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1. What file formats do you support for sequencer output?

The GATK supports the BAM format for reads, quality scores, alignments, and metadata (e.g. the lane of sequencing, center of origin, sample name, etc.). No other file formats are supported.

2. How do I get my data into BAM format?

The GATK doesn't have any tools for getting data into BAM format, but many other toolkits exist for this purpose. We recommend you look at Picard and Samtools for creating and manipulating BAM files. Also, many aligners are starting to emit BAM files directly. See BWA for one such aligner.

3. What are the formatting requirements for my BAM file(s)?

All BAM files must satisfy the following requirements:

• It must be aligned to one of the references described here.
• It must be sorted in coordinate order (not by queryname and not "unsorted").
• It must list the read groups with sample names in the header.
• Every read must belong to a read group.
• The BAM file must pass Picard validation.

See the BAM specification for more information.

4. What is the canonical ordering of human reference contigs in a BAM file?

It depends on whether you're using the NCBI/GRC build 36/build 37 version of the human genome, or the UCSC hg18/hg19 version of the human genome. While substantially equivalent, the naming conventions are different. The canonical ordering of contigs for these genomes is as follows:

Human genome reference consortium standard ordering and names (b3x): 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, X, Y, MT...

UCSC convention (hg1x): chrM, chr1, chr2, chr3, chr4, chr5, chr6, chr7, chr8, chr9, chr10, chr11, chr12, chr13, chr14, chr15, chr16, chr17, chr18, chr19, chr20, chr21, chr22, chrX, chrY...

5. How can I tell if my BAM file is sorted properly?

The easiest way to do it is to download Samtools and run the following command to examine the header of your file:

$ samtools view -H /path/to/my.bam
@HD     VN:1.0  GO:none SO:coordinate
@SQ     SN:1    LN:247249719
@SQ     SN:2    LN:242951149
@SQ     SN:3    LN:199501827
@SQ     SN:4    LN:191273063
@SQ     SN:5    LN:180857866
@SQ     SN:6    LN:170899992
@SQ     SN:7    LN:158821424
@SQ     SN:8    LN:146274826
@SQ     SN:9    LN:140273252
@SQ     SN:10   LN:135374737
@SQ     SN:11   LN:134452384
@SQ     SN:12   LN:132349534
@SQ     SN:13   LN:114142980
@SQ     SN:14   LN:106368585
@SQ     SN:15   LN:100338915
@SQ     SN:16   LN:88827254
@SQ     SN:17   LN:78774742
@SQ     SN:18   LN:76117153
@SQ     SN:19   LN:63811651
@SQ     SN:20   LN:62435964
@SQ     SN:21   LN:46944323
@SQ     SN:22   LN:49691432
@SQ     SN:X    LN:154913754
@SQ     SN:Y    LN:57772954
@SQ     SN:MT   LN:16571
@SQ     SN:NT_113887    LN:3994
...

If the order of the contigs here matches the contig ordering specified above, and the SO:coordinate flag appears in your header, then your contig and read ordering satisfies the GATK requirements.

6. My BAM file isn't sorted that way. How can I fix it?

Picard offers a tool called SortSam that will sort a BAM file properly. A similar utility exists in Samtools, but we recommend the Picard tool because SortSam will also set a flag in the header that specifies that the file is correctly sorted, and this flag is necessary for the GATK to know it is safe to process the data. Also, you can use the ReorderSam command to make a BAM file SQ order match another reference sequence.

7. How can I tell if my BAM file has read group and sample information?

A quick Unix command using Samtools will do the trick:

