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     <title>Specifications of Common File Formats Used by the ENCODE Consortium</title>
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-    <a href="/ENCODE/index.html"><img alt="UCSC Genome Browser logo" src="/images/gbLogoOnly.png" title="ENCODE Data at NHGRI"></a>
+    <a href="/ENCODE/index.html"><img src="/images/gbLogoOnly.png"
+        alt="ENCODE Data at UCSC" title="ENCODE Data at NHGRI"></a>
       <span class="txt">Specifications of Common File Formats Used by the ENCODE Consortium</span>
     </div>
     
     <div class="wrapper">
       <div class="bar"><h4 class="title">September 2013</h4></div>
       <div class="content">
         <p>
           The ENCODE consortium uses several file formats to store, display, and disseminate data:
           <ul>
             <li><a href="#FASTQ">FASTQ</a></li>
             <li><a href="#BAM">BAM</a></li>
             <li><a href="#bigWig">bigWig</a></li>
             <li><a href="#bigBed">bigBed</a></li>
           </ul>
         <p>
           FASTQ<a href="#reference1"><sup>[1]</sup></a> is a text-based format for storing nucleotide
           sequences (reads) and their quality scores. The Sequence Alignment/Mapping
           (SAM)<a href="#reference2"><sup>[2]</sup></a> format is a text-based format for storing read
           alignments against reference sequences and it is interconvertible with the binary BAM
           format. The bigWig format is an indexed binary format for rapid display of continuous
           and dense data in the UCSC Genome Browser. And the bigBed format is also an indexed
           binary format for rapid display of annotation items such as a linked collection of
           exons or the binding peaks of a transcription factor.
         </p>
         <p>
           These file formats were originally designed to be generic and flexible. As the
           ENCODE consortium is a collaborative effort, the consortium has made several specifications
           on the file formats to facilitate data archival, presentation, and distribution, as
           well as integrative analysis on the data. The consortium considers FASTQ as the basic file
           format for archival purpose and thus the FASTQ format's specifications aim to preserve the raw
           sequence data. In comparison, the other file formats are geared towards data
           visualization and dissemination, thus their specifications aim to facilitate
           user-friendliness.
         </p>
         <a href="../FAQ/FAQformat.html#ENCODE">UCSC Genome Browser ENCODE-specific File Formats</a><br>
         <a href="#references">References</a>
         <p class="date">Updated 4 Dec 2013
         </p>
 
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     <div class="wrapper">
       <div class="bar"><h4 class="title">
           <a name="FASTQ">FASTQ: Original Text-based Reads and Quality Scores for Archival Purpose</a></h4></div>
       <div class="content">
         <h4>FASTQ file content</h4>
         
         <ul>
           <p>
             FASTQ files are submitted as they come off the sequencing instrument to allow
             for maximal decision making of downstream users. The files are accompanied by
             documentation detailing how the sequencing libraries were constructed to inform
             the end-user about how they might want to process the data, the strengths and
             limitations of the various options of data processing, and how these may apply
             according to the user's biological questions of interest. 
           </p>
           <p>
             ENCODE produces replicate data for most experiments to quantify reliability.
             Biological replicates involve different biological samples, e.g., different tissue
             preparations for cell growth and expansion when cell lines are used. Biological replicates are
             contrasted with technical replicates, for which different sequencing libraries are prepared from
             the same sample, or different sequencing lanes for the same library. Reads from different
             replicates are stored in separate files and should include flow cell and lane ID. If
             multiple lanes are used for the same biological or technical replicate, they are stored
             in the same file (after a QC check to eliminate failed lanes), with information on flow cell and
             lane ID included. For experiments that produce paired-end reads, the two reads in each
             pair are stored in two separate files, with the reads in the same order in the two files.
           </p>
           <p>
             The reads in FASTQ files are unfiltered, i.e., barcodes, adapter sequences, and
             spike-ins remain in the files. For Illumina sequencing, the barcodes that are in the
             so-called third read position should not be present in the sequence. Spike-in reads
             are kept. For bisulfite sequencing experiments, the raw FASTQ files are presented,
             wherein most unmethylated cytosines are converted to thymines.
           </p>
           <p>
             Reads are not "clipped" (no bases are removed). For example, in the case of small RNAs that are
             shorter than the read-length, there may be adapters flanking these reads&mdash;these adapter
             sequences remain in the FASTQ file. Some libraries are constructed in a way such that the
             barcode is read out in the sequence (CSHL small RNAs were made this way during phase II of ENCODE)
             and will appear in the FASTQ. Even though these barcodes would need to be trimmed off prior to
             mapping, they are still included in the FASTQ file because different users may choose
             different trimming algorithms.   
           </p>
           <p>
         </ul>
         
