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Added support for coverage calculation from alignment files
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akmorrow13 committed Aug 18, 2016
1 parent e7e1adf commit f15afe5
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Showing 15 changed files with 687 additions and 60 deletions.
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Expand Up @@ -51,7 +51,8 @@ object ADAMMain {
Features2ADAM,
WigFix2Bed,
Fragments2Reads,
Reads2Fragments
Reads2Fragments,
Reads2Coverage
)
),
CommandGroup(
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@@ -0,0 +1,85 @@
/**
* Licensed to Big Data Genomics (BDG) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The BDG licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.bdgenomics.adam.cli

import org.apache.spark.SparkContext
import org.bdgenomics.adam.projections.AlignmentRecordField._
import org.bdgenomics.adam.projections.Projection
import org.bdgenomics.adam.rdd.ADAMContext._
import org.bdgenomics.adam.rdd.features.CoverageRDD
import org.bdgenomics.adam.rdd.read.{ AlignedReadRDD, AlignmentRecordRDD }
import org.bdgenomics.utils.cli._
import org.kohsuke.args4j.{ Argument, Option => Args4jOption }

/**
* Reads2Coverage (accessible as the command 'reads2coverage' through the CLI) takes two arguments,
* an INPUT and OUTPUT, and calculates the number of reads from INPUT at every location in
* the file. Optional arguments are only_negative_strands, only_positive_strands and collapse.
* only_negative_strands and only_positive_strands save coverage computed from only negative and positive strands,
* respectively. Collapse specifies whether saved coverage should merge neighboring coverage with the same counts
* to one record.
*/
object Reads2Coverage extends BDGCommandCompanion {
val commandName: String = "reads2coverage"
val commandDescription: String = "Calculate the coverage from a given ADAM file"

def apply(cmdLine: Array[String]): BDGCommand = {
new Reads2Coverage(Args4j[Reads2CoverageArgs](cmdLine))
}
}

class Reads2CoverageArgs extends Args4jBase with ParquetArgs {
@Argument(required = true, metaVar = "INPUT", usage = "The reads file to use to calculate depths", index = 0)
var inputPath: String = null
@Argument(required = true, metaVar = "OUTPUT", usage = "Location to write the coverage data in ADAM/Parquet format", index = 1)
var outputPath: String = null
@Args4jOption(required = false, name = "-collapse", usage = "Collapses neighboring coverage records " +
"of equal counts into the same record")
var collapse: Boolean = true
@Args4jOption(required = false, name = "-only_negative_strands", usage = "Compute coverage for negative strands")
var onlyNegativeStrands: Boolean = false
@Args4jOption(required = false, name = "-only_positive_strands", usage = "Compute coverage for positive strands")
var onlyPositiveStrands: Boolean = false
}

class Reads2Coverage(protected val args: Reads2CoverageArgs) extends BDGSparkCommand[Reads2CoverageArgs] {
val companion: BDGCommandCompanion = Reads2Coverage

def run(sc: SparkContext): Unit = {

val proj = Projection(contigName, start, end, cigar)

// If saving strand specific coverage, require that only one direction is specified
require(!(args.onlyNegativeStrands && args.onlyPositiveStrands),
"Cannot compute coverage for both negative and positive strands separately")

// load reads
val readsRdd: AlignmentRecordRDD = sc.loadAlignments(args.inputPath, projection = Some(proj))

val finalReads = if (args.onlyNegativeStrands && !args.onlyPositiveStrands) {
readsRdd.transform(rdd => rdd.filter(_.getReadNegativeStrand))
} else if (!args.onlyNegativeStrands && args.onlyPositiveStrands) {
readsRdd.transform(rdd => rdd.filter(!_.getReadNegativeStrand))
} else {
readsRdd
}

finalReads.toCoverage(args.collapse)
.save(args.outputPath)
}
}
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/**
* Licensed to Big Data Genomics (BDG) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The BDG licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.bdgenomics.adam.cli

import org.bdgenomics.adam.rdd.ADAMContext._
import org.bdgenomics.adam.util.ADAMFunSuite
import org.bdgenomics.utils.cli.Args4j

