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1 # sickle - A windowed adaptive trimming tool for FASTQ files using quality
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2
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3 ## About
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4
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5 Most modern sequencing technologies produce reads that have
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6 deteriorating quality towards the 3'-end and some towards the 5'-end as well. Incorrectly called bases
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7 in both regions negatively impact assembles, mapping, and downstream
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8 bioinformatics analyses.
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9
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10 Sickle is a tool that uses sliding windows along with quality and
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11 length thresholds to determine when quality is sufficiently low to
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12 trim the 3'-end of reads and also determines when the quality is
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13 sufficiently high enough to trim the 5'-end of reads. It will also discard reads based upon the
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14 length threshold. It takes the quality values and slides a window
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15 across them whose length is 0.1 times the length of the read. If this
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16 length is less than 1, then the window is set to be equal to the
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17 length of the read. Otherwise, the window slides along the quality
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18 values until the average quality in the window rises above the threshold, at
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19 which point the algorithm determines where within the window the rise occurs
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20 and cuts the read and quality there for the 5'-end cut. Then when the average quality
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21 in the window drops below the threshold, the algorithm determines where in the window
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22 the drop occurs and cuts both the read and quality strings there for the 3'-end cut.
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23 However, if the length of the remaining sequence is less than the minimum length threshold,
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24 then the read is discarded entirely. 5'-end trimming can be disabled.
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25
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26 Sickle also has an option to discard reads with any Ns in them.
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27
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28 Sickle supports three types of quality values: Illumina, Solexa,
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29 and Sanger. Note that the Solexa quality setting is an approximation
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30 (the actual conversion is a non-linear transformation). The end
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31 approximation is close. Illumina quality refers to qualities encoded
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32 with the CASAVA pipeline between versions 1.3 and 1.7. Illumina quality
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33 using CASAVA >= 1.8 is Sanger encoded.
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34
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35 Note that Sickle will remove the 2nd fastq record header (on the "+" line) and replace it
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36 with simply a "+". This is the default format for CASAVA >= 1.8.
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37
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38 Sickle also supports gzipped file inputs. There is also a sickle.xml file
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39 included in the package that can be used to add sickle to your local [Galaxy](http://galaxy.psu.edu/) server.
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40
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41 ## Requirements
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42
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43 Sickle requires a C compiler; GCC or clang are recommended. Sickle
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44 relies on Heng Li's kseq.h, which is bundled with the source.
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45
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46 Sickle also requires Zlib, which can be obtained at
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47 <http://www.zlib.net/>.
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48
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49 ## Building and Installing Sickle
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50
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51 To build Sickle, enter:
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52
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53 make
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54
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55 Then, copy or move "sickle" to a directory in your $PATH.
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56
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57 ## Usage
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58
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59 Sickle has two modes to work with both paired-end and single-end
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60 reads: `sickle se` and `sickle pe`.
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61
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62 Running sickle by itself will print the help:
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63
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64 sickle
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65
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66 Running sickle with either the "se" or "pe" commands will give help
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67 specific to those commands:
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68
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69 sickle se
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70 sickle pe
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71
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72 ### Sickle Single End (`sickle se`)
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73
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74 `sickle se` takes an input fastq file and outputs a trimmed version of
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75 that file. It also has options to change the length and quality
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76 thresholds for trimming, as well as disabling 5'-trimming and enabling removal
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77 of sequences with Ns.
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78
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79 #### Examples
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80
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81 sickle se -f input_file.fastq -t illumina -o trimmed_output_file.fastq
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82 sickle se -f input_file.fastq -t illumina -o trimmed_output_file.fastq -q 33 -l 40
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83 sickle se -f input_file.fastq -t illumina -o trimmed_output_file.fastq -x -n
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84
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85 ### Sickle Paired End (`sickle pe`)
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86
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87 `sickle pe` takes two paired-end files as input and outputs two
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88 trimmed paired-end files as well as a "singles" file. The "singles"
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89 file contains reads that passed filter in one of the paired-end files
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90 but not the other. You can also change the length and quality
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91 thresholds for trimming, as well as disable 5'-trimming and enable removal
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92 of sequences with Ns.
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93
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94 #### Examples
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95
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96 sickle pe -f input_file1.fastq -r input_file2.fastq -t sanger \
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97 -o trimmed_output_file1.fastq -p trimmed_output_file2.fastq \
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98 -s trimmed_singles_file.fastq
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99
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100 sickle pe -f input_file1.fastq -r input_file2.fastq -t sanger \
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101 -o trimmed_output_file1.fastq -p trimmed_output_file2.fastq \
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102 -s trimmed_singles_file.fastq -q 12 -l 15
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103
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104 sickle pe -f input_file1.fastq -r input_file2.fastq -t sanger \
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105 -o trimmed_output_file1.fastq -p trimmed_output_file2.fastq \
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106 -s trimmed_singles_file.fastq -n
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107
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