$ samtools view -H /path/to/my.bam | grep '^@RG'
@RG ID:0    PL:solid    PU:Solid0044_20080829_1_Pilot1_Ceph_12414_B_lib_1_2Kb_MP_Pilot1_Ceph_12414_B_lib_1_2Kb_MP   LB:Lib1 PI:2750 DT:2008-08-28T20:00:00-0400 SM:NA12414  CN:bcm
@RG ID:1    PL:solid    PU:0083_BCM_20080719_1_Pilot1_Ceph_12414_B_lib_1_2Kb_MP_Pilot1_Ceph_12414_B_lib_1_2Kb_MP    LB:Lib1 PI:2750 DT:2008-07-18T20:00:00-0400 SM:NA12414  CN:bcm
@RG ID:2    PL:LS454    PU:R_2008_10_02_06_06_12_FLX01080312_retry  LB:HL#01_NA11881    PI:0    SM:NA11881  CN:454MSC
@RG ID:3    PL:LS454    PU:R_2008_10_02_06_07_08_rig19_retry    LB:HL#01_NA11881    PI:0    SM:NA11881  CN:454MSC
@RG ID:4    PL:LS454    PU:R_2008_10_02_17_50_32_FLX03080339_retry  LB:HL#01_NA11881    PI:0    SM:NA11881  CN:454MSC
...

The presence of the @RG tags indicate the presence of read groups. Each read group has a SM tag, indicating the sample from which the reads belonging to that read group originate.

In addition to the presence of a read group in the header, each read must belong to one and only one read group. Given the following example reads,

$ samtools view /path/to/my.bam | grep '^@RG'
EAS139_44:2:61:681:18781    35  1   1   0   51M =   9   59  TAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAA B<>;==?=?<==?=?=>>?>><=<?=?8<=?>?<:=?>?<==?=>:;<?:= RG:Z:4  MF:i:18 Aq:i:0  NM:i:0  UQ:i:0  H0:i:85 H1:i:31
EAS139_44:7:84:1300:7601    35  1   1   0   51M =   12  62  TAACCCTAAGCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAA G<>;==?=?&=>?=?<==?>?<>>?=?<==?>?<==?>?1==@>?;<=><; RG:Z:3  MF:i:18 Aq:i:0  NM:i:1  UQ:i:5  H0:i:0  H1:i:85
EAS139_44:8:59:118:13881    35  1   1   0   51M =   2   52  TAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAA @<>;<=?=?==>?>?<==?=><=>?-?;=>?:><==?7?;<>?5?<<=>:; RG:Z:1  MF:i:18 Aq:i:0  NM:i:0  UQ:i:0  H0:i:85 H1:i:31
EAS139_46:3:75:1326:2391    35  1   1   0   51M =   12  62  TAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAA @<>==>?>@???B>A>?>A?A>??A?@>?@A?@;??A>@7>?>>@:>=@;@ RG:Z:0  MF:i:18 Aq:i:0  NM:i:0  UQ:i:0  H0:i:85 H1:i:31
...

membership in a read group is specified by the RG:Z:* tag. For instance, the first read belongs to read group 4 (sample NA11881), while the last read shown here belongs to read group 0 (sample NA12414).

8. My BAM file doesn't have read group and sample information. Do I really need it?

Yes! Many algorithms in the GATK need to know that certain reads were sequenced together on a specific lane, as they attempt to compensate for variability from one sequencing run to the next. Others need to know that the data represents not just one, but many samples. Without the read group and sample information, the GATK has no way of determining this critical information.

9. What's the meaning of the standard read group fields?

For technical details, see the SAM specification on the Samtools website.

We do not require value for the CN, DS, DT, PG, PI, or PU fields.

A concrete example may be instructive. Suppose I have a trio of samples: MOM, DAD, and KID. Each has two DNA libraries prepared, one with 400 bp inserts and another with 200 bp inserts. Each of these libraries is run on two lanes of an Illumina HiSeq, requiring 3 x 2 x 2 = 12 lanes of data. When the data come off the sequencer, I would create 12 bam files, with the following @RG fields in the header:

Dad's data:
@RG     ID:FLOWCELL1.LANE1      PL:ILLUMINA     LB:LIB-DAD-1 SM:DAD      PI:200
@RG     ID:FLOWCELL1.LANE2      PL:ILLUMINA     LB:LIB-DAD-1 SM:DAD      PI:200
@RG     ID:FLOWCELL1.LANE3      PL:ILLUMINA     LB:LIB-DAD-2 SM:DAD      PI:400
@RG     ID:FLOWCELL1.LANE4      PL:ILLUMINA     LB:LIB-DAD-2 SM:DAD      PI:400

