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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,167 @@ | ||
| using System; | ||
| using System.Linq; | ||
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| namespace Ovation.FasterQC.Net | ||
| { | ||
| public class MultiQC : IQcModule | ||
| { | ||
| private const byte ILLUMINA_BASE_ADJUSTMENT_LOWER = 33; | ||
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| private const byte ILLUMINA_BASE_ADJUSTMENT_UPPER = 126; | ||
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| private int maxReadLength = 0; | ||
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| private ulong sequenceCount = 0; | ||
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| private ulong[][] qualityScoresAtPosition = Array.Empty<ulong[]>(); | ||
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| private uint lowestMean = uint.MaxValue; | ||
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| private uint highestMean = uint.MinValue; | ||
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| private ulong[] nCountsAtPosition = Array.Empty<ulong>(); | ||
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| private readonly ulong[] gcPercentageCounts = new ulong[101]; | ||
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| private readonly ulong[] meanPhredCounts = new ulong[128]; | ||
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| public string Name => "multiqc"; | ||
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| public string Description => "Generates limited / Ovation-branded output compatible with MultiQC"; | ||
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| public bool IsEnabledForAll => true; | ||
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| public ReaderType SupportedReaders => ReaderType.AllReaders; | ||
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| public object Data | ||
| { | ||
| get | ||
| { | ||
| var meanPhreds = new ulong[maxReadLength][]; | ||
| for (var pos = 0; pos < maxReadLength; pos++) | ||
| { | ||
| meanPhreds[pos] = new ulong[128]; | ||
| for (var qual = 0UL; qual < 128; qual++) | ||
| { | ||
| meanPhreds[pos][qual] = qualityScoresAtPosition[pos][qual] * qual; | ||
| } | ||
| } | ||
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| var phreds = meanPhredCounts | ||
| .Skip(ILLUMINA_BASE_ADJUSTMENT_LOWER) | ||
| .Take(ILLUMINA_BASE_ADJUSTMENT_UPPER - ILLUMINA_BASE_ADJUSTMENT_LOWER + 1) | ||
| .ToArray(); | ||
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| return new | ||
| { | ||
| meanPhredByPosition = meanPhreds | ||
| .Select((p, idx) => new { idx, val = (int)(p.Sum(q => (decimal)q) / sequenceCount) }) | ||
| .ToDictionary(i => i.idx + 1, i => i.val), | ||
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| gcPercentageCounts = gcPercentageCounts | ||
| .Select((gcc, idx) => new { idx, gcc }) | ||
| .ToDictionary(i => i.idx, i => i.gcc), | ||
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| gcPercentagePercentage = gcPercentageCounts | ||
| .Select((gcc, idx) => new { idx, val = Math.Round((float)gcc / (float)sequenceCount * 100.0, 3) }) | ||
| .ToDictionary(i => i.idx, i => i.val), | ||
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| nCountsAtPosition = nCountsAtPosition | ||
| .Select((nc, idx) => new { idx, nc }) | ||
| .ToDictionary(i => i.idx + 1, i => i.nc), | ||
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| nPercentageAtPosition = nCountsAtPosition | ||
| .Select((nc, idx) => new { idx, val = Math.Round((float)nc / (float)sequenceCount * 100.0, 3) }) | ||
| .ToDictionary(i => i.idx + 1, i => i.val), | ||
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| meanPhredCounts = meanPhredCounts | ||
| .Skip(ILLUMINA_BASE_ADJUSTMENT_LOWER) | ||
| .Take(ILLUMINA_BASE_ADJUSTMENT_UPPER - ILLUMINA_BASE_ADJUSTMENT_LOWER + 1) | ||
| .Select((val, idx) => new { idx, val }) | ||
| .ToDictionary(i => ILLUMINA_BASE_ADJUSTMENT_LOWER + i.idx, i => i.val), | ||
|
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| meanPhredPercentage = meanPhredCounts | ||
| .Skip(ILLUMINA_BASE_ADJUSTMENT_LOWER) | ||
| .Take(ILLUMINA_BASE_ADJUSTMENT_UPPER - ILLUMINA_BASE_ADJUSTMENT_LOWER + 1) | ||
| .Select((pc, idx) => new { idx, val = Math.Round((float)pc / (float)sequenceCount * 100.0, 3) }) | ||
| .ToDictionary(i => ILLUMINA_BASE_ADJUSTMENT_LOWER + i.idx, i => i.val), | ||
|
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| phreds = phreds | ||
| .Select((val, idx) => new { phred = Convert.ToChar(ILLUMINA_BASE_ADJUSTMENT_LOWER + idx), count = val }) | ||
| .ToDictionary(i => i.phred, i => i.count) | ||
| }; | ||
| } | ||
| } | ||
|
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| public void ProcessSequence(Sequence sequence) | ||
| { | ||
| sequenceCount++; | ||
|
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| var sequenceLength = sequence.Read.Length; | ||
|
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| // see if we need to resize our arrays | ||
| if (sequenceLength > maxReadLength) | ||
| { | ||
| maxReadLength = sequenceLength; | ||
|
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| Array.Resize(ref qualityScoresAtPosition, maxReadLength); | ||
| for (var n = 0; n < maxReadLength; n++) | ||
| { | ||
| if (qualityScoresAtPosition[n] == null) | ||
| { | ||
