annotate README.md @ 7:c8e22efcaeda draft

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date Wed, 24 Jul 2024 08:49:37 +0000
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1 ## bigwig peak bed maker
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3 ### July 30 2024 for the VGP
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5 This is a Galaxy tool, for building some of the [NIH MARBL T2T assembly polishing](https://github.com/marbl/training) tools as Galaxy workflows.
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7 JBrowse2 2.12.3 update will include a plugin for optional colours to distinguish bed features, shown being tested in the screenshots below.
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9 ### Find and mark BigWig peaks to a bed file for display
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11 In the spirit of DeepTools, but finding contiguous regions where the bigwig value is either above or below a given centile.
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12 0.99 and 0.01 for example. These quantile cut point values are found and applied over each chromosome using some [cunning numpy code](http://gregoryzynda.com/python/numpy/contiguous/interval/2019/11/29/contiguous-regions.html)
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14 ![image](https://github.com/fubar2/bigwig_peak_bed/assets/6016266/cdee3a2b-ae31-4282-b744-992c15fb49db)
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16 ![image](https://github.com/fubar2/bigwig_peak_bed/assets/6016266/59d1564b-0c34-42a3-b437-44332cf1b2f0)
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18 Big differences between chromosomes 14,15,21,22 and Y in this "all contigs" view - explanations welcomed:
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20 ![image](https://github.com/fubar2/bigwig_peak_bed/assets/6016266/162bf681-2977-4eb8-8d6f-9dad5b3931f8)
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23 [pybedtools](https://github.com/jackh726/bigtools) is used for the bigwig interface. Optionally allow
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24 multiple bigwigs to be processed into a single bed - the bed features have the bigwig name in the label for viewing.
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26 ### Note on quantiles per chromosome rather than quantiles for the whole bigwig
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28 It is just not feasible to hold all contigs in the entire decoded bigwig in RAM to estimate quantiles. It may be
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29 better to sample across all chromosomes so as not to lose any systematic differences between them - the current method will hide those
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30 differences unfortunately. Sampling might be possible. Looking at the actual quantile values across a couple of test bigwigs suggests that
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31 there is not much variation between chromosomes but there's now a tabular report to check them for each input bigwig.
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33 ### Table reports
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35 The optional table output report gives a crude histogram and the top/bottom 10 values to help
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36 understand what is likely to be informative. In this example, there are 26700 zero values so
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37 using a lower cutoff quantile is likely to have a lot of them, although a large window requirement
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38 will decease the overload...
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39
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40 Descriptive measures
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41 bigwig test
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42 contig chr10_PATERNAL
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43 n 135711693
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44 mean 12.178164
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45 std 7.997467
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46 min 0.000000
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47 max 365.000000
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48 qtop 364.00
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49 qbot noqlo
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50 First/Last 10 value counts
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51 Value Count
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52 0.00 26700
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53 1.00 82900
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54 2.00 261400
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55 3.00 676993
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56 4.00 1665500
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57 5.00 3125700
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58 6.00 5078000
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59 7.00 7469000
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60 8.00 10191700
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61 9.00 12544600
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62 355.00 100
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63 356.00 100
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64 357.00 300
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65 358.00 100
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66 360.00 500
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67 361.00 300
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68 362.00 200
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69 363.00 600
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70 364.00 900
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71 365.00 700
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72 Histogram of bigwig values
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73 chr10_PATERNAL 18.25 | 127,047,593 | **************************************************************************
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74 chr10_PATERNAL 36.50 | 7,510,000 | ****
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75 chr10_PATERNAL 54.75 | 818,900 |
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76 chr10_PATERNAL 73.00 | 117,200 |
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77 chr10_PATERNAL 91.25 | 51,900 |
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78 chr10_PATERNAL 109.50 | 44,200 |
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79 chr10_PATERNAL 127.75 | 21,600 |
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80 chr10_PATERNAL 146.00 | 17,900 |
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81 chr10_PATERNAL 164.25 | 16,400 |
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82 chr10_PATERNAL 182.50 | 18,600 |
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83 chr10_PATERNAL 200.75 | 5,400 |
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84 chr10_PATERNAL 219.00 | 6,600 |
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85 chr10_PATERNAL 237.25 | 6,200 |
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86 chr10_PATERNAL 255.50 | 3,900 |
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87 chr10_PATERNAL 273.75 | 4,500 |
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88 chr10_PATERNAL 292.00 | 7,100 |
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89 chr10_PATERNAL 310.25 | 3,000 |
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90 chr10_PATERNAL 328.50 | 2,700 |
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91 chr10_PATERNAL 346.75 | 3,500 |
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92 chr10_PATERNAL 365.00 | 4,500 |
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93 chr10_PATERNAL ------------ |------------ |
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94 chr10_PATERNAL N= | 135,711,693 |
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95 chr10_PATERNAL ------------ |------------ |
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96
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97