Mom's data:
@RG     ID:FLOWCELL1.LANE5      PL:ILLUMINA     LB:LIB-MOM-1 SM:MOM      PI:200
@RG     ID:FLOWCELL1.LANE6      PL:ILLUMINA     LB:LIB-MOM-1 SM:MOM      PI:200
@RG     ID:FLOWCELL1.LANE7      PL:ILLUMINA     LB:LIB-MOM-2 SM:MOM      PI:400
@RG     ID:FLOWCELL1.LANE8      PL:ILLUMINA     LB:LIB-MOM-2 SM:MOM      PI:400

Kid's data:
@RG     ID:FLOWCELL2.LANE1      PL:ILLUMINA     LB:LIB-KID-1 SM:KID      PI:200
@RG     ID:FLOWCELL2.LANE2      PL:ILLUMINA     LB:LIB-KID-1 SM:KID      PI:200
@RG     ID:FLOWCELL2.LANE3      PL:ILLUMINA     LB:LIB-KID-2 SM:KID      PI:400
@RG     ID:FLOWCELL2.LANE4      PL:ILLUMINA     LB:LIB-KID-2 SM:KID      PI:400

Note the hierarchical relationship between read groups (unique for each lane) to libraries (sequenced on two lanes) and samples (across four lanes, two lanes for each library).

9. My BAM file doesn't have read group and sample information. How do I add it?

Use Picard's AddOrReplaceReadGroups tool to add read group information.

10. How do I know if my BAM file is valid?

Picard contains a tool called ValidateSamFile that can be used for this. BAMs passing STRICT validation stringency work best with the GATK.

11. What's the best way to create a subset of my BAM file containing only reads over a small interval?

You can use the GATK to do the following:

GATK -I full.bam -T PrintReads -L chr1:10-20 -o subset.bam

and you'll get a BAM file containing only reads overlapping those points. This operation retains the complete BAM header from the full file (this was the reference aligned to, after all) so that the BAM remains easy to work with. We routinely use these features for testing and high-performance analysis with the GATK.

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ReorderSam

The GATK can be particular about the ordering of a BAM file. If you find yourself in the not uncommon situation of having created or received BAM files sorted in a bad order, you can use the tool ReorderSam to generate a new BAM file where the reads have been reordered to match a well-ordered reference file.

java -jar picard/ReorderSam.jar I= lexicographc.bam O= kayrotypic.bam REFERENCE= Homo_sapiens_assembly18.kayrotypic.fasta

This tool requires you have a correctly sorted version of the reference sequence you used to align your reads. This tool will drop reads that don't have equivalent contigs in the new reference (potentially bad, but maybe not). If contigs have the same name in the bam and the new reference, this tool assumes that the alignment of the read in the new BAM is the same. This is not a lift over tool!

The tool, though once in the GATK, is now part of the Picard package.

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This utility replaces read groups in a BAM file

It is useful for fixing problems such as not having read groups in a bam file.

java -jar picard/AddOrReplaceReadGroups.jar I= testdata/exampleNORG.bam O= exampleNewRG.bam SORT_ORDER=coordinate RGID=foo RGLB=bar RGPL=illumina RGSM=DePristo

Note that this tool is now part of the Picard package: http://picard.sourceforge.net/command-line-overview.shtml#AddOrReplaceReadGroups

This tool can fix BAM files without read group information:

# throws an error
java -jar dist/GenomeAnalysisTK.jar -R testdata/exampleFASTA.fasta -I testdata/exampleNORG.bam -T UnifiedGenotyper 

# fix the read groups
java -jar picard/AddOrReplaceReadGroups.jar I= testdata/exampleNORG.bam O= exampleNewRG.bam SORT_ORDER=coordinate RGID=foo RGLB=bar RGPL=illumina RGSM=DePristo CREATE_INDEX=True

# runs without error
java -jar dist/GenomeAnalysisTK.jar -R testdata/exampleFASTA.fasta -I exampleNewRG.bam -T UnifiedGenotyper

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See this announcement regarding our plans for support of DepthOfCoverage and DiagnoseTargets. If you find that there are functionalities missing in either tool, leave us a comment and we will consider adding them.

