text: user3235: I would like to trim/mark adapters using trimmomatic or picard MarkIlluminaAdapters from a series of Illumina Paired-End read fastqs. The fastq files may have been done using different kits or different generations/versions of illumina chips.
  Without knowing ahead of time how the libraries were prepared (or which kit was used), Is there a safe "catch all" adapter sequence (or set of such sequences) that can be passed to a trimming tool and that would cover all Illumina kits? In other words, what are we expected to know about the fastq to ensure correct trimming?
  edit: Picard defines a few built-in adapters which cover many standard kits, but it's not immediately obvious if you need to pass a common one (built-in sequences defined here).
  
  user77: You're best off just using fastp or Trim Galore!, both of which will determine the adapter sequence for you. Trim Galore! uses a built-in list of known sequences for this, whereas fastp uses read overlap.
  
  user4298: Alternatively, I really like using bbduk which is part of the BBMap suite.
  I've processed every nascent sequencing dataset that has been published, and found a lot of quirky errors with older datasets using TrimGalore. bbduk is a little more fine-tuneable relative to cutadapt/trimmomatic/trimGalore (built on top of cutadapt)/fastp and the run time and memory usage is significantly less.
  When you clone/install the repository, there is a directory of adapter fa files that you can choose from for trimming in the resources/ subdirectory which you can specify using the "ref" argument (i.e. ref=adapters.fa). The "adapters.fa" file is an excellent catchall for adapters, but you will likely over-trim a little. Alternatively, if you know what adapters were used in your dataset, you can choose one of the other pre-configured fa files. There are also a number of stats/marking/reporting/trimmed read save options which you can see here:
  https://github.com/BioInfoTools/BBMap/blob/master/sh/bbduk.sh
  
original_text: 3235: <p>I would like to trim/mark adapters using trimmomatic or picard MarkIlluminaAdapters from a series of Illumina Paired-End read fastqs. The fastq files may have been done using different kits or different generations/versions of illumina chips.</p>
  
  <p>Without knowing ahead of time how the libraries were prepared (or which kit was used), Is there a safe "catch all" adapter sequence (or set of such sequences) that can be passed to a trimming tool and that would cover <em>all</em> Illumina kits? In other words, what are we expected to know about the fastq to ensure correct trimming?</p>
  
  <p><em>edit:</em> Picard defines a few built-in adapters which cover many standard kits, but it's not immediately obvious if you need to pass a common one (<a href="https://github.com/broadinstitute/picard/blob/1531278515aaf39c9049b5792ae569b92326dd90/src/main/java/picard/util/IlluminaUtil.java#L141" rel="nofollow noreferrer">built-in sequences defined here</a>).</p>
   77: <p>You're best off just using <a href="https://github.com/OpenGene/fastp" rel="nofollow noreferrer"><code>fastp</code></a> or <a href="https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/" rel="nofollow noreferrer"><code>Trim Galore!</code></a>, both of which will determine the adapter sequence for you. Trim Galore! uses a built-in list of known sequences for this, whereas fastp uses read overlap.</p>
   4298: <p>Alternatively, I really like using bbduk which is part of the <a href="https://github.com/BioInfoTools/BBMap" rel="nofollow noreferrer">BBMap suite</a>.</p>
  
  <p>I've processed every nascent sequencing dataset that has been published, and found a lot of quirky errors with older datasets using TrimGalore. bbduk is a little more fine-tuneable relative to cutadapt/trimmomatic/trimGalore (built on top of cutadapt)/fastp and the run time and memory usage is significantly less.</p>
  
  <p>When you clone/install the repository, there is a directory of adapter fa files that you can choose from for trimming in the resources/ subdirectory which you can specify using the "ref" argument (i.e. ref=adapters.fa). The "adapters.fa" file is an excellent catchall for adapters, but you will likely over-trim a little. Alternatively, if you know what adapters were used in your dataset, you can choose one of the other pre-configured fa files. There are also a number of stats/marking/reporting/trimmed read save options which you can see here:</p>
  
  <p><a href="https://github.com/BioInfoTools/BBMap/blob/master/sh/bbduk.sh" rel="nofollow noreferrer">https://github.com/BioInfoTools/BBMap/blob/master/sh/bbduk.sh</a></p>
  