In general, it is anticipated that collaborators will retain first and senior authorship for straightforward discoveries made on their samples (either discovered by the core CMG staff or if made directly by the collaborators). The Center must be named as an author on resulting publications, along with individual CMG analysts who played a major role in the discovery.
The Center will notify all collaborators in cases where the same gene is discovered in samples spanning multiple sites; in such cases, we expect that authorship decisions will be resolved fairly between the parties involved. If a discovery requires an unusually large or innovative effort made by the core CMG staff to solve certain cases, we expect authorship will be awarded according to the actual contributions of all participating investigators.
In addition, the CMG funding must be noted in the acknowledgments of resulting publications. Please include the following statement:
Sequencing and analysis was provided by the Broad Institute of MIT and Harvard Center for Mendelian Genomics (Broad CMG) and was funded by the National Human Genome Research Institute, the National Eye Institute, and the National Heart, Lung and Blood Institute grant UM1 HG008900 to Daniel MacArthur and Heidi Rehm.
Whole Exome Methods Template Text
Whole exome sequencing and data processing were performed by the Genomics Platform at the Broad Institute of Harvard and MIT (Broad Institute, Cambridge, MA, USA). We performed whole exome sequencing on DNA samples (>250 ng of DNA, at >2 ng/ul) using Illumina exome capture (38 Mb target). Our exome-sequencing pipeline included sample plating, library preparation (2-plexing of samples per hybridization), hybrid capture, sequencing (150 bp paired reads), sample identification QC check, and data storage. Our hybrid selection libraries cover >90% of targets at 20x and a mean target coverage of ~100x. The exome sequencing data was de-multiplexed and each sample's sequence data were aggregated into a single Picard BAM file.
Exome sequencing data was processed through a pipeline based on Picard, using base quality score recalibration and local realignment at known indels. We used the BWA aligner for mapping reads to the human genome build 37 (hg19). Single Nucleotide Polymorphism (SNPs) and insertions/deletions (indels) were jointly called across all samples using Genome Analysis Toolkit (GATK) HaplotypeCaller package version 3.4. Default filters were applied to SNP and indel calls using the GATK Variant Quality Score Recalibration (VQSR) approach. Lastly, the variants were annotated using Variant Effect Predictor (VEP). For additional information please refer to Supplementary Section 1 in ExAC paper (Lek et. al.). The variant call set was uploaded on to seqr and analysis was performed using the various inheritance patterns.