User guide

Basic usage

To trim a 3’ adapter, the basic command-line for cutadapt is:

cutadapt -a AACCGGTT -o output.fastq input.fastq

The sequence of the adapter is given with the -a option. You need to replace AACCGGTT with the correct adapter sequence. Reads are read from the input file input.fastq and are written to the output file output.fastq.

Compressed in- and output files are also supported:

cutadapt -a AACCGGTT -o output.fastq.gz input.fastq.gz

Cutadapt searches for the adapter in all reads and removes it when it finds it. Unless you use a filtering option, all reads that were present in the input file will also be present in the output file, some of them trimmed, some of them not. Even reads that were trimmed entirely (because the adapter was found in the very beginning) are output. All of this can be changed with command-line options, explained further down.

Input and output file formats

Input files for cutadapt need to be in one the these formats:

  • FASTA with extensions .fasta, .fa or .fna
  • FASTQ with extensions .fastq or .fq
  • Any of the above, but compressed as .gz, .bz2 or .xz

Cutadapt’s support for processing of colorspace data is described elsewhere.

Input and output file formats are recognized from the file name extension. You can override the input format with the --format option.

You can use the automatic format detection to convert from FASTQ to FASTA (without doing any adapter trimming):

cutadapt -o output.fasta.gz input.fastq.gz

Compressed files

Cutadapt supports compressed input and output files. Whether an input file needs to be decompressed or an output file needs to be compressed is detected automatically by inspecting the file name: If it ends in .gz, then gzip compression is assumed. This is why the example given above works:

cutadapt -a AACCGGTT -o output.fastq.gz input.fastq.gz

All of cutadapt’s options that expect a file name support this.

Files compressed with bzip2 (.bz2) or xz (.xz) are also supported, but only if the Python installation includes the proper modules. xz files require Python 3.3 or later.

Concatenated bz2 input files are not supported on Python versions before 3.3. These files are created by utilities such as pbzip2 (parallel bzip2).

Concatenated gz input files are supported on all supported Python versions.

Standard input and output

If no output file is specified via the -o option, then the output is sent to the standard output stream. Instead of the example command line from above, you can therefore also write:

cutadapt -a AACCGGTT input.fastq > output.fastq

There is one difference in behavior if you use cutadapt without -o: The report is sent to the standard error stream instead of standard output. You can redirect it to a file like this:

cutadapt -a AACCGGTT input.fastq > output.fastq 2> report.txt

Wherever cutadapt expects a file name, you can also write a dash (-) in order to specify that standard input or output should be used. For example:

tail -n 4 input.fastq | cutadapt -a AACCGGTT - > output.fastq

The tail -n 4 prints out only the last four lines of input.fastq, which are then piped into cutadapt. Thus, cutadapt will work only on the last read in the input file.

In most cases, you should probably use - at most once for an input file and at most once for an output file, in order not to get mixed output.

You cannot combine - and gzip compression since cutadapt needs to know the file name of the output or input file. if you want to have a gzip-compressed output file, use -o with an explicit name.

One last “trick” is to use /dev/null as an output file name. This special file discards everything you send into it. If you only want to see the statistics output, for example, and do not care about the trimmed reads at all, you could use something like this:

cutadapt -a AACCGGTT -o /dev/null input.fastq

Multi-core support

Cutadapt supports parallel processing, that is, it can use multiple CPU cores. Multi-core is currently not enabled by default. To enable it, use the option -j N (or the spelled-out version --cores=N), where N is the number of cores to use.

Make also sure that you have pigz (parallel gzip) installed if you use multiple cores and write to a .gz output file. Otherwise, compression of the output will be done in a single thread and therefore be the main bottleneck.


In a future release, the plan is to make cutadapt automatically use as many CPU cores as are available, even when no --cores option was given. Please help to ensure that multi-core support is as stable as possible by reporting any problems you may find!

There are some limitations:

  • Multi-core is only available when you run cutadapt with Python 3.3 or later.

  • Multi-core cutadapt can only write to output files given by -o and -p. This implies that the following command-line arguments are not compatible with multi-core:

    • --info-file
    • --rest-file
    • --wildcard-file
    • --untrimmed-output, --untrimmed-paired-output
    • --too-short-output, --too-short-paired-output
    • --too-long-output, --too-long-paired-output
  • Additionally, the following command-line arguments are not compatible with multi-core:

    • --format
    • --colorspace
  • Multi-core is also not available when you use cutadapt for demultiplexing.

If you try to use multiple cores with an incompatible commandline option, you will get an error message.

Some of these limitations will be lifted in the future, as time allows.

New in version 1.15.

Read processing

Cutadapt can do a lot more in addition to removing adapters. There are various command-line options that make it possible to modify and filter reads and to redirect them to various output files. Each read is processed in the following way:

  1. Read modification options are applied. This includes adapter removal, quality trimming, read name modifications etc. The order in which they are applied is the order in which they are listed in the help shown by cutadapt --help under the “Additional read modifications” heading. Adapter trimming itself does not appear in that list and is done after quality trimming and before length trimming (--length/-l).
  2. Filtering options are applied, such as removal of too short or untrimmed reads. Some of the filters also allow to redirect a read to a separate output file. The filters are applied in the order in which they are listed in the help shown by cutadapt --help under the “Filtering of processed reads” heading.
  3. If the read has passed all the filters, it is written to the output file.

Removing adapters

Cutadapt supports trimming of multiple types of adapters:

Adapter type Command-line option
3’ adapter -a ADAPTER
5’ adapter -g ADAPTER
Anchored 3’ adapter -a ADAPTER$
Anchored 5’ adapter -g ^ADAPTER
5’ or 3’ (both possible) -b ADAPTER
Linked adapter -a ADAPTER1...ADAPTER2
Non-anchored linked adapter -g ADAPTER1...ADAPTER2

Here is an illustration of the allowed adapter locations relative to the read and depending on the adapter type:


By default, all adapters are searched error-tolerantly. Adapter sequences may also contain any IUPAC wildcard character (such as N).

In addition, it is possible to remove a fixed number of bases from the beginning or end of each read, and to remove low-quality bases (quality trimming) from the 3’ and 5’ ends.

