trimming last 5 bases of this dataset:: @081017-and-081020:1:1:1715:1759 GGACTCAGATAGTAATCCACGCTCCTTTAAAATATC + II#IIIIIII$5+.(9IIIIIII$%*$G$A31I&&B cab done by setting **Remove everything from this position to the end** to 31:: @081017-and-081020:1:1:1715:1759 GGACTCAGATAGTAATCCACGCTCCTTTAAA + II#IIIIIII$5+.(9IIIIIII$%*$G$A3 **Note** that headers are skipped. .. class:: warningmark **WARNING:** This tool will only work on properly formatted fastq datasets where (1) each read and quality string occupy one line and (2) '@' (read header) and "+" (quality header) lines are evenly numbered like in the above example.