         <h4>FASTQ Sequencing quality</h4>
         <ul>
           <p>
             FASTQ uses four lines for each sequence with the fourth line denoting the sequencing
             quality in each position. The consortium reports the Phred quality score from 0 to 93 using ASCII
             33 to 126, i.e., Phred score plus 33. This is used by the newest versions of the
             Illumina pipeline, Sanger and SRA. The Phred score of a
             base<a href="#reference3"><sup>[3]</sup></a><a href="#reference4"><sup>[4]</sup></a> is defined as -l0
             log<sub>10</sub> (<em>e</em>) where <em>e</em> is the estimated probability for a base to be erroneous.
           </p>
           <p>
             <li><a class="thick" href="http://en.wikipedia.org/wiki/FASTQ_format"
                    target="_blank">Introductory information on the FASTQ format</a><br></li>
         </ul>
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     </div><!--end wrapper-->
 
     <div class="wrapper">
       <div class="bar"><h4 class="title"><a name="BAM">BAM: Binary Format of Sequence Alignment/Mapping (SAM)</a></h4></div>
       <div class="content">
         <h4>BAM file content</h4>
         
         <ul>
           <p>
             When sequence reads are mapped to reference sequences, the resulting alignments are
             stored in BAM files (SAMtools are used to convert between SAM and BAM files). Mapping
             algorithms (e.g., Bowtie, BWA, STAR etc.) use many parameters, such as the version of
             a reference genome, the total number of mismatches allowed during mapping, the maximal
             number of times a read is allowed to map to the reference etc. Furthermore, SAMtools
             may change the content while converting a SAM file to a BAM file. For example, the user
             may allow both unique-mapping and multiple-mapping reads during the mapping and then
             decide to retain only unique-mapping reads in the BAM file. Therefore the consortium documents
             the parameters used by the mapping algorithm and SAMtools in the header of the BAM files. 
           </p>
           <p>
             For experiments that generate paired-end reads, the paired reads are stored in the
             same BAM file. The consortium also retains unmapped reads and spike-ins (whenever appropriate).
             Because spike-in reads are "non-chromosomal", they need to be filtered out before downstream
             processing. The quality scores for unmapped reads are stored in the same format as in FASTQ files,
             i.e., Phred+33. Biological replicates are stored in separate BAM files. Multiple lanes
             of the same library are pooled into a single BAM, with read names containing lane
             information so that it is possible to decompose the pooled BAM file into individual
             BAM files by lane.
           </p>
           <p>
             At the present time, the consortium only releases one BAM file for each FASTQ file (or for each
             pair of FASTQ files in the case of paired-end datasets). However in the future the consortium
             may allow multiple BAM files for the same FASTQ file, potentially for different mapping
             algorithms (e.g., Bowtie and STAR for RNA-seq data) or for mapping to different
             reference genomes (e.g., personalized genomes). In that case, the consortium will provide clear
             guidelines for usage. 
           </p>
         </ul>
         
         <h4>BAM mapping parameters</h4>
         
         <ul>
           <p>
             Due to the diverse data types used in ENCODE, the choice of mapping algorithms and
             the parameters used are data type dependent. These parameters include how many
             mismatches are allowed, whether seed matching is used (only the prefix of each read
             is used for mapping while the low-quality suffix is discarded), whether reads that
             map to many locations in the reference are allowed, etc. The consortium aims to specify the
             settings of these parameters for each individual data type, and these specifications will
             be released in the future versions of this document. Nonetheless, the settings of
             all tunable parameters are specified in the header of each BAM file.
           </p>
           <li><a class="thick" href="http://en.wikipedia.org/wiki/BAM_format"
                  target="_blank">Introductory information on the SAM/BAM format</a><br></li>
         </ul>
       </div><!--end content-->
     </div><!--end wrapper-->
     
     <div class="wrapper">
       <div class="bar"><h4 class="title"><a name="bigWig">bigWig: Genome Browser Signal (Wiggle) Files in Indexed Binary Format</a></h4></div>
       <div class="content">
         