class Reads2CoverageSuite extends ADAMFunSuite {

sparkTest("correctly calculates coverage from small sam file") {
val inputPath = copyResource("artificial.sam")
val outputPath = tmpFile("coverage.adam")

val args: Array[String] = Array(inputPath, outputPath)
new Reads2Coverage(Args4j[Reads2CoverageArgs](args)).run(sc)
val coverage = sc.loadCoverage(outputPath)

val pointCoverage = coverage.flatten.rdd.filter(_.start == 30).first
assert(pointCoverage.count == 5)
}
}
85 changes: 85 additions & 0 deletions adam-core/src/main/scala/org/bdgenomics/adam/models/Coverage.scala
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@@ -0,0 +1,85 @@
/**
* Licensed to Big Data Genomics (BDG) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The BDG licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.bdgenomics.adam.models

import org.apache.spark.rdd.RDD
import org.bdgenomics.formats.avro.Feature

/**
* Converts from avro Feature to Coverage.
*/
object Coverage {

/**
* Creates Coverage from ReferenceRegion and coverage count in that ReferenceRegion.
*
* @param region ReferenceRegion in which Coverage spans
* @param count Coverage count for each base pair in region
* @return Coverage spanning the specified ReferenceRegion
*/
private[adam] def apply(region: ReferenceRegion, count: Double): Coverage = {
Coverage(region.referenceName, region.start, region.end, count)
}

/**
* Creates Coverage from Feature, extracting region information and feature score for coverage.
*
* @param feature Feature to create coverage from
* @return Coverage spanning the specified feature
*/
private[adam] def apply(feature: Feature): Coverage = {
Coverage(feature.getContigName, feature.getStart, feature.getEnd, feature.getScore)
}

/**
* Creates an RDD of Coverage from RDD of Features.
*
* @param rdd RDD of Features to extract Coverage from
* @return RDD of Coverage spanning all features in rdd
*/
private[adam] def apply(rdd: RDD[Feature]): RDD[Coverage] = {
rdd.map(f => Coverage(f))
}
}

/**
* Coverage record for CoverageRDD.
* Contains Region indexed by contig name, start and end, as well as count of coverage at
* each base pair in that region.
*
* @param contigName Specifies chromosomal location of coverage
* @param start Specifies start position of coverage
* @param end Specifies end position of coverage
* @param count Specifies count of coverage at location
*/
case class Coverage(contigName: String, start: Long, end: Long, count: Double) {

/**
* Converts Coverage to Feature, setting Coverage count in the score attribute.
*
* @return Feature built from Coverage
*/
def toFeature: Feature = {
val fb = Feature.newBuilder()
fb.setContigName(contigName)
fb.setStart(start)
fb.setEnd(end)
fb.setScore(count)
fb.build()
}
}
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Expand Up @@ -150,9 +150,25 @@ object ReferenceRegion {
}
}

/**
* Extracts ReferenceRegion from Feature
*
* @param feature Feature to extract ReferenceRegion from
* @return Extracted ReferenceRegion
*/
def apply(feature: Feature): ReferenceRegion = {
new ReferenceRegion(feature.getContigName, feature.getStart, feature.getEnd)
}

/**
* Extracts ReferenceRegion from Coverage
*
* @param coverage Coverage to extract ReferenceRegion from
* @return Extracted ReferenceRegion
*/
def apply(coverage: Coverage): ReferenceRegion = {
new ReferenceRegion(coverage.contigName, coverage.start, coverage.end)
}
}

