case class SampleBarcodeMetric(barcode_name: String = "", library_name: String = "", barcode: String = "", templates: Count = 0, pf_templates: Count = 0, perfect_matches: Count = 0, pf_perfect_matches: Count = 0, one_mismatch_matches: Count = 0, pf_one_mismatch_matches: Count = 0, fraction_matches: Proportion = 0d, ratio_this_barcode_to_best_barcode: Proportion = 0d, pf_fraction_matches: Proportion = 0d, pf_ratio_this_barcode_to_best_barcode: Proportion = 0d, pf_normalized_matches: Proportion = 0d) extends Metric with Product with Serializable
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).
- barcode_name
the name for the sample barcode, typically the sample name from the SampleSheet.
- library_name
the name of the library, typically the library identifier from the SampleSheet.
- barcode
the sample barcode bases. Dual index barcodes will have two sample barcode sequences delimited by a dash.
- templates
the total number of templates matching the given barcode.
- pf_templates
the total number of pass-filter templates matching the given barcode.
- perfect_matches
the number of templates that match perfectly the given barcode.
- pf_perfect_matches
the number of pass-filter templates that match perfectly the given barcode.
- one_mismatch_matches
the number of pass-filter templates that match the given barcode with exactly one mismatch.
- pf_one_mismatch_matches
the number of pass-filter templates that match the given barcode with exactly one mismatch.
- fraction_matches
the fraction of all templates that match the given barcode.
- 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.
- pf_fraction_matches
the fraction of all pass-filter templates that match the given barcode.
- 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.
- 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 1.
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new
SampleBarcodeMetric(barcode_name: String = "", library_name: String = "", barcode: String = "", templates: Count = 0, pf_templates: Count = 0, perfect_matches: Count = 0, pf_perfect_matches: Count = 0, one_mismatch_matches: Count = 0, pf_one_mismatch_matches: Count = 0, fraction_matches: Proportion = 0d, ratio_this_barcode_to_best_barcode: Proportion = 0d, pf_fraction_matches: Proportion = 0d, pf_ratio_this_barcode_to_best_barcode: Proportion = 0d, pf_normalized_matches: Proportion = 0d)
- barcode_name
the name for the sample barcode, typically the sample name from the SampleSheet.
- library_name
the name of the library, typically the library identifier from the SampleSheet.
- barcode
the sample barcode bases. Dual index barcodes will have two sample barcode sequences delimited by a dash.
- templates
the total number of templates matching the given barcode.
- pf_templates
the total number of pass-filter templates matching the given barcode.
- perfect_matches
the number of templates that match perfectly the given barcode.
- pf_perfect_matches
the number of pass-filter templates that match perfectly the given barcode.
- one_mismatch_matches
the number of pass-filter templates that match the given barcode with exactly one mismatch.
- pf_one_mismatch_matches
the number of pass-filter templates that match the given barcode with exactly one mismatch.
- fraction_matches
the fraction of all templates that match the given barcode.
- 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.
- pf_fraction_matches
the fraction of all pass-filter templates that match the given barcode.
- 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.
- 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 1.
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ensuring(cond: (SampleBarcodeMetric) ⇒ Boolean, msg: ⇒ Any): SampleBarcodeMetric
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Increments the counts for the metric.
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iterator: Iterator[(String, String)]
Gets an iterator over the fields of this metric in the order they were defined.
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- var perfect_matches: Count
- var pf_fraction_matches: Proportion
- var pf_normalized_matches: Proportion
- var pf_one_mismatch_matches: Count
- var pf_perfect_matches: Count
- var pf_ratio_this_barcode_to_best_barcode: Proportion
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-
def
toStream: Stream[(String, String)]
- Definition Classes
- IterableLike → TraversableLike → GenTraversableOnce
-
def
toString(): String
- Definition Classes
- Metric → TraversableLike → AnyRef → Any
-
def
toTraversable: Traversable[(String, String)]
- Definition Classes
- TraversableLike → TraversableOnce → GenTraversableOnce
- Annotations
- @deprecatedOverriding( ... , "2.11.0" )
-
def
toVector: Vector[(String, String)]
- Definition Classes
- TraversableOnce → GenTraversableOnce
-
def
transpose[B](implicit asTraversable: ((String, String)) ⇒ GenTraversableOnce[B]): Iterable[Iterable[B]]
- Definition Classes
- GenericTraversableTemplate
- Annotations
- @migration
- Migration
(Changed in version 2.9.0)
transpose
throws anIllegalArgumentException
if collections are not uniformly sized.