3’ adapters

A 3’ adapter is a piece of DNA ligated to the 3’ end of the DNA fragment you are interested in. The sequencer starts the sequencing process at the 5’ end of the fragment and sequences into the adapter if the read is long enough. The read that it outputs will then have a part of the adapter in the end. Or, if the adapter was short and the read length quite long, then the adapter will be somewhere within the read (followed by other bases).

For example, assume your fragment of interest is MYSEQUENCE and the adapter is ADAPTER. Depending on the read length, you will get reads that look like this:


Use cutadapt’s -a ADAPTER option to remove this type of adapter. This will be the result:


As can be seen, cutadapt correctly deals with partial adapter matches, and also with any trailing sequences after the adapter. Cutadapt deals with 3’ adapters by removing the adapter itself and any sequence that may follow. If the sequence starts with an adapter, like this:


Then the sequence will be empty after trimming. By default, empty reads are kept and will appear in the output.

5’ adapters


Unless your adapter may also occur in a degraded form, you probably want to use an anchored 5’ adapter, described in the next section.

A 5’ adapter is a piece of DNA ligated to the 5’ end of the DNA fragment of interest. The adapter sequence is expected to appear at the start of the read, but may be partially degraded. The sequence may also appear somewhere within the read. In all cases, the adapter itself and the sequence preceding it is removed.

Again, assume your fragment of interest is MYSEQUENCE and the adapter is ADAPTER. The reads may look like this:


All the above sequences are trimmed to MYSEQUENCE when you use -g ADAPTER. As with 3’ adapters, the resulting read may have a length of zero when the sequence ends with the adapter. For example, the read


will be empty after trimming.

Anchored 5’ adapters

In many cases, the above behavior is not really what you want for trimming 5’ adapters. You may know, for example, that degradation does not occur and that the adapter is also not expected to be within the read. Thus, you always expect the read to look like the first example from above:


If you want to trim only this type of adapter, use -g ^ADAPTER. The ^ is supposed to indicate the the adapter is “anchored” at the beginning of the read. In other words: The adapter is expected to be a prefix of the read. Note that cases like these are also recognized:


The read will simply be empty after trimming.

Be aware that cutadapt still searches for adapters error-tolerantly and, in particular, allows insertions. So if your maximum error rate is sufficiently high, even this read will be trimmed:


The B in the beginning is seen as an insertion. If you also want to prevent this from happening, use the option --no-indels to disallow insertions and deletions entirely.

Anchored 3’ adapters

It is also possible to anchor 3’ adapters to the end of the read. This is rarely necessary, but if you have merged, for example, overlapping paired-end reads, then it is useful. Add the $ character to the end of an adapter sequence specified via -a in order to anchor the adapter to the end of the read, such as -a ADAPTER$. The adapter will only be found if it is a suffix of the read, but errors are still allowed as for 5’ adapters. You can disable insertions and deletions with --no-indels.

Anchored 3’ adapters work as if you had reversed the sequence and used an appropriate anchored 5’ adapter.

As an example, assume you have these reads:


Using -a ADAPTER$ will result in:


That is, only the middle read is trimmed at all.

Linked adapters (combined 5’ and 3’ adapter)

If your sequence of interest ist “framed” by a 5’ and a 3’ adapter, and you want to remove both adapters, then you may want to use a linked adapter. A linked adapter combines an anchored 5’ adapter and a 3’ adapter. The 3’ adapter can be regular or anchored. The idea is that a read is only trimmed if the anchored adapters occur. Thus, the 5’ adapter is always required, and if the 3’ adapter was specified as anchored, it also must exist for a successful match.

See the previous sections for what anchoring means.

Use -a ADAPTER1...ADAPTER2 to search for a linked adapter. ADAPTER1 is always interpreted as an anchored 5’ adapter. Here, ADAPTER2 is a regular 3’ adapter. If you write -a ADAPTER1...ADAPTER2$ instead, then the 3’ adapter also becomes anchored, that is, for a read to be trimmed, both adapters must exist at the respective ends.

Note that the ADAPTER1 is always interpreted as an anchored 5’ adapter even though there is no ^ character in the beginning.

In summary:

  • -a ADAPTER1...ADAPTER2: The 5’ adapter is removed if it occurs. If a 3’ adapter occurs, it is removed only when also a 5’ adapter is present.
  • -a ADAPTER1...ADAPTER2$: The adapters are removed only if both occur.

As an example, assume the 5’ adapter is FIRST and the 3’ adapter is SECOND and you have these input reads:


Trimming with

cutadapt -a FIRST...SECOND -o output.fastq input.fastq

will result in


The 3’ adapter in the last read is not trimmed because the read does not contain the 5’ adapter.

This feature does not work when used in combination with some other options, such as --info-file, --mask-adapter.

New in version 1.10.

New in version 1.13: Ability to anchor the 3’ adapter.

Linked adapters without anchoring

This adapter type is especially suited for trimming CRISR screening reads.

Sometimes, the 5’ adapter of a linked adapter pair should not be anchored. It is possible to specify linked adapters also with -g ADAPTER1...ADAPTER2 (note that -g is used instead of -a). These work like the linked adapters described in the previous section, but with these two differences:

  • The 5’ adapter is not anchored by default. (So neither the 5’ nor 3’ adapter are anchored.)
  • Both adapters are required. If one of them is not found, the read is not trimmed.

That is, when you use the –discard-untrimmed` option (or --trimmed-only) with a linked adapter specified with -g, then a read is considered to be trimmed if both adapter parts (5’ and 3’) are present in the read. This is different from linked adapters specified with -a, where a non-anchored 3’ adapter is optional.

This feature has been added on a tentative basis. It may change in the next program version.

New in version 1.13.

Changed in version 1.15: Require both adapters for a read to be trimmed.

Linked adapter statistics

For linked adapters, the statistics report contains a line like this:

=== Adapter 1 ===

Sequence: AAAAAAAAA...TTTTTTTTTT; Type: linked; Length: 9+10; Trimmed: 3 times; Half matches: 2

The value for “Half matches” tells you how often only the 5’-side of the adapter was found, but not the 3’-side of it. This applies only to linked adapters with regular (non-anchored) 3’ adapters.

5’ or 3’ adapters

The last type of adapter is a combination of the 5’ and 3’ adapter. You can use it when your adapter is ligated to the 5’ end for some reads and to the 3’ end in other reads. This probably does not happen very often, and this adapter type was in fact originally implemented because the library preparation in an experiment did not work as it was supposed to.