For a complete, detailed argument reference, refer to the GATK document page here.

Introduction

DepthOfCoverage is a coverage profiler for a (possibly multi-sample) bam file. It uses a granular histogram that can be user-specified to present useful aggregate coverage data. It reports the following metrics over the entire .bam file:

• Total, mean, median, and quartiles for each partition type: aggregate
• Total, mean, median, and quartiles for each partition type: for each interval
• A series of histograms of the number of bases covered to Y depth for each partition type (granular; e.g. Y can be a range, like 16 to 22)
• A matrix of counts of the number of intervals for which at least Y samples and/or read groups had a median coverage of at least X
• A matrix of counts of the number of bases that were covered to at least X depth, in at least Y groups (e.g. # of loci with ≥15x coverage for ≥12 samples)
• A matrix of proportions of the number of bases that were covered to at least X depth, in at least Y groups (e.g. proportion of loci with ≥18x coverage for ≥15 libraries)

Because the common question "What proportion of my targeted bases are well-powered to discover SNPs?" is answered by the last matrix on the above list, it is strongly recommended that this walker be run on all samples simultaneously.

For humans, DepthOfCoverage can also be configured to output these statistics aggregated over genes, by providing it with a RefSeq ROD.

DepthOfCoverage also outputs, by default, the total coverage at every locus, and the coverage per sample and/or read group. This behavior can optionally be turned off, or switched to base count mode, where base counts will be output at each locus, rather than total depth.

Coverage by Gene

To get a summary of coverage by each gene, you may supply a refseq (or alternative) gene list via the argument

-geneList /path/to/gene/list.txt

The provided gene list must be of the following format:

585     NM_001005484    chr1    +       58953   59871   58953   59871   1       58953,  59871,  0       OR4F5   cmpl    cmpl    0,
587     NM_001005224    chr1    +       357521  358460  357521  358460  1       357521, 358460, 0       OR4F3   cmpl    cmpl    0,
587     NM_001005277    chr1    +       357521  358460  357521  358460  1       357521, 358460, 0       OR4F16  cmpl    cmpl    0,
587     NM_001005221    chr1    +       357521  358460  357521  358460  1       357521, 358460, 0       OR4F29  cmpl    cmpl    0,
589     NM_001005224    chr1    -       610958  611897  610958  611897  1       610958, 611897, 0       OR4F3   cmpl    cmpl    0,
589     NM_001005277    chr1    -       610958  611897  610958  611897  1       610958, 611897, 0       OR4F16  cmpl    cmpl    0,
589     NM_001005221    chr1    -       610958  611897  610958  611897  1       610958, 611897, 0       OR4F29  cmpl    cmpl    0,

If you are on the broad network, the properly-formatted file containing refseq genes and transcripts is located at

/humgen/gsa-hpprojects/GATK/data/refGene.sorted.txt

If you supply the -geneList argument, DepthOfCoverage v3.0 will output an additional summary file that looks as follows:

Gene_Name     Total_Cvg       Avg_Cvg       Sample_1_Total_Cvg    Sample_1_Avg_Cvg    Sample_1_Cvg_Q3       Sample_1_Cvg_Median      Sample_1_Cvg_Q1
SORT1    594710  238.27  594710  238.27  165     245     330
NOTCH2  3011542 357.84  3011542 357.84  222     399     >500
LMNA    563183  186.73  563183  186.73  116     187     262
NOS1AP  513031  203.50  513031  203.50  91      191     290

Note that the gene coverage will be aggregated only over samples (not read groups, libraries, or other types). The -geneList argument also requires specific intervals within genes to be given (say, the particular exons you are interested in, or the entire gene), and it functions by aggregating coverage from the interval level to the gene level, by referencing each interval to the gene in which it falls. Because by-gene aggregation looks for intervals that overlap genes, -geneList is ignored if -omitIntervals is thrown.

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