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Applying ADAM to process VCF Files from 1000 Genome Project – MyGenomics

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Keywords cloud ADAM INFO file Client Convert VCF format hdfs supergroup rwrr adamsubmit Y88b SLF4J files application container Spark records Parquet d8b
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H1 H2 H3 H4 H5 H6
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About Priyanka Dangi
About Priyanka Dangi – MyGenomics
Clustering of Genotype Information from 1000 Genome Project using k-means||, ADAM and Spark MLLib
Clustering of Genotype Information from 1000 Genome Project using k-means||, ADAM and Spark MLLib – MyGenomics
Cluster Analysis — (Data points | Birds) of (classes | feathers) flock together….
Cluster Analysis — (Data points | Birds) of (classes | feathers) flock together…. – MyGenomics
Comparing VCF Format to its equivalent representation in ADAM/Avro for a Triallelic site
Comparing VCF Format to its equivalent representation in ADAM/Avro for a Triallelic site – MyGenomics
Genomics & ADAM Format — Digging Deeper
Genomics & ADAM Format — Digging Deeper – MyGenomics
Applying ADAM to process VCF Files from 1000 Genome Project
Applying ADAM to process VCF Files from 1000 Genome Project – MyGenomics

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Applying ADAM to process VCF Files from 1000 Genome Project – MyGenomics Skip to content MyGenomics Cloud Scale Genomic Analytics Home Technology Blog ContactWell-nighPriyanka Dangi Applying ADAM to process VCF Files from 1000 Genome Project Posted on May 16, 2016December 10, 2016 pdangiPosted in ADAM ADAM from UC Berkeley, provides a set of formats, APIs and implementations for cloud-scale computing of BAM/SAM and VCF files. ADAM uses Parquet format that provides the required interoperability (between variegated languages C++/Java and variegated components of Big Data, ex. Apache Spark) and increasingly importantly space and query efficiencies. Files spewed out of the Sequencing machines are huge and ADAM helps to reduce the file size and brings efficiency in querying. Native sequencing formats don’t lend themselves well in cloud-scale multi-node environment. I believe ADAM and Apache Spark can slide variant calling. Let’s squint at how we first convert the VCF file into ADAM. -bash-4.2$ ./adam-submit Using ADAM_MAIN=org.bdgenomics.adam.cli.ADAMMain Using SPARK_SUBMIT=/home/spark/spark-1.5.2-bin-hadoop2.6/bin/spark-submit e 888~-_ e e e d8b 888 \ d8b d8b d8b /Y88b 888 | /Y88b d888bdY88b / Y88b 888 | / Y88b / Y88Y Y888b /____Y88b 888 / /____Y88b / YY Y888b / Y88b 888_-~ / Y88b / Y888b Usage: adam-submit [ --] Choose one of the pursuit commands: ADAM ACTIONS depth : Calculate the depth from a given ADAM file, at each variant in a VCF count_kmers : Counts the k-mers/q-mers from a read dataset. count_contig_kmers : Counts the k-mers/q-mers from a read dataset. transform : Convert SAM/BAM to ADAM format and optionally perform read pre-processing transformations adam2fastq : Convert BAM to FASTQ files flatten : Convert a ADAM format file to a version with a flattened schema, suitable for querying with tools like Impala CONVERSION OPERATIONS vcf2adam : Convert a VCF file to the respective ADAM format adam2vcf : Convert an ADAM variant to the VCF ADAM format anno2adam : Convert a voice-over file (in VCF format) to the respective ADAM format fasta2adam : Converts a text FASTA sequence file into an ADAMNucleotideContig Parquet file which represents assembled sequences. adam2fasta : Convert ADAM nucleotide contig fragments to FASTA files features2adam : Convert a file with sequence features into respective ADAM format wigfix2bed : Locally convert a wigFix file to BED format fragments2reads : Convert structuring records into fragment records. reads2fragments : Convert structuring records into fragment records. PRINT print : Print an ADAM formatted file print_genes : Load a GTF file containing gene annotations and print the respective gene models flagstat : Print statistics on reads in an ADAM file (similar to samtools flagstat) listdict : Print the contents of an ADAM sequence wordlist allelecount : Calculate Allele frequencies view : View unrepealable reads from an alignment-record file. -bash-4.1$ ./adam-submit --master yarn --deploy-mode cluster -- vcf2adam /vcf/ALL.chip.omni_broad_sanger_combined.20140818.snps.genotypes.vcf /adam3 Using ADAM_MAIN=org.bdgenomics.adam.cli.ADAMMain Using SPARK_SUBMIT=/opt/cloudera/parcels/CDH-5.5.2-1.cdh5.5.2.p0.4/lib/spark/bin/spark-submit SLF4J:Matriculationpath contains multiple SLF4J bindings. SLF4J: Found tightness in [jar:file:/opt/cloudera/parcels/CDH-5.5.2-1.cdh5.5.2.p0.4/jars/avro-tools-1.7.6-cdh5.5.2.