For this type of adapter, the sequence is specified with -b ADAPTER (or use the longer spelling --anywhere ADAPTER). The adapter may appear in the beginning (even degraded), within the read, or at the end of the read (even partially). The decision which part of the read to remove is made as follows: If there is at least one base before the found adapter, then the adapter is considered to be a 3’ adapter and the adapter itself and everything following it is removed. Otherwise, the adapter is considered to be a 5’ adapter and it is removed from the read, but the sequence after it remains.

Here are some examples.

Read before trimming Read after trimming Detected adapter type
MADAPTER M 3’ adapter

The -b option cannot be used with colorspace data.

Error tolerance

All searches for adapter sequences are error tolerant. Allowed errors are mismatches, insertions and deletions. For example, if you search for the adapter sequence ADAPTER and the error tolerance is set appropriately (as explained below), then also ADABTER will be found (with 1 mismatch), as well as ADAPTR (with 1 deletion), and also ADAPPTER (with 1 insertion).

The level of error tolerance is adjusted by specifying a maximum error rate, which is 0.1 (=10%) by default. Use the -e option to set a different value. To determine the number of allowed errors, the maximum error rate is multiplied by the length of the match (and then rounded off).

What does that mean? Assume you have a long adapter LONGADAPTER and it appears in full somewhere within the read. The length of the match is 11 characters since the full adapter has a length of 11, therefore 11·0.1=1.1 errors are allowed with the default maximum error rate of 0.1. This is rounded off to 1 allowed error. So the adapter will be found within this read:


If the match is a bit shorter, however, the result is different:


Only 9 characters of the adapter match: LONGADAPT matches LONGADUPT with one substitution. Therefore, only 9·0.1=0.9 errors are allowed. Since this is rounded off to zero allowed errors, the adapter will not be found.

The number of errors allowed for a given adapter match length is also shown in the report that cutadapt prints:

Sequence: 'LONGADAPTER'; Length: 11; Trimmed: 2 times.

No. of allowed errors:
0-9 bp: 0; 10-11 bp: 1

This tells us what we now already know: For match lengths of 0-9 bases, zero errors are allowed and for matches of length 10-11 bases, one error is allowed.

The reason for this behavior is to ensure that short matches are not favored unfairly. For example, assume the adapter has 40 bases and the maximum error rate is 0.1, which means that four errors are allowed for full-length matches. If four errors were allowed even for a short match such as one with 10 bases, this would mean that the error rate for such a case is 40%, which is clearly not what was desired.

Insertions and deletions can be disallowed by using the option --no-indels.

See also the section on details of the alignment algorithm.

Multiple adapter occurrences within a single read

If a single read contains multiple copies of the same adapter, the basic rule is that the leftmost match is used for both 5’ and 3’ adapters. For example, when searching for a 3’ adapter in


the read will be trimmed to


When the adapter is a 5’ adapter instead, the read will be trimmed to


The above applies when both occurrences of the adapter are exact matches, and it also applies when both occurrences of the adapter are inexact matches (that is, it has at least one indel or mismatch). However, if one match is exact, but the other is inexact, then the exact match wins, even if it is not the leftmost one! The reason for this behavior is that cutadapt searches for exact matches first and, to improve performance, skips the error-tolerant matching step if an exact match was found.

Reducing random matches

Since cutadapt allows partial matches between the read and the adapter sequence, short matches can occur by chance, leading to erroneously trimmed bases. For example, roughly 25% of all reads end with a base that is identical to the first base of the adapter. To reduce the number of falsely trimmed bases, the alignment algorithm requires that at least three bases match between adapter and read. The minimum overlap length can be changed with the parameter --overlap (or its short version -O). Shorter matches are simply ignored, and the bases are not trimmed.

Requiring at least three bases to match is quite conservative. Even if no minimum overlap was required, we can compute that we lose only about 0.44 bases per read on average, see Section 2.3.3 in my thesis. With the default minimum overlap length of 3, only about 0.07 bases are lost per read.

When choosing an appropriate minimum overlap length, take into account that true adapter matches are also lost when the overlap length is higher than zero, reducing cutadapt’s sensitivity.


All IUPAC nucleotide codes (wildcard characters) are supported. For example, use an N in the adapter sequence to match any nucleotide in the read, or use -a YACGT for an adapter that matches both CACGT and TACGT. The wildcard character N is useful for trimming adapters with an embedded variable barcode:

cutadapt -a ACGTAANNNNTTAGC -o output.fastq input.fastq

Even the X wildcard that does not match any nucleotide is supported. It is useful, for example, as a trick for avoiding internal adapter matches.

Wildcard characters are by default only allowed in adapter sequences and are not recognized when they occur in a read. This is to avoid matches in reads that consist of many (often low-quality) N bases. Use --match-read-wildcards to enable wildcards also in reads.

Use the option -N to disable interpretation of wildcard characters even in the adapters. If wildcards are disabled entirely, that is, when you use -N and do not use --match-read-wildcards, then cutadapt compares characters by their ASCII value. Thus, both the read and adapter can be arbitrary strings (such as SEQUENCE or ADAPTER as used here in the examples).

Wildcards do not work in colorspace.

Repeated bases in the adapter sequence

If you have many repeated bases in the adapter sequence, such as many N s or many A s, you do not have to spell them out. For example, instead of writing ten A in a row (AAAAAAAAAA), write A{10} instead. The number within the curly braces specifies how often the character that preceeds it will be repeated. This works also for IUPAC wildcard characters, as in N{5}.

It is recommended that you use quotation marks around your adapter sequence if you use this feature. For poly-A trimming, for example, you would write:

cutadapt -a "A{100}" -o output.fastq input.fastq

Modifying reads

This section describes in which ways reads can be modified other than adapter removal.

Removing a fixed number of bases

By using the --cut option or its abbreviation -u, it is possible to unconditionally remove bases from the beginning or end of each read. If the given length is positive, the bases are removed from the beginning of each read. If it is negative, the bases are removed from the end.

For example, to remove the first five bases of each read:

cutadapt -u 5 -o trimmed.fastq reads.fastq

To remove the last seven bases of each read:

cutadapt -u -7 -o trimmed.fastq reads.fastq

The -u/--cut option can be combined with the other options, but the --cut is applied before any adapter trimming.

