com.fulcrumgenomics.util.SampleBarcodeMetric.scala Maven / Gradle / Ivy
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/*
* The MIT License
*
* Copyright (c) 2016 Fulcrum Genomics LLC
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
* THE SOFTWARE.
*
*/
package com.fulcrumgenomics.util
object SampleBarcodeMetric {
def apply(barcodeName: String, libraryName: String, barcode: String): SampleBarcodeMetric = {
new SampleBarcodeMetric(barcode_name=barcodeName, library_name=libraryName, barcode=barcode)
}
/** Computes values that are require the summary counts across multiple barcode metrics, such as certain fractions.
*
* @param barcodeToMetrics the map in which barcode metrics per sample are stored.
* @param noMatchBarcode the barcode for the unmatched templates. This should stored in `barcodeToMetrics`.
*/
def finalizeMetrics(barcodeToMetrics: Map[String, SampleBarcodeMetric],
noMatchBarcode: String): Unit = {
val noMatchMetric = barcodeToMetrics(noMatchBarcode)
var totalReads: Long = 0
var totalPfReads: Long = 0
var totalPfReadsAssigned: Long = 0
var totalBases: Long = 0
barcodeToMetrics.foreach { case (_, metric) =>
totalReads += metric.templates
totalPfReads += metric.pf_templates
totalPfReadsAssigned += metric.pf_templates
totalBases += metric.total_number_of_bases
}
if (totalReads > 0) {
noMatchMetric.fraction_matches = noMatchMetric.templates / totalReads.toDouble
var bestPctOfAllBarcodeMatches: Double = 0
barcodeToMetrics.foreach { case (_, metric) =>
val fracMatches = metric.templates / totalReads.toDouble
if (fracMatches > bestPctOfAllBarcodeMatches) {
bestPctOfAllBarcodeMatches = fracMatches
}
metric.fraction_matches = fracMatches
}
if (bestPctOfAllBarcodeMatches > 0) {
noMatchMetric.ratio_this_barcode_to_best_barcode = noMatchMetric.fraction_matches / bestPctOfAllBarcodeMatches
barcodeToMetrics.foreach { case (_, metric) =>
metric.ratio_this_barcode_to_best_barcode = metric.fraction_matches / bestPctOfAllBarcodeMatches
}
}
}
if (totalPfReads > 0) {
var bestPfPctOfAllBarcodeMatches: Double = 0
barcodeToMetrics.foreach { case (_, metric) =>
val fracPfMatches = metric.pf_templates / totalPfReads.toDouble
if (fracPfMatches > bestPfPctOfAllBarcodeMatches) {
bestPfPctOfAllBarcodeMatches = fracPfMatches
}
metric.pf_fraction_matches = fracPfMatches
}
if (bestPfPctOfAllBarcodeMatches > 0) {
noMatchMetric.pf_ratio_this_barcode_to_best_barcode = noMatchMetric.pf_fraction_matches / bestPfPctOfAllBarcodeMatches
barcodeToMetrics.foreach { case (_, metric) =>
metric.pf_ratio_this_barcode_to_best_barcode = metric.pf_fraction_matches / bestPfPctOfAllBarcodeMatches
}
}
}
if (totalPfReadsAssigned > 0) {
val mean: Double = totalPfReadsAssigned.toDouble / barcodeToMetrics.values.size.toDouble
barcodeToMetrics.foreach { case (_, metric) =>
metric.pf_normalized_matches = metric.pf_templates / mean
}
}
if (totalBases > 0) {
barcodeToMetrics.foreach { case (_, metric) =>
if (metric.total_number_of_bases > 0) {
metric.frac_q20_bases = metric.q20_bases / metric.total_number_of_bases.toDouble
metric.frac_q30_bases = metric.q30_bases / metric.total_number_of_bases.toDouble
}
}
}
}
}
/**
* Metrics for matching templates to sample barcodes primarily used in [[com.fulcrumgenomics.fastq.DemuxFastqs]].
*
* The number of templates will match the number of reads for an Illumina single-end sequencing run, while the number
* of templates will be half the number of reads for an Illumina paired-end sequencing run (i.e. R1 & R2 observe the
* same template).
*
* @param barcode_name the name for the sample barcode, typically the sample name from the SampleSheet.
* @param library_name the name of the library, typically the library identifier from the SampleSheet.