         <h4>bigWig file content</h4>
         <ul>
           <p>
             In order to visualize the number of reads that are mapped to a reference genome
             as a continuous signal in the UCSC genome browser, a user can convert a BAM file
             to a bigWig file (via the intermediate bedGraph format, using computer programs
             provided by the UCSC Genome Browser). 
           <p>
             Stranded data are stored in two bigWig files, one file for the plus genomic strand
             and the other file for the minus strand. The data on the two strands are displayed
             as two separate UCSC tracks by default and can also be displayed in different
             colors as a single overlayed track (without changing the two bigWig files).  For
             unstranded data, signals on the plus and minus strands are summed and only one
             bigWig file is needed. 
           </p>
           <p>
             Data from biological replicates are stored in individual bigWig files and can
             be viewed as separate UCSC tracks; however, this may cease to be necessary after
             the user has concluded that the replicates are highly reproducible. Thus the consortium also
             provides one bigWig file for each experiment with the reads in all biological
             replicates pooled and use this file to define the default track for the experiment.
           </p>
         </ul>
         
         <h4>Generation of bigWig files</h4>
         <ul>
           <p>
             To facilitate the comparison across datasets, ENCODE bigWig files are automatically
             generated by ENCODE uniform processing pipelines which contain appropriate parameters
             for data normalization and filtering. The version and key parameters of the pipeline
             that have been used to generate a bigWig file are provided.
           </p>
           <p>
             <li><a class="thick" href="../goldenPath/help/bigWig.html"
                    target="_blank">Introductory information on the bigWig format</a><br></li>
       </div><!--end content-->
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     <div class="wrapper">
       <div class="bar"><h4 class="title"><a name="bigBed">bigBed: Genome Browser Bed Files in Indexed Binary Format</a></h4></div>
       <div class="content">
         
         <h4>bigBed file content</h4>
         <ul>
           <p>
             Analyses of ENCODE data produce annotation files, e.g., genomic regions that are
             enriched in ChIP-seq signal of transcription factors (ChIP-seq peaks), splice
             junctions detected using RNA-seq data, or differentially methylated regions detected
             using bisulfite sequencing data. Such annotation files can be visualized in the UCSC
             genome browser using the bigBed format. Related to and interconvertible with the
             text-based Bed format, bigBed is an indexed binary format designed for rapid
             visualization. For each element in an ENCODE bigBed file, the consortium specifies its chromosome,
             start, end, genomic strand when applicable, and a color score that denotes average
             signal enrichment for the region.
           </p>
           <p>
             <li><a class="thick" href="../goldenPath/help/bigBed.html"
                    target="_blank">Introductory information on the bigBed format</a><br></li>
         </ul>
       </div><!--end content-->
     </div><!--end wrapper-->
     
     <div class="wrapper">
       <div class="bar"><h4 class="title"><a name="references">References for Common File Formats Used by the ENCODE Consortium</a></h4></div>
       <div class="content">
         
         <h4>References</h4>
         <ul>
           
           <p><a name="reference1">[1]</a>
             Cock PJ, Fields CJ, Goto N, Heuer ML, Rice PM.
             <a href="http://nar.oxfordjournals.org/cgi/pmidlookup?view=long&amp;pmid=20015970" target="_blank">
               The Sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ
               variants</a>.
             <em>Nucleic Acids Res</em>. 2010 Apr;38(6):1767-71.
             PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/20015970" target="_blank">20015970</a>; PMC:
             <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2847217" target="_blank">PMC2847217</a>
           </p>
           
           <p><a name="reference2">[2]</a>
             Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, 1000 Genome
             Project Data Processing Subgroup.
             <a href="https://www.ncbi.nlm.nih.gov/pubmed/19505943" target="_blank">
               The Sequence Alignment/Map format and SAMtools</a>.
             <em>Bioinformatics</em>. 2009 Aug 15;25(16):2078-9.
             PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/19505943" target="_blank">19505943</a>; PMC:
             <a  href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2723002" target="_blank">PMC2723002</a>
           </p>
 
           <p><a name="reference3">[3]</a>
             Ewing B, Hillier L, Wendl MC, Green P.
             <a href="http://genome.cshlp.org/cgi/pmidlookup?view=long&amp;pmid=9521921" target="_blank">
               Base-calling of automated sequencer traces using phred. I. Accuracy assessment</a>.
             <em>Genome Res</em>. 1998 Mar;8(3):175-85.
             PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/9521921" target="_blank">9521921</a>
           </p>
           
           <p><a name="reference4">[4]</a>
             Ewing B, Green P.
             <a href="http://genome.cshlp.org/cgi/pmidlookup?view=long&amp;pmid=9521922" target="_blank">
               Base-calling of automated sequencer traces using phred. II. Error probabilities</a>.
             <em>Genome Res</em>. 1998 Mar;8(3):186-94.
             PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/9521922" target="_blank">9521922</a>
           </p>
           
         </ul>
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