Quality trimming

The -q (or --quality-cutoff) parameter can be used to trim low-quality ends from reads before adapter removal. For this to work correctly, the quality values must be encoded as ascii(phred quality + 33). If they are encoded as ascii(phred quality + 64), you need to add --quality-base=64 to the command line.

Quality trimming can be done without adapter trimming, so this will work:

cutadapt -q 10 -o output.fastq input.fastq

By default, only the 3’ end of each read is quality-trimmed. If you want to trim the 5’ end as well, use the -q option with two comma-separated cutoffs:

cutadapt -q 15,10 -o output.fastq input.fastq

The 5’ end will then be trimmed with a cutoff of 15, and the 3’ end will be trimmed with a cutoff of 10. If you only want to trim the 5’ end, then use a cutoff of 0 for the 3’ end, as in -q 10,0.

Quality trimming of reads using two-color chemistry (NextSeq)

Some Illumina instruments use a two-color chemistry to encode the four bases. This includes the NextSeq and the (at the time of this writing) recently announced NovaSeq. In those instruments, a ‘dark cycle’ (with no detected color) encodes a G. However, dark cycles also occur when when sequencing “falls off” the end of the fragment. The read then contains a run of high-quality, but incorrect ``G` calls <>`_ at its 3’ end.

Since the regular quality-trimming algorithm cannot deal with this situation, you need to use the --nextseq-trim option:

cutadapt --nextseq-trim=20 -o out.fastq input.fastq

This works like regular quality trimming (where one would use -q 20 instead), except that the qualities of G bases are ignored.

New in version 1.10.

Quality trimming algorithm

The trimming algorithm is the same as the one used by BWA, but applied to both ends of the read in turn (if requested). That is: Subtract the given cutoff from all qualities; compute partial sums from all indices to the end of the sequence; cut the sequence at the index at which the sum is minimal. If both ends are to be trimmed, repeat this for the other end.

The basic idea is to remove all bases starting from the end of the read whose quality is smaller than the given threshold. This is refined a bit by allowing some good-quality bases among the bad-quality ones. In the following example, we assume that the 3’ end is to be quality-trimmed.

Assume you use a threshold of 10 and have these quality values:

42, 40, 26, 27, 8, 7, 11, 4, 2, 3

Subtracting the threshold gives:

32, 30, 16, 17, -2, -3, 1, -6, -8, -7

Then sum up the numbers, starting from the end (partial sums). Stop early if the sum is greater than zero:

(70), (38), 8, -8, -25, -23, -20, -21, -15, -7

The numbers in parentheses are not computed (because 8 is greater than zero), but shown here for completeness. The position of the minimum (-25) is used as the trimming position. Therefore, the read is trimmed to the first four bases, which have quality values 42, 40, 26, 27.

Shortening reads to a fixed length

To shorten each read down to a certain length, use the --length option or the short version -l:

cutadapt -l 10 -o output.fastq.gz input.fastq.gz

This shortens all reads from input.fastq.gz down to 10 bases. The removed bases are those on the 3’ end.

If you want to remove a fixed number of bases from each read, use the –cut option instead.

Modifying read names

If you feel the need to modify the names of processed reads, some of the following options may be useful.

Use -y or --suffix to append a text to read names. The given string can contain the placeholder {name}, which will be replaced with the name of the adapter found in that read. For example, writing

cutadapt -a adapter1=ACGT -y ' we found {name}' input.fastq

changes a read named read1 to read1 we found adapter1 if the adapter ACGT was found. The options -x/--prefix work the same, but the text is added in front of the read name. For both options, spaces need to be specified explicitly, as in the above example. If no adapter was found in a read, the text no_adapter is inserted for {name}.

In order to remove a suffix of each read name, use --strip-suffix.

Some old 454 read files contain the length of the read in the name:

>read1 length=17

If you want to update this to the correct length after trimming, use the option --length-tag. In this example, this would be --length-tag 'length='. After trimming, the read would perhaps look like this:

>read1 length=10

Read modification order

The read modifications described above are applied in the following order to each read. Steps not requested on the command-line are skipped.

  1. Unconditional base removal with --cut
  2. Quality trimming (-q)
  3. Adapter trimming (-a, -b, -g and uppercase versions)
  4. Read shortening (--length)
  5. N-end trimming (--trim-n)
  6. Length tag modification (--length-tag)
  7. Read name suffix removal (--strip-suffix)
  8. Addition of prefix and suffix to read name (-x/--prefix and -y/--suffix)
  9. Double-encode the sequence (only colorspace)
  10. Replace negative quality values with zero (zero capping, only colorspace)
  11. Trim primer base (only colorspace)

The last three steps are colorspace-specific.

Filtering reads

By default, all processed reads, no matter whether they were trimmed are not, are written to the output file specified by the -o option (or to standard output if -o was not provided). For paired-end reads, the second read in a pair is always written to the file specified by the -p option.

The options described here make it possible to filter reads by either discarding them entirely or by redirecting them to other files. When redirecting reads, the basic rule is that each read is written to at most one file. You cannot write reads to more than one output file.

In the following, the term “processed read” refers to a read to which all modifications have been applied (adapter removal, quality trimming etc.). A processed read can be identical to the input read if no modifications were done.

--minimum-length LENGTH or -m LENGTH
Discard processed reads that are shorter than LENGTH. Reads that are too short even before adapter removal are also discarded. Without this option, reads that have a length of zero (empty reads) are kept in the output.
--too-short-output FILE
Instead of discarding the reads that are too short according to -m, write them to FILE (in FASTA/FASTQ format).
--maximum-length LENGTH or -M LENGTH
Discard processed reads that are longer than LENGTH. Reads that are too long even before adapter removal are also discarded.
--too-long-output FILE
Instead of discarding reads that are too long (according to -M), write them to FILE (in FASTA/FASTQ format).
--untrimmed-output FILE
Write all reads without adapters to FILE (in FASTA/FASTQ format) instead of writing them to the regular output file.
Discard reads in which an adapter was found.
Discard reads in which no adapter was found. This has the same effect as specifying --untrimmed-output /dev/null.

