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  • cutadapt: guidance on rationale for --overlap=LENGTH values


    I'm getting up to speed with Marcel Martin's cutadapt for removing adapter sequences from Illumina libraries.

    I'd appreciate some expert input on what values might be reasonable for the -O (--overlap) parameter. As explained in the excellent help pages, this parameter defines the minumum overlap between the input adapter sequence and read sequences:
      -O LENGTH, --overlap=LENGTH
           Minimum overlap length. If the overlap between the read and the adapter is
    shorter than LENGTH, the read is not modified.This reduces the no. of bases
     trimmed purely due to short random adapter matches (default: 3).
    My initial run has used the default. I get trim data like this:

    Adapter 'GATCGGAAGAGCACACGTCTGAACTCCAGTCAC', length 33, was trimmed 205113 times.
    Histogram of adapter lengths
    length  count
    3       95613
    4       12912
    5       5869
    6       4173
    7       3809
    8       3323
    9       3183
    10      2934
    11      2938
    12      2464
    13      2213
    14      2041
    15      1803
    16      1650
    17      1489
    18      1334
    19      1269
    20      1147
    21      1031
    22      909
    23      859
    24      819
    25      701
    26      656
    27      536
    28      528
    29      488
    30      386
    31      368
    32      351
    33      47317
    I can see this is not sensible.

    With length=3 I get 95613 reads removed from my library; a good proportion of these must be spurious (i.e. by chance).
    With length=33 I get 47317 reads removed. These have a better chance of not being spurious.

    Somewhere between the boundaries here (3 .. 33) there must be a 'sensible' value for --offset. How do I identify it? Using what rationale? I could just opt for 33, the length of the adapter. But that would discount the probability that those of length 32 are also genuine (this library has an abrupt shift from 32 with 351 reads to 33 with the 47317, but not all my libraries look like this).

    How might I go about this??


  • #2
    My strategy so far was to not worry too much about the bases that get lost due to random matches. It depends on your data, but although 94613 looks large, you lose “only” 95613x3 bp, which may not be that bad.

    However, the “count” column in your histogram decreases montonically from length 3 to 32. This is different from what I see in my data. One explanation is that your adapter almost never appears partially – it's either fully there or not at all and all matches from length 3 to 32 are, in fact, spurious. In that case, you can safely set --overlap to 33.

    I'll probably change the output that cutadapt prints to make this all a bit clearer. Perhaps helpful would be print the number of bases removed and to give an estimate of how many of those were removed due to chance alone.


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