* @param barcode the sample barcode bases. Dual index barcodes will have two sample barcode sequences delimited by a
* dash.
* @param templates the total number of templates matching the given barcode.
* @param pf_templates the total number of pass-filter templates matching the given barcode.
* @param perfect_matches the number of templates that match perfectly the given barcode.
* @param pf_perfect_matches the number of pass-filter templates that match perfectly the given barcode.
* @param one_mismatch_matches the number of pass-filter templates that match the given barcode with exactly one
* mismatch.
* @param pf_one_mismatch_matches the number of pass-filter templates that match the given barcode with exactly
* one mismatch.
* @param q20_bases the number of bases in a template with a quality score 20 or above
* @param q30_bases the number of bases in a template with a quality score 30 or above
* @param total_number_of_bases the total number of bases in the templates combined
* @param fraction_matches the fraction of all templates that match the given barcode.
* @param ratio_this_barcode_to_best_barcode the rate of all templates matching this barcode to all template
* reads matching the most prevalent barcode. For the most prevalent
* barcode this will be 1, for all others it will be less than 1 (except
* for the possible exception of when there are more unmatched templates
* than for any other barcode, in which case the value may be arbitrarily
* large). One over the lowest number in this column gives you the
* fold-difference in representation between barcodes.
* @param pf_fraction_matches the fraction of all pass-filter templates that match the given barcode.
* @param pf_ratio_this_barcode_to_best_barcode the rate of all pass-filter templates matching this barcode to
* all templates matching the most prevalent barcode. For the
* most prevalent barcode this will be 1, for all others it will be
* less than 1 (except for the possible exception of when there are
* more unmatched templates than for any other barcode, in which
* case the value may be arbitrarily large). One over the lowest
* number in this column gives you the fold-difference in
* representation between barcodes.
* @param pf_normalized_matches The "normalized" matches to each barcode. This is calculated as the number of
* pass-filter templates matching this barcode over the mean of all pass-filter
* templates matching any barcode (excluding unmatched). If all barcodes are
* represented equally this will be
* @param frac_q20_bases the fraction of bases in a template with a quality score 20 or above
* @param frac_q30_bases the fraction of bases in a template with a quality score 30 or above
*/
case class SampleBarcodeMetric
( var barcode_name: String = "",
var library_name: String = "",
var barcode: String = "",
var templates: Metric.Count = 0,
var pf_templates: Metric.Count = 0,
var perfect_matches: Metric.Count = 0,
var pf_perfect_matches: Metric.Count = 0,
var one_mismatch_matches: Metric.Count = 0,
var pf_one_mismatch_matches: Metric.Count = 0,
var q20_bases: Metric.Count = 0,
var q30_bases: Metric.Count = 0,
var total_number_of_bases: Metric.Count = 0,
var fraction_matches: Metric.Proportion = 0d,
var ratio_this_barcode_to_best_barcode: Metric.Proportion = 0d,
var pf_fraction_matches: Metric.Proportion = 0d,
var pf_ratio_this_barcode_to_best_barcode: Metric.Proportion = 0d,
var pf_normalized_matches: Metric.Proportion = 0d,
var frac_q20_bases: Metric.Proportion = 0d,
var frac_q30_bases: Metric.Proportion = 0d
) extends Metric {
/** Increments the counts for a metric
*
* @param numMismatches number of mismatches
* @param isPf true if the template passes QC
* @param basesToAdd number of total bases in the record
* @param q20Bases number of bases that have a quality score of 20 or higher
* @param q30Bases number of bases that have a quality score of 30 or higher
* @param omitFailing if failing reads are to be omitted from the output
*/
def increment(numMismatches: Int,
isPf: Boolean = true,
basesToAdd: Int,
q20Bases: Int,
q30Bases: Int,
omitFailing: Boolean): Unit = {
this.templates += 1
if (isPf) this.pf_templates += 1
if (numMismatches == 0) {
this.perfect_matches += 1
if (isPf) this.pf_perfect_matches += 1
}
else if (numMismatches == 1) {
this.one_mismatch_matches += 1
if (isPf) this.pf_one_mismatch_matches += 1
}
if (isPf || !omitFailing) {
this.total_number_of_bases += basesToAdd
this.q20_bases += q20Bases
this.q30_bases += q30Bases
}
}
}
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