The options --too-short-output and --too-long-output are applied first. This means, for example, that a read that is too long will never end up in the --untrimmed-output file when --too-long-output was given, no matter whether it was trimmed or not.

The options --untrimmed-output, --discard-trimmed and -discard-untrimmed are mutually exclusive.

Trimming paired-end reads

Cutadapt supports trimming of paired-end reads, trimming both reads in a pair at the same time.

Assume the input is in reads.1.fastq and reads.2.fastq and that ADAPTER_FWD should be trimmed from the forward reads (first file) and ADAPTER_REV from the reverse reads (second file).

The basic command-line is:

cutadapt -a ADAPTER_FWD -A ADAPTER_REV -o out.1.fastq -p out.2.fastq reads.1.fastq reads.2.fastq

-p is the short form of --paired-output. The option -A is used here to specify an adapter sequence that cutadapt should remove from the second read in each pair. There are also the options -G, -B. All of them work just like their lowercase counterparts, except that the adapter is searched for in the second read in each paired-end read. There is also option -U, which you can use to remove a fixed number of bases from the second read in a pair.

While it is possible to run cutadapt on the two files separately, processing both files at the same time is highly recommended since the program can check for problems in your input files only when they are processed together.

When you use -p/--paired-output, cutadapt checks whether the files are properly paired. An error is raised if one of the files contains more reads than the other or if the read names in the two files do not match. Only the part of the read name before the first space is considered. If the read name ends with /1 or /2, then that is also ignored. For example, two FASTQ headers that would be considered to denote properly paired reads are:

@my_read/1 a comment


@my_read/2 another comment

This is an example for improperly paired read names:




Since the /1 and /2 are ignored only if the occur at the end of the read name, and since the ;1 is considered to be part of the read name, these reads will not be considered to be propely paired.

As soon as you start to use one of the filtering options that discard reads, it is mandatory you process both files at the same time to make sure that the output files are kept synchronized: If a read is removed from one of the files, cutadapt will ensure it is also removed from the other file.

The following command-line options are applied to both reads:

  • -q (along with --quality-base)
  • --times applies to all the adapters given
  • --no-trim
  • --trim-n
  • --mask
  • --length
  • --length-tag
  • --prefix, --suffix
  • --strip-f3
  • --colorspace, --bwa, -z, --no-zero-cap, --double-encode, --trim-primer

The following limitations still exist:

  • The --info-file, --rest-file and --wildcard-file options write out information only from the first read.

Filtering paired-end reads

The filtering options listed above can also be used when trimming paired-end data.

Importantly, cutadapt always discards both reads of a pair if it determines that the pair should be discarded. This ensures that the reads in the output files are in sync. (If you don’t want or need this, you can run cutadapt separately on the R1 and R2 files.)

The same applies also to the options that redirect reads to other files if they fulfill a filtering criterion, such as --too-short-output/--too-short-paired-output. That is, the reads are always sent in pairs to these alternative output files.

By default, a read pair is discarded (or redirected) if one of the reads (R1 or R2) fulfills the filtering criterion. As an example, if option --minimum-length=20 is used and paired-end data is processed, a read pair if discarded if one of the reads is shorter than 20 nt.

To require that filtering criteria must apply to both reads in order for a read pair to be discarded, use the option --pair-filter=both. The following table describes the effect for each filtering option.

Filtering option With --pair-filter=any, the pair is discarded if … With -pair-filter=both, the pair is discarded if …
--minimum-length one of the reads is too short both reads are too short
--maximum-length one of the reads is too long both reads are too long
--discard-trimmed one of the reads contains an adapter both reads contain an adapter
--discard-untrimmed one of the reads does not contain an adapter both reads do not contain an adapter
--max-n one of the reads contains too many N bases both reads contain too many N bases

To further complicate matters, cutadapt switches to a backwards compatibility mode (“legacy mode”) when none of the uppercase modification options (-A/-B/-G/-U) are given. In that mode, filtering criteria are checked only for the first read. Cutadapt will also tell you at the top of the report whether legacy mode is active. Check that line if you get strange results!

These are the paired-end specific filtering and output options:

--paired-output FILE or -p FILE
Write the second read of each processed pair to FILE (in FASTA/FASTQ format).
--untrimmed-paired-output FILE
Used together with --untrimmed-output. The second read in a pair is written to this file when the processed pair was not trimmed.
--too-short-paired-output FILE
Write the second read in a pair to this file if pair is too short. Use together with --too-short-output.
--too-long-paired-output FILE
Write the second read in a pair to this file if pair is too long. Use together with --too-long-output.
Which of the reads in a paired-end read have to match the filtering criterion in order for it to be filtered.

Note that the option names can be abbreviated as long as it is clear which option is meant (unique prefix). For example, instead of --untrimmed-output and --untrimmed-paired-output, you can write --untrimmed-o and --untrimmed-p.

Interleaved paired-end reads

Paired-end reads can be read from a single FASTQ file in which the entries for the first and second read from each pair alternate. The first read in each pair comes before the second. Enable this file format by adding the --interleaved option to the command-line. For example:

cutadapt --interleaved -q 20 -a ACGT -A TGCA -o trimmed.fastq reads.fastq

To read from an interleaved file, but write regular two-file output, provide the second output file as usual with the -p option:

cutadapt --interleaved -q 20 -a ACGT -A TGCA -o trimmed.1.fastq -p trimmed.2.fastq reads.fastq

Reading two-file input and writing interleaved is also possible by providing a second input file:

cutadapt --interleaved -q 20 -a ACGT -A TGCA -o trimmed.1.fastq reads.1.fastq reads.2.fastq

Cutadapt will detect if an input file is not properly interleaved by checking whether read names match and whether the file contains an even number of entries.

When --interleaved is used, legacy mode is disabled (that is, read-modification options such as -q always apply to both reads).

Legacy paired-end read trimming


This section describes the way paired-end trimming was done in cutadapt before 1.8, where the -A, -G, -B options were not available. It is less safe and more complicated, but you can still use it.