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: Found tightness in [jar:file:/opt/cloudera/parcels/CDH-5.5.2-1.cdh5.5.2.p0.4/jars/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation. 21/05/06 18:05:55 INFO RMProxy: Connecting to ResourceManager at worker1.mygenomics.cloud/169.172.134.176:8032 21/05/06 18:05:55 INFO Client: Requesting a new using from cluster with 4 NodeManagers 21/05/06 18:05:55 INFO Client: Verifying our using has not requested increasingly than the maximum memory sufficiency of the cluster (57344 MB per container) 21/05/06 18:05:55 INFO Client: Will intrust AM container, with 1408 MB memory including 384 MB overhead 21/05/06 18:05:55 INFO Client: Setting up container launch context for our AM 21/05/06 18:05:55 INFO Client: Setting up the launch environment for our AM container 21/05/06 18:05:55 INFO Client: Preparing resources for our AM container 21/05/06 18:05:55 INFO Client: Uploading resource file:/home/products/adam/adam-assembly/target/adam_2.10-0.19.1-SNAPSHOT.jar -> hdfs://worker1.mygenomics.cloud:8020/user/hdfs/.sparkStaging/application_1480703390328_0014/adam_2.10-0.19.1-SNAPSHOT.jar 21/05/06 18:05:56 INFO Client: Uploading resource file:/tmp/spark-a5faeab5-7f48-4ef0-b039-efabfb1b8ca5/__spark_conf__1199542023904572405.zip -> hdfs://worker1.mygenomics.cloud:8020/user/hdfs/.sparkStaging/application_1480703390328_0014/__spark_conf__1199542023904572405.zip 21/05/06 18:05:56 INFO SecurityManager: Changing view acls to: hdfs 21/05/06 18:05:56 INFO SecurityManager: Changing modify acls to: hdfs 21/05/06 18:05:56 INFO SecurityManager: SecurityManager: hallmark disabled; ui acls disabled; users with view permissions: Set(hdfs); users with modify permissions: Set(hdfs) 21/05/06 18:05:56 INFO Client: Submitting using 14 to ResourceManager 21/05/06 18:05:56 INFO YarnClientImpl: Submitted using application_1480703390328_0014 21/05/06 18:05:57 INFO Client:Usingreport for application_1480703390328_0014 (state: ACCEPTED) 21/05/06 18:05:57 INFO Client: vendee token: N/A diagnostics: N/A ApplicationMaster host: N/A ApplicationMaster RPC port: -1 queue: root.hdfs start time: 1481065556633 final status: UNDEFINED tracking URL: http://worker1.mygenomics.cloud:8088/proxy/application_1480703390328_0014/ user: hdfs 21/05/06 18:05:58 INFO Client:Usingreport for application_1480703390328_0014 (state: ACCEPTED) Below Figure 1, shows the state of the using we just submitted on YARN UI launched by ADAM (adam-submit) Figure 1 adam-submit Spark job Spark’s Directed Acylic Graph (To Learn More, Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing) Here is the final output generated from adam-submit command. There are 178 Parquet files generated. Let’s squint at the structure of the Parquet files. We will use parquet-tools for this.Increasinglyabout it in next blog!! -rw-r--r-- 2 hdfs supergroup 6826212 2016-05-21 21:22 /adam3/part-r-00166.gz.parquet -rw-r--r-- 2 hdfs supergroup 7407102 2016-05-21 21:24 /adam3/part-r-00167.gz.parquet -rw-r--r-- 2 hdfs supergroup 6972131 2016-05-21 21:25 /adam3/part-r-00168.gz.parquet -rw-r--r-- 2 hdfs supergroup 6103125 2016-05-21 21:27 /adam3/part-r-00169.gz.parquet -rw-r--r-- 2 hdfs supergroup 7355941 2016-05-21 21:22 /adam3/part-r-00170.gz.parquet -rw-r--r-- 2 hdfs supergroup 2012070 2016-05-21 21:23 /adam3/part-r-00171.gz.parquet -bash-4.1$ hadoop fs -ls /adam3 | wc -l 178 ADAM, Apache Spark, VCF Post navigation Genomics & ADAM Format — Digging Deeper Leave a Reply Cancel reply Your email write will not be published. Required fields are marked *Comment Name * Email * Website Search for: Recent Posts Clustering of Genotype Information from 1000 Genome Project using k-means||, ADAM and Spark MLLib Cluster Analysis — (Data points | Birds) of (classes | feathers) flock together…. Comparing VCF Format to its equivalent representation in ADAM/Avro for a Triallelic site Genomics & ADAM Format — Digging Deeper Applying ADAM to process VCF Files from 1000 Genome Project