![]() Rcgrep is a lightweight wrapper for the UNIX grep command and is intended to make these irrelevant details disappear as much as possible. Searching for DNA sequences in text files is a very simple task that too often is unnecessarily complicated by uninteresting and frustrating technical details. ME, HEAD ON DESK: Uggghh, bzgrep on Linux doesn't support multiple -e flags. ME, 5 MINUTES LATER: This time I want to search a different file (bzip2-compressed) for 3 sequences and their reverse complements. ME AGAIN: Oops, I forgot to search for the sequence's reverse complement as well. I'll use grep.ĪLSO ME: Oh, the file is gzip-compressed. ME: I just need to search for a sequence in this text file real quick. There are circumstances in which this extra work is justified, but many times you just need a flexible tool to do a quick-n-dirty search.Ĭonsider the following, totally not-real never-happened-to-me hypothetical situation. If input files are compressed in a certain way, or stored in a non-standard format, there is usually some non-trivial work and storage involved in converting the data to a format the software will accept. Trimmed_sequences_ (324.There are many wonderfully elegant and efficient tools for performing all sorts of exact and inexact searches on large collections of DNA sequences.Įxperience has shown, however, that these tools are usually very rigid with respect to their assumptions about input data. Qiime cutadapt trim-paired -i-demultiplexed-sequences analysis/seqs/combined_seqs.qza -p-adapter-f GCATCGATGAAGAACGCAGC -p-front-f CTTGGTCATTTAGAGGAAGTAA -output-dir analysis/seqs_trimmed_both-f qiime demux summarize -i-data analysis/seqs_trimmed_both-f/trimmed_sequences.qza -o-visualization analysis/visualisations/trimmed_sequences_both-f.qza However, when I run the two parameters at the same time, it seems not to trim the reverse complement ( Demultiplexed sequence length summary). Qiime demux summarize -i-data analysis/seqs_trimmed_CTTGGTCATTTAGAGGAAGTAA/trimmed_sequences.qza -o-visualization analysis/visualisations/trimmed_sequences_CTTGGTCATTTAGAGGAAGTAA.qza Trimmed_sequences_ (324.6 KB) qiime cutadapt trim-paired -i-demultiplexed-sequences analysis/seqs/combined_seqs.qza -p-front-f CTTGGTCATTTAGAGGAAGTAA -output-dir analysis/seqs_trimmed_CTTGGTCATTTAGAGGAAGTAA Qiime demux summarize -i-data analysis/seqs_trimmed_GCATCGATGAAGAACGCAGC/trimmed_sequences.qza -o-visualization analysis/visualisations/trimmed_sequences_GCATCGATGAAGAACGCAGC.qza I then ran cutadapt with the parameters on their own to see what the results would be and they seem to trim the data accordingly (again looking at the Demultiplexed sequence length summary): qiime cutadapt trim-paired -i-demultiplexed-sequences analysis/seqs/combined_seqs.qza -p-adapter-f GCATCGATGAAGAACGCAGC -output-dir analysis/seqs_trimmed_GCATCGATGAAGAACGCAGC o-visualization analysis/visualisations/trimmed_sequences.qzvĪfter running cutadapt above, I was surprised that more sequence in my forward reads had not been trimmed as shown in Demultiplexed sequence length summary (based on what I'd seen in my grep command). ![]() i-data analysis/seqs_trimmed/trimmed_sequences.qza \ i-demultiplexed-sequences analysis/seqs/combined_seqs.qza \ #reverse complement of the reverse primer: GCATCGATGAAGAACGCAGC qiime cutadapt trim-paired \ #Reverse complement of forward primer: TTACTTCCTCTAAATGACCAAG o-visualization analysis/visualisations/combined_seq.qzv i-data analysis/seqs/combined_seqs.qza \ output-path analysis/seqs/combined_seqs.qza input-format CasavaOneEightSingleLanePerSampleDirFmt \ I imported the data and can see that the reads are 300bps as they should be (pre-trimming): qiime tools import \ I then ran cutadapt to remove these and am a little confused by the results. I did a "grep" of the primer sequences (and reverse-complement) my raw sequences and can see that I have read-through. I'm running qiime2-2021.8 (Conda install) on some ITS data and following along with this tutorial: tutorial.
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