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Geraldine_VdAuwera
Posts: 2,484Administrator, GSA Official Member admin
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.
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.
All BAM files must satisfy the following requirements:
See the BAM specification for more information.
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...
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.
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.
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).
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.
For technical details, see the SAM specification on the Samtools website.
| Tag | Importance | SAM spec definition | Meaning |
|---|---|---|---|
ID |
Required | Read group identifier. Each @RG line must have a unique ID. The value of ID is used in the RG tags of alignment records. Must be unique among all read groups in header section. Read groupIDs may be modified when merging SAM files in order to handle collisions. |
Ideally, this should be a globally unique identify across all sequencing data in the world, such as the Illumina flowcell + lane name and number. Will be referenced by each read with the RG:Z field, allowing tools to determine the read group information associated with each read, including the sample from which the read came. Also, a read group is effectively treated as a separate run of the NGS instrument in tools like base quality score recalibration -- all reads within a read group are assumed to come from the same instrument run and to therefore share the same error model. |
SM |
Sample. Use pool name where a pool is being sequenced. | Required. As important as ID. |
The name of the sample sequenced in this read group. GATK tools treat all read groups with the same SM value as containing sequencing data for the same sample. Therefore it's critical that the SM field be correctly specified, especially when using multi-sample tools like the Unified Genotyper. |
PL |
Platform/technology used to produce the read. Valid values: ILLUMINA, SOLID, LS454, HELICOS and PACBIO. | Important. Not currently used in the GATK, but was in the past, and may return. The only way to known the sequencing technology used to generate the sequencing data . | It's a good idea to use this field. |
LB |
DNA preparation library identify | Essential for MarkDuplicates | MarkDuplicates uses the LB field to determine which read groups might contain molecular duplicates, in case the same DNA library was sequenced on multiple lanes. |
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).
Use Picard's AddOrReplaceReadGroups tool to add read group information.
Picard contains a tool called ValidateSamFile that can be used for this. BAMs passing STRICT validation stringency work best with the GATK.
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.
Geraldine Van der Auwera, PhD
Comments
In the example of LB and PI (section 9) should the PI not be PI:200, PI:400, PI:200, PI:400 vs 200,200,400,400? LB flags the library, and you have the 2 libraries sequenced twice, once at 200bp inserts, once at 400bp. Surely this example defines it as being sequenced twice at 200 and 400bp respectively?
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0 · Off Topic Disagree Agree Like WTF ·We do not require value for the CN, DS, DT, PG, PI, or PU fields
Mauricio Carneiro, PhD http://www.broadinstitute.org/~carneiro/
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0 · Off Topic Disagree Agree Like WTF ·Hi there,
Does base recalibration look at the RG ID field to determine sequencing lanes, or does it look at the fastq headers for each read? How important is the format of the ID field for GATK (as long as it's unique per bam file)? It it doesn't contain all of the fastq header information (flowcell, lane etc), does that affect the performance of the gatk algorithms?
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0 · Off Topic Disagree Agree Like WTF ·It is important to put as much information as possible in the RG field, because that is indeed what the tool uses to determine covariates for the analysis. The more information there is in the RG, the more accurate the analysis, for base recalibration at least. Other tools are not so reliant on that information, however.
Geraldine Van der Auwera, PhD
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0 · Off Topic Disagree Agree Like WTF ·