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GATK 2.7 was released on August 21, 2013. Highlights are listed below. Read the detailed version history overview here: http://www.broadinstitute.org/gatk/guide/version-history
Changed the underlying convention of having unstranded reduced reads; instead there are now at least 2 compressed reads at every position, one for each strand (forward and reverse). This allows us to maintain strand information that is useful for downstream filtering.
Fixed bug where representative depths were arbitrarily being capped at 127 (instead of the expected 255).
Added --onlyEmitSamples argument that, when provided, instructs that caller to emit only the selected samples into the VCF (even though the calling is performed over all samples present in the provided bam files).
FPGA support was added to the underlying HMM that is automatically used when the appropriate hardware is available on the machine.
Added a still somewhat experimental PCR indel error model to the Haplotype Caller. By default this modeling is turned on and is very useful for removing false positive indel calls associated with PCR slippage around short tandem repeats (esp. homopolymers). Users have the option (with the --pcr_indel_model argument) of turning it off or making it even more aggressive (at the expense of losing some true positives too).
Added the ability to emit accurate likelihoods for non-variant positions (i.e. what we call a "reference model" that incorporates indels as well as SNP confidences at every position). The output format can be either a record for every position or use the gVCF style recording of blocks. See the --emitRefConfidence argument for more details; note that this replaces the use of "--output_mode EMIT_ALL_SITES" in the HaplotypeCaller.
General improvements to the Gaussian modeling, mostly centered around separating the parameters for the positive and negative training models.
The percentBadVariants argument has been replaced with the numBad argument.
General performance improvements to the VCF reading code contributed by Michael McCowan.
Error messages are much less verbose and "scary."
Eric Banks, PhD -- Director, Data Sciences and Data Engineering, Broad Institute of Harvard and MIT