If you do not use any of the filtering options that discard reads, such as --discard, --minimum-length or --maximum-length, you can run cutadapt on each file separately:

cutadapt -a ADAPTER_FWD -o trimmed.1.fastq reads1.fastq
cutadapt -a ADAPTER_REV -o trimmed.2.fastq reads2.fastq

You can use the options that are listed under ‘Additional modifications’ in cutadapt’s help output without problems. For example, if you want to quality-trim the first read in each pair with a threshold of 10, and the second read in each pair with a threshold of 15, then the commands could be:

cutadapt -q 10 -a ADAPTER_FWD -o trimmed.1.fastq reads1.fastq
cutadapt -q 15 -a ADAPTER_REV -o trimmed.2.fastq reads2.fastq

If you use any of the filtering options, you must use cutadapt in the following way (with the -p option) to make sure that read pairs remain sychronized.

First trim the forward read, writing output to temporary files (we also add some quality trimming):

cutadapt -q 10 -a ADAPTER_FWD --minimum-length 20 -o tmp.1.fastq -p tmp.2.fastq reads.1.fastq reads.2.fastq

Then trim the reverse read, using the temporary files as input:

cutadapt -q 15 -a ADAPTER_REV --minimum-length 20 -o trimmed.2.fastq -p trimmed.1.fastq tmp.2.fastq tmp.1.fastq

Finally, remove the temporary files:

rm tmp.1.fastq tmp.2.fastq

Please see the previous section for a much simpler way of trimming paired-end reads!

In legacy paired-end mode, the read-modifying options such as -q only apply to the first file in each call to cutadapt (first reads.1.fastq, then tmp.2.fastq in this example). Reads in the second file are not affected by those options, but by the filtering options: If a read in the first file is discarded, then the matching read in the second file is also filtered and not written to the output given by --paired-output in order to keep both output files synchronized.

Multiple adapters

It is possible to specify more than one adapter sequence by using the options -a, -b and -g more than once. Any combination is allowed, such as five -a adapters and two -g adapters. Each read will be searched for all given adapters, but only the best matching adapter is removed. (But it is possible to trim more than one adapter from each read). This is how a command may look like to trim one of two possible 3’ adapters:

cutadapt -a TGAGACACGCA -a AGGCACACAGGG -o output.fastq input.fastq

The adapter sequences can also be read from a FASTA file. Instead of giving an explicit adapter sequence, you need to write file: followed by the name of the FASTA file:

cutadapt -a file:adapters.fasta -o output.fastq input.fastq

All of the sequences in the file adapters.fasta will be used as 3’ adapters. The other adapter options -b and -g also support this. Again, only the best matching adapter is trimmed from each read.

When cutadapt has multiple adapter sequences to work with, either specified explicitly on the command line or via a FASTA file, it decides in the following way which adapter should be trimmed:

  • All given adapter sequences are matched to the read.
  • Adapter matches where the overlap length (see the -O parameter) is too small or where the error rate is too high (-e) are removed from further consideration.
  • Among the remaining matches, the one with the greatest number of matching bases is chosen.
  • If there is a tie, the first adapter wins. The order of adapters is the order in which they are given on the command line or in which they are found in the FASTA file.

If your adapter sequences are all similar and differ only by a variable barcode sequence, you should use a single adapter sequence instead that contains wildcard characters.

If you want to search for a combination of a 5’ and a 3’ adapter, you may want to provide them as a single so-called “linked adapter” instead.

Named adapters

Cutadapt reports statistics for each adapter separately. To identify the adapters, they are numbered and the adapter sequence is also printed:

=== Adapter 1 ===

Sequence: AACCGGTT; Length 8; Trimmed: 5 times.

If you want this to look a bit nicer, you can give each adapter a name in this way:

cutadapt -a My_Adapter=AACCGGTT -o output.fastq input.fastq

The actual adapter sequence in this example is AACCGGTT and the name assigned to it is My_Adapter. The report will then contain this name in addition to the other information:

=== Adapter 'My_Adapter' ===

Sequence: TTAGACATATCTCCGTCG; Length 18; Trimmed: 5 times.

When adapters are read from a FASTA file, the sequence header is used as the adapter name.

Adapter names are also used in column 8 of info files.


Cutadapt supports demultiplexing, which means that reads are written to different output files depending on which adapter was found in them. To use this, include the string {name} in the name of the output file and give each adapter a name. The path is then interpreted as a template and each trimmed read is written to the path in which {name} is replaced with the name of the adapter that was found in the read. Reads in which no adapter was found will be written to a file in which {name} is replaced with unknown.


cutadapt -a one=TATA -a two=GCGC -o trimmed-{name}.fastq.gz input.fastq.gz

This command will create the three files demulti-one.fastq.gz, demulti-two.fastq.gz and demulti-unknown.fastq.gz. You can also provide adapter sequences in a FASTA file.

In order to not trim the input files at all, but to only do multiplexing, use option --no-trim. And if you want to output the reads in which no adapters were found to a different file, use the --untrimmed-output parameter with a file name. Here is an example that uses both parameters and reads the adapters from a FASTA file (note that --untrimmed-output can be abbreviated):

cutadapt -a file:barcodes.fasta --no-trim --untrimmed-o untrimmed.fastq.gz -o trimmed-{name}.fastq.gz input.fastq.gz

Here is a made-up example for the barcodes.fasta file:


Demultiplexing is also supported for paired-end data if you provide the {name} template in both output file names (-o and -p). Paired-end demultiplexing always uses the adapter matches of the first read to decide where a read should be written. If adapters to be found in read 2 are given (-A/-G), they are detected and removed as normal, but these matches do not influence where the read pair is written. This is to ensure that read 1 and read 2 are always synchronized. Example:

cutadapt -a first=AACCGG -a second=TTTTGG -A ACGTACGT -A TGCATGCA -o trimmed-{name}.1.fastq.gz -p trimmed-{name}.2.fastq.gz input.1.fastq.gz input.2.fastq.gz

This will create up to six output files named trimmed-first.1.fastq.gz, trimmed-second.1.fastq.gz, trimmed-unknown.1.fastq.gz and trimmed-first.2.fastq.gz, trimmed-second.2.fastq.gz, trimmed-unknown.2.fastq.gz.

You can use --untrimmed-paired-output to change the name for the output file that receives the untrimmed second reads.

New in version 1.15: Demultiplexing of paired-end data.

Trimming more than one adapter from each read

By default, at most one adapter sequence is removed from each read, even if multiple adapter sequences were provided. This can be changed by using the --times option (or its abbreviated form -n). Cutadapt will then search for all the given adapter sequences repeatedly, either until no adapter match was found or until the specified number of rounds was reached.