| qualityScoresAtPosition[n] = new ulong[128]; | ||
| } | ||
| } | ||
| Array.Resize(ref nCountsAtPosition, maxReadLength); | ||
| } | ||
|
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| // calculate mean quality score | ||
| var sum = 0; | ||
| var count = 0; | ||
|
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| var qual = sequence.Quality; | ||
| for (var i = 0; i < sequenceLength; i++) | ||
| { | ||
| byte q = qual[i]; | ||
|
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| qualityScoresAtPosition[i][q]++; | ||
| sum += q; | ||
| count++; | ||
| } | ||
|
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| var mean = (uint)((float)sum / (float)count); | ||
| meanPhredCounts[mean]++; | ||
|
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| lowestMean = Math.Min(lowestMean, mean); | ||
| highestMean = Math.Max(highestMean, mean); | ||
|
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| // calculate the gc percentage and ncount of the read | ||
| var gcCount = 0; | ||
| var read = sequence.Read; | ||
| for (var i = 0; i < sequenceLength; i++) | ||
| { | ||
| switch (read[i]) | ||
| { | ||
| case (byte)'G': | ||
| case (byte)'C': | ||
| gcCount++; | ||
| break; | ||
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| case (byte)'N': | ||
| nCountsAtPosition[i]++; | ||
| break; | ||
|
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| default: | ||
| break; | ||
| } | ||
| } | ||
|
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| var gcPercentage = (int)((float)gcCount / (float)sequenceLength * 100.0); | ||
| gcPercentageCounts[gcPercentage]++; | ||
| } | ||
|
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| public void Reset() | ||
| { | ||
| } | ||
| } | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,86 @@ | ||
| using System; | ||
| using System.Collections.Generic; | ||
| using System.Linq; | ||
|
|
||
| namespace Ovation.FasterQC.Net.Utils | ||
| { | ||
| public static class Statistics | ||
| { | ||
| /// <summary> | ||
| /// Partitions the given list around a pivot element such that all elements on left of pivot are <= pivot | ||
| /// and the ones at thr right are > pivot. This method can be used for sorting, N-order statistics such as | ||
| /// as median finding algorithms. | ||
| /// Pivot is selected ranodmly if random number generator is supplied else its selected as last element in the list. | ||
| /// Reference: Introduction to Algorithms 3rd Edition, Corman et al, pp 171 | ||
| /// </summary> | ||
| private static int Partition<T>(this IList<T> list, int start, int end, Random? rnd = null) where T : IComparable<T> | ||
| { | ||
| if (rnd != null) | ||
| list.Swap(end, rnd.Next(start, end + 1)); | ||
|
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| var pivot = list[end]; | ||
| var lastLow = start - 1; | ||
|
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| for (var i = start; i < end; i++) | ||
| { | ||
| if (list[i].CompareTo(pivot) <= 0) | ||
| list.Swap(i, ++lastLow); | ||
| } | ||
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| list.Swap(end, ++lastLow); | ||
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| return lastLow; | ||
| } | ||
|
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| /// <summary> | ||
| /// Returns Nth smallest element from the list. Here n starts from 0 so that n=0 returns minimum, n=1 returns 2nd smallest element etc. | ||
| /// Note: specified list would be mutated in the process. | ||
| /// Reference: Introduction to Algorithms 3rd Edition, Corman et al, pp 216 | ||
| /// </summary> | ||
| public static T NthOrderStatistic<T>(this IList<T> list, int n, Random? rnd = null) where T : IComparable<T> | ||
| { | ||
| return NthOrderStatistic(list, n, 0, list.Count - 1, rnd); | ||
| } | ||
|
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| private static T NthOrderStatistic<T>(this IList<T> list, int n, int start, int end, Random? rnd) where T : IComparable<T> | ||
| { | ||
| while (true) | ||
| { | ||
| var pivotIndex = list.Partition(start, end, rnd); | ||
| if (pivotIndex == n) | ||
| return list[pivotIndex]; | ||
|
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| if (n < pivotIndex) | ||
| end = pivotIndex - 1; | ||
| else | ||
| start = pivotIndex + 1; | ||
| } | ||
| } | ||
|
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| public static void Swap<T>(this IList<T> list, int i, int j) | ||
| { | ||
| // This check is not required but Partition | ||
| // function may make many calls so it's for perf reason | ||
| if (i == j) | ||
| return; | ||
|
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| (list[j], list[i]) = (list[i], list[j]); | ||
| } | ||
|
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| /// <summary> | ||
| /// Note: specified list would be mutated in the process. | ||
| /// </summary> | ||
| public static T Median<T>(this IList<T> list) where T : IComparable<T> | ||
| { | ||
| return list.NthOrderStatistic((list.Count - 1) / 2); | ||
| } | ||
|
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| public static double Median<T>(this IEnumerable<T> sequence, Func<T, double> getValue) | ||
| { | ||
| var list = sequence.Select(getValue).ToList(); | ||
| var mid = (list.Count - 1) / 2; | ||
|
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| return list.NthOrderStatistic(mid); | ||
| } | ||
| } | ||
| } |