Type Members

1.  class CollectErccMetrics extends FgBioTool with LazyLogging

   Annotations

   @ClpAnnotation()

2.  case class ErccDetailedMetric (name: String, concentration: Double, count: Long, normalized_count: Double) extends Metric with Product with Serializable

   Metrics produced by CollectErccMetrics describing various per-transcript metrics related to the spike-in of ERCC (External RNA Controls Consortium) into an RNA-Seq experiment.

   Metrics produced by CollectErccMetrics describing various per-transcript metrics related to the spike-in of ERCC (External RNA Controls Consortium) into an RNA-Seq experiment. One metric per ERCC transcript will be present.

   name

   the name (or ID) of the ERCC transcript.

   concentration

   the expected concentration as input to CollectErccMetrics.

   count

   the observed count of the number of read pairs (or single end reads) .

   normalized_count

   the observed count of the number of read pairs (or single end reads) normalized by the ERCC transcript length.

3.  sealed trait ErccMixture extends EnumEntry
4.  case class ErccSummaryMetrics (total_reads: Long, ercc_reads: Long, fraction_ercc_reads: Double, ercc_templates: Long, total_transcripts: Int, passing_filter_transcripts: Int, pearsons_correlation: Option[Double], spearmans_correlation: Option[Double], intercept: Option[Double], slope: Option[Double], r_squared: Option[Double]) extends Metric with Product with Serializable

   Metrics produced by CollectErccMetrics describing various summary metrics related to the spike-in of ERCC (External RNA Controls Consortium) into an RNA-Seq experiment.

   Metrics produced by CollectErccMetrics describing various summary metrics related to the spike-in of ERCC (External RNA Controls Consortium) into an RNA-Seq experiment.

   The correlation coefficients and linear regression are calculated based on the log2 observed read pair count normalized by ERCC transcript length versus the log2 expected concentration.

   total_reads

   the total number of reads considered.

   ercc_reads

   the total number of reads mapping to an ERCC transcript.

   fraction_ercc_reads

   the fraction of total reads that map to an ERCC transcript.

   ercc_templates

   the total number of read pairs (or single end reads) mapping to an ERCC transcript.

   total_transcripts

   the total number of ERCC transcripts with at least one read observed.

   passing_filter_transcripts

   the total number of ERCC transcripts with at least the user-set minimum # of reads observed.

   pearsons_correlation

   Pearson's correlation coefficient for correlation of concentration and normalized counts.

   spearmans_correlation

   Spearman's correlation coefficient for correlation of concentration and normalized counts.

   intercept

   the intercept of the linear regression.

   slope

   the slope of the linear regression.

   r_squared

   the r-squared of the linear regression.

5.  class EstimateRnaSeqInsertSize extends FgBioTool with LazyLogging

   Annotations

   @ClpAnnotation()

6.  case class InsertSizeMetric (pair_orientation: PairOrientation, read_pairs: Long = 0, mean: Double = 0, standard_deviation: Double = 0, median: Double = 0, min: Long = 0, max: Long = 0, median_absolute_deviation: Double = 0) extends Metric with Product with Serializable

   Metrics produced by EstimateRnaSeqInsertSize to describe the distribution of insert sizes within an RNA-seq experiment.

   Metrics produced by EstimateRnaSeqInsertSize to describe the distribution of insert sizes within an RNA-seq experiment. The insert sizes are computed in "transcript space", accounting for spliced alignments, in order to get a true estimate of the size of the DNA fragment, not just it's span on the genome.

   pair_orientation

   The orientation of the reads within a read-pair relative to each other. Possible values are FR, RF and TANDEM.

   read_pairs

   The number of read pairs observed with the pair_orientation.

   mean

   The mean insert size of the read pairs.

   standard_deviation

   The standard deviation of the insert size of the read pairs.

   median

   The median insert size of the read pairs.

   min

   The minimum observed insert size of the read pairs.

   max

   The maximum observed insert size of the read pairs.

   median_absolute_deviation

   The median absolution deviation of the read pairs.