As an example, assume you have a protocol in which a 5’ adapter gets ligated to your DNA fragment, but it’s possible that the adapter is ligated more than once. So your sequence could look like this:


To be on the safe side, you assume that there are at most five copies of the adapter sequence. This command can be used to trim the reads correctly:

cutadapt -g ^ADAPTER -n 5 -o output.fastq.gz input.fastq.gz

To search for a combination of a 5’ and a 3’ adapter, have a look at the support for “linked adapters” instead, which works better for that particular case because it is allows you to require that the 3’ adapter is trimmed only when the 5’ adapter also occurs, and it cannot happen that the same adapter is trimmed twice.

Before cutadapt supported linked adapters, the --times option was the recommended way to search for 5’/3’ linked adapters. For completeness, we describe how it was done. For example, when the 5’ adapter is FIRST and the 3’ adapter is SECOND, then the read could look like this:


That is, the sequence of interest is framed by the 5’ and the 3’ adapter. The following command can be used to trim such a read:

cutadapt -g ^FIRST -a SECOND -n 2 ...

Illumina TruSeq

If you have reads containing Illumina TruSeq adapters, follow these steps.

Single-end reads as well as the first reads of paired-end data need to be trimmed with A + the “TruSeq Indexed Adapter”. Use only the prefix of the adapter sequence that is common to all Indexed Adapter sequences:

cutadapt -a AGATCGGAAGAGCACACGTCTGAACTCCAGTCAC -o trimmed.fastq.gz reads.fastq.gz

If you have paired-end data, trim also read 2 with the reverse complement of the “TruSeq Universal Adapter”. The full command-line looks as follows:

cutadapt \
            -o trimmed.1.fastq.gz -p trimmed.2.fastq.gz \
            reads.1.fastq.gz reads.2.fastq.gz

See also the section about paired-end adapter trimming above.

If you want to simplify this a bit, you can also use the common prefix AGATCGGAAGAGC as the adapter sequence in both cases. However, you should be aware that this sequence occurs multiple times in the human genome and it could therefore skew your results very slightly at those loci

cutadapt \
            -o trimmed.1.fastq.gz -p trimmed.2.fastq.gz \
            reads.1.fastq.gz reads.2.fastq.gz

The adapter sequences can be found in the document Illumina TruSeq Adapters De-Mystified.

Under some circumstances you may want to consider not trimming adapters at all. If you have whole-exome or whole-genome reads, there will be very few reads with adapters anyway. And if you use BWA-MEM, the trailing (5’) bases of a read that do not match the reference are soft-clipped, which covers those cases in which an adapter does occur.

Warning about incomplete adapter sequences

Sometimes cutadapt’s report ends with these lines:

    One or more of your adapter sequences may be incomplete.
    Please see the detailed output above.

Further up, you’ll see a message like this:

Bases preceding removed adapters:
  A: 95.5%
  C: 1.0%
  G: 1.6%
  T: 1.6%
  none/other: 0.3%
    The adapter is preceded by "A" extremely often.
    The provided adapter sequence may be incomplete.
    To fix the problem, add "A" to the beginning of the adapter sequence.

This means that in 95.5% of the cases in which an adapter was removed from a read, the base coming before that was an A. If your DNA fragments are not random, such as in amplicon sequencing, then this is to be expected and the warning can be ignored. If the DNA fragments are supposed to be random, then the message may be genuine: The adapter sequence may be incomplete and should include an additional A in the beginning.

This warning exists because some documents list the Illumina TruSeq adapters as starting with GATCGGA.... While that is technically correct, the library preparation actually results in an additional A before that sequence, which also needs to be removed. See the previous section for the correct sequence.

Dealing with N bases

Cutadapt supports the following options to deal with N bases in your reads:

--max-n COUNT
Discard reads containing more than COUNT N bases. A fractional COUNT between 0 and 1 can also be given and will be treated as the proportion of maximally allowed N bases in the read.

Remove flanking N bases from each read. That is, a read such as this:


Is trimmed to just ACGTACGT. This option is applied after adapter trimming. If you want to get rid of N bases before adapter removal, use quality trimming: N bases typically also have a low quality value associated with them.

Bisulfite sequencing (RRBS)

When trimming reads that come from a library prepared with the RRBS (reduced representation bisulfite sequencing) protocol, the last two 3’ bases must be removed in addition to the adapter itself. This can be achieved by using not the adapter sequence itself, but by adding two wildcard characters to its beginning. If the adapter sequence is ADAPTER, the command for trimming should be:

cutadapt -a NNADAPTER -o output.fastq input.fastq

Details can be found in Babraham bioinformatics’ “Brief guide to RRBS”. A summary follows.

During RRBS library preparation, DNA is digested with the restriction enzyme MspI, generating a two-base overhang on the 5’ end (CG). MspI recognizes the sequence CCGG and cuts between C and CGG. A double-stranded DNA fragment is cut in this way:


The fragment between two MspI restriction sites looks like this:


Before sequencing (or PCR) adapters can be ligated, the missing base positions must be filled in with GTP and CTP:


The filled-in bases, marked in lowercase above, do not contain any original methylation information, and must therefore not be used for methylation calling. By prefixing the adapter sequence with NN, the bases will be automatically stripped during adapter trimming.

Cutadapt’s output

How to read the report

After every run, cutadapt prints out per-adapter statistics. The output starts with something like this:

Sequence: 'ACGTACGTACGTTAGCTAGC'; Length: 20; Trimmed: 2402 times.

The meaning of this should be obvious.

The next piece of information is this:

No. of allowed errors:
0-7 bp: 0; 8-15 bp: 1; 16-20 bp: 2

The adapter, as was shown above, has a length of 20 characters. We are using a custom error rate of 0.12. What this implies is shown above: Matches up to a length of 7 bp are allowed to have no errors. Matches of lengths 8-15 bp are allowd to have 1 error and matches of length 16 or more can have 2 errors. See also the section about error-tolerant matching.