-
def
unzip[A1, A2](implicit asPair: ((String, String)) ⇒ (A1, A2)): (Iterable[A1], Iterable[A2])
- Definition Classes
- GenericTraversableTemplate
-
def
unzip3[A1, A2, A3](implicit asTriple: ((String, String)) ⇒ (A1, A2, A3)): (Iterable[A1], Iterable[A2], Iterable[A3])
- Definition Classes
- GenericTraversableTemplate
-
def
values: Seq[String]
Get the values of the arguments in the order they were defined.
Get the values of the arguments in the order they were defined.
- Definition Classes
- Metric
-
def
view(from: Int, until: Int): IterableView[(String, String), Iterable[(String, String)]]
- Definition Classes
- IterableLike → TraversableLike
-
def
view: IterableView[(String, String), Iterable[(String, String)]]
- Definition Classes
- IterableLike → TraversableLike
-
final
def
wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
final
def
wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
final
def
wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
def
withFilter(p: ((String, String)) ⇒ Boolean): FilterMonadic[(String, String), Iterable[(String, String)]]
- Definition Classes
- TraversableLike → FilterMonadic
-
def
zip[A1 >: (String, String), B, That](that: GenIterable[B])(implicit bf: CanBuildFrom[Iterable[(String, String)], (A1, B), That]): That
- Definition Classes
- IterableLike → GenIterableLike
-
def
zipAll[B, A1 >: (String, String), That](that: GenIterable[B], thisElem: A1, thatElem: B)(implicit bf: CanBuildFrom[Iterable[(String, String)], (A1, B), That]): That
- Definition Classes
- IterableLike → GenIterableLike
-
def
zipWithIndex[A1 >: (String, String), That](implicit bf: CanBuildFrom[Iterable[(String, String)], (A1, Int), That]): That
- Definition Classes
- IterableLike → GenIterableLike
-
def
→[B](y: B): (SampleBarcodeMetric, B)
- Implicit
- This member is added by an implicit conversion from SampleBarcodeMetric to ArrowAssoc[SampleBarcodeMetric] performed by method ArrowAssoc in scala.Predef.
- Definition Classes
- ArrowAssoc
Shadowed Implicit Value Members
-
def
filter(p: ((String, String)) ⇒ Boolean): TraversableOnce[(String, String)]
- Implicit
- This member is added by an implicit conversion from SampleBarcodeMetric to MonadOps[(String, String)] performed by method MonadOps in scala.collection.TraversableOnce.
- Shadowing
- This implicitly inherited member is shadowed by one or more members in this class.
To access this member you can use a type ascription:(sampleBarcodeMetric: MonadOps[(String, String)]).filter(p)
- Definition Classes
- MonadOps
-
def
flatMap[B](f: ((String, String)) ⇒ GenTraversableOnce[B]): TraversableOnce[B]
- Implicit
- This member is added by an implicit conversion from SampleBarcodeMetric to MonadOps[(String, String)] performed by method MonadOps in scala.collection.TraversableOnce.
- Shadowing
- This implicitly inherited member is shadowed by one or more members in this class.
To access this member you can use a type ascription:(sampleBarcodeMetric: MonadOps[(String, String)]).flatMap(f)
- Definition Classes
- MonadOps
-
def
map[B](f: ((String, String)) ⇒ B): TraversableOnce[B]
- Implicit
- This member is added by an implicit conversion from SampleBarcodeMetric to MonadOps[(String, String)] performed by method MonadOps in scala.collection.TraversableOnce.
- Shadowing
- This implicitly inherited member is shadowed by one or more members in this class.
To access this member you can use a type ascription:(sampleBarcodeMetric: MonadOps[(String, String)]).map(f)
- Definition Classes
- MonadOps
-
def
withFilter(p: ((String, String)) ⇒ Boolean): Iterator[(String, String)]
- Implicit
- This member is added by an implicit conversion from SampleBarcodeMetric to MonadOps[(String, String)] performed by method MonadOps in scala.collection.TraversableOnce.
- Shadowing
- This implicitly inherited member is shadowed by one or more members in this class.
To access this member you can use a type ascription:(sampleBarcodeMetric: MonadOps[(String, String)]).withFilter(p)
- Definition Classes
- MonadOps