/**
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38 changes: 25 additions & 13 deletions adam-core/src/main/scala/org/bdgenomics/adam/rdd/ADAMContext.scala
Original file line number Diff line number Diff line change
Expand Up @@ -17,12 +17,12 @@
*/
package org.bdgenomics.adam.rdd

import collection.JavaConverters._
import java.io.{ File, FileNotFoundException, InputStream }
import java.util.regex.Pattern

import com.google.common.collect.ImmutableList
import htsjdk.samtools.{ SAMFileHeader, ValidationStringency }
import htsjdk.samtools.util.{ Interval, Locatable }
import htsjdk.samtools.{ SAMFileHeader, ValidationStringency }
import htsjdk.variant.vcf.VCFHeader
import org.apache.avro.Schema
import org.apache.avro.file.DataFileStream
Expand All @@ -35,33 +35,35 @@ import org.apache.parquet.avro.{ AvroParquetInputFormat, AvroReadSupport }
import org.apache.parquet.filter2.predicate.FilterPredicate
import org.apache.parquet.hadoop.ParquetInputFormat
import org.apache.parquet.hadoop.util.ContextUtil
import org.apache.spark.SparkContext
import org.apache.spark.rdd.MetricsContext._
import org.apache.spark.rdd.RDD
import org.apache.spark.SparkContext
import org.bdgenomics.adam.converters._
import org.bdgenomics.adam.instrumentation.Timers._
import org.bdgenomics.adam.io._
import org.bdgenomics.adam.models._
import org.bdgenomics.adam.projections.{ AlignmentRecordField, NucleotideContigFragmentField, Projection }
import org.bdgenomics.adam.projections.{
AlignmentRecordField,
FeatureField,
NucleotideContigFragmentField,
Projection
}
import org.bdgenomics.adam.rdd.contig.NucleotideContigFragmentRDD
import org.bdgenomics.adam.rdd.features._
import org.bdgenomics.adam.rdd.fragment.FragmentRDD
import org.bdgenomics.adam.rdd.read.{
AlignedReadRDD,
AlignmentRecordRDD,
UnalignedReadRDD
}
import org.bdgenomics.adam.rdd.read.{ AlignedReadRDD, AlignmentRecordRDD, UnalignedReadRDD }
import org.bdgenomics.adam.rdd.variation._
import org.bdgenomics.adam.rich.RichAlignmentRecord
import org.bdgenomics.adam.util.{ TwoBitFile, ReferenceContigMap, ReferenceFile }
import org.bdgenomics.adam.util.{ ReferenceContigMap, ReferenceFile, TwoBitFile }
import org.bdgenomics.formats.avro._
import org.bdgenomics.utils.instrumentation.Metrics
import org.bdgenomics.utils.io.LocalFileByteAccess
import org.bdgenomics.utils.misc.HadoopUtil
import org.bdgenomics.utils.misc.Logging
import org.bdgenomics.utils.misc.{ HadoopUtil, Logging }
import org.seqdoop.hadoop_bam._
import org.seqdoop.hadoop_bam.util._

import scala.collection.JavaConversions._
import scala.collection.JavaConverters._
import scala.collection.Map
import scala.reflect.ClassTag

Expand Down Expand Up @@ -757,6 +759,17 @@ class ADAMContext(@transient val sc: SparkContext) extends Serializable with Log
FragmentRDD.fromRdd(records.map(fastqRecordConverter.convertFragment))
}

/**
* Loads Parquet file of Features to a CoverageRDD.
* Coverage is stored in the score attribute of Feature.
* @param filePath File path to load coverage from
* @return CoverageRDD containing an RDD of Coverage
*/
def loadCoverage(filePath: String): CoverageRDD = {
val proj = Projection(FeatureField.contigName, FeatureField.start, FeatureField.end, FeatureField.score)
loadFeatures(filePath, projection = Some(proj)).toCoverage
}

def loadGff3(filePath: String, minPartitions: Option[Int] = None): FeatureRDD = {
val records = sc.textFile(filePath, minPartitions.getOrElse(sc.defaultParallelism)).flatMap(new GFF3Parser().parse)
if (Metrics.isRecording) records.instrument() else records
Expand Down Expand Up @@ -999,7 +1012,6 @@ class ADAMContext(@transient val sc: SparkContext) extends Serializable with Log
} else if (filePath.endsWith(".fa") ||
filePath.endsWith(".fasta")) {
log.info(s"Loading $filePath as FASTA and converting to AlignmentRecords. Projection is ignored.")
import ADAMContext._
UnalignedReadRDD(loadFasta(filePath, fragmentLength = 10000).toReads,
RecordGroupDictionary.empty)
} else if (filePath.endsWith("contig.adam")) {
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