Finally, a table is output that gives more detailed information about the lengths of the removed sequences. The following is only an excerpt; some rows are left out:

Overview of removed sequences
length  count   expect  max.err error counts
3       140     156.2   0       140
4       57      39.1    0       57
5       50      9.8     0       50
6       35      2.4     0       35
7       13      0.3     0       1 12
8       31      0.1     1       0 31
100     397     0.0     3       358 36 3

The first row tells us the following: Three bases were removed in 140 reads; randomly, one would expect this to occur 156.2 times; the maximum number of errors at that match length is 0 (this is actually redundant since we know already that no errors are allowed at lengths 0-7 bp).

The last column shows the number of reads that had 0, 1, 2 … errors. In the last row, for example, 358 reads matched the adapter with zero errors, 36 with 1 error, and 3 matched with 2 errors.

In the row for length 7 is an apparent anomaly, where the max.err column is 0 and yet we have 31 reads matching with 1 error. This is because the matches are actually contributed by alignments to the first 8 bases of the adapter with one deletion, so 7 bases are removed but the error cut-off applied is for length 8.

The “expect” column gives only a rough estimate of the number of sequences that is expected to match randomly, but it can help to estimate whether the matches that were found are true adapter matches or if they are due to chance. At lengths 6, for example, only 2.4 reads are expected, but 35 do match, which hints that most of these matches are due to actual adapters. For slightly more accurate estimates, you can provide the correct GC content (as a percentage) of your reads with the option --gc-content. The default is --gc-content=50.

Note that the “length” column refers to the length of the removed sequence. That is, the actual length of the match in the above row at length 100 is 20 since that is the adapter length. Assuming the read length is 100, the adapter was found in the beginning of 397 reads and therefore those reads were trimmed to a length of zero.

The table may also be useful in case the given adapter sequence contains an error. In that case, it may look like this:

length  count   expect  max.err error counts
10      53      0.0     1       51 2
11      45      0.0     1       42 3
12      51      0.0     1       48 3
13      39      0.0     1       0 39
14      40      0.0     1       0 40
15      36      0.0     1       0 36

We can see that no matches longer than 12 have zero errors. In this case, it indicates that the 13th base of the given adapter sequence is incorrect.

Format of the info file

When the --info-file command-line parameter is given, detailed information about the found adapters is written to the given file. The output is a tab-separated text file. Each line corresponds to one read of the input file (unless –times is used, see below). A row is written for all reads, even those that are discarded from the final output FASTA/FASTQ due to filtering options (such as --minimum-length).

The fields in each row are:

  1. Read name
  2. Number of errors
  3. 0-based start coordinate of the adapter match
  4. 0-based end coordinate of the adapter match
  5. Sequence of the read to the left of the adapter match (can be empty)
  6. Sequence of the read that was matched to the adapter
  7. Sequence of the read to the right of the adapter match (can be empty)
  8. Name of the found adapter.
  9. Quality values corresponding to sequence left of the adapter match (can be empty)
  10. Quality values corresponding to sequence matched to the adapter (can be empty)
  11. Quality values corresponding to sequence to the right of the adapter match (can be empty)

The concatenation of the fields 5-7 yields the full read sequence. Column 8 identifies the found adapter. The section about named adapters <named-adapters> describes how to give a name to an adapter. Adapters without a name are numbered starting from 1. Fields 9-11 are empty if quality values are not available. Concatenating them yields the full sequence of quality values.

If no adapter was found, the format is as follows:

  1. Read name
  2. The value -1
  3. The read sequence
  4. Quality values

When parsing the file, be aware that additional columns may be added in the future. Note also that some fields can be empty, resulting in consecutive tabs within a line.

If the --times option is used and greater than 1, each read can appear more than once in the info file. There will be one line for each found adapter, all with identical read names. Only for the first of those lines will the concatenation of columns 5-7 be identical to the original read sequence (and accordingly for columns 9-11). For subsequent lines, the shown sequence are the ones that were used in subsequent rounds of adapter trimming, that is, they get successively shorter.

New in version 1.9: Columns 9-11 were added.

The alignment algorithm

Since the publication of the EMBnet journal application note about cutadapt, the alignment algorithm used for finding adapters has changed significantly. An overview of this new algorithm is given in this section. An even more detailed description is available in Chapter 2 of my PhD thesis Algorithms and tools for the analysis of high-throughput DNA sequencing data.

The algorithm is based on semiglobal alignment, also called free-shift, ends-free or overlap alignment. In a regular (global) alignment, the two sequences are compared from end to end and all differences occuring over that length are counted. In semiglobal alignment, the sequences are allowed to freely shift relative to each other and differences are only penalized in the overlapping region between them:


The prefix ELE and the suffix ASTIC do not have a counterpart in the respective other row, but this is not counted as an error. The overlap FANT has a length of four characters.

Traditionally, alignment scores are used to find an optimal overlap aligment: This means that the scoring function assigns a positive value to matches, while mismatches, insertions and deletions get negative values. The optimal alignment is then the one that has the maximal total score. Usage of scores has the disadvantage that they are not at all intuitive: What does a total score of x mean? Is that good or bad? How should a threshold be chosen in order to avoid finding alignments with too many errors?

For cutadapt, the adapter alignment algorithm uses unit costs instead. This means that mismatches, insertions and deletions are counted as one error, which is easier to understand and allows to specify a single parameter for the algorithm (the maximum error rate) in order to describe how many errors are acceptable.

There is a problem with this: When using costs instead of scores, we would like to minimize the total costs in order to find an optimal alignment. But then the best alignment would always be the one in which the two sequences do not overlap at all! This would be correct, but meaningless for the purpose of finding an adapter sequence.

The optimization criteria are therefore a bit different. The basic idea is to consider the alignment optimal that maximizes the overlap between the two sequences, as long as the allowed error rate is not exceeded.

Conceptually, the procedure is as follows:

  1. Consider all possible overlaps between the two sequences and compute an alignment for each, minimizing the total number of errors in each one.
  2. Keep only those alignments that do not exceed the specified maximum error rate.
  3. Then, keep only those alignments that have a maximal number of matches (that is, there is no alignment with more matches).
  4. If there are multiple alignments with the same number of matches, then keep only those that have the smallest error rate.
  5. If there are still multiple candidates left, choose the alignment that starts at the leftmost position within the read.

In Step 1, the different adapter types are taken into account: Only those overlaps that are actually allowed by the adapter type are actually considered.