Life Technologies Corporation

Fiona Hyland

Sowmi Utiramerur

Timothy Looney

Heinz Breu

Jeoffrey Schageman

Rajesh Gottimukkala

Asha Kamat

Dumitru Brinza

Susan Maylin Magdaleno

Paul Williams

Simon Cawley

Seth Sadis

Jian Gu

Kelli Bramlett

Zheng Zhang

Rongsu Qi

Varun Bagai

James Veitch

Amir Marcovitz

Alexander Joyner

Scott Myrand

Yongming Sun

Aren Ewing

Charles Scafe

Ruchi Chaudhary

David Merrill

Wing Lee

Birgit Drews

Janice Au-young

Heesun Shin

Susan Magdaleno

The method includes compressing numbers of reads data for targeted genes of a gene expression assay performed on a test sample. The targeted genes are organized into categories. Each category represents a functional context associated with the targeted genes in that category. The numbers of reads corresponding to targeted genes each category is compressed to form a compressed value for the category. The compressed value is compared to a baseline value for the category to determine an enrichment or a loss of a signature corresponding to the functional context of the category. The method may include analyzing information from multiple assays performed on the test sample, assigning a score value to each assay result and predicting a response to immune-oncology treatment based on the assigned scores.

Methods for context based compression of genomic data for immuno-oncology biomarkers

A method for detecting a gene fusion includes amplifying a nucleic acid sample in the presence of primer pool to produce a plurality of amplicons. The primer pool includes primers targeting a plurality of exon-exon junctions of a driver gene. The amplicons correspond to the exon-exon junctions. The amplicons are sequenced and aligned to a reference sequence. The number of reads corresponding to each amplicon is normalized to give a normalized read count. A baseline correction is applied to the normalized read counts for the amplicons to form corrected read counts. A binary segmentation score is calculated for each corrected read count. A predicted breakpoint for the gene fusion is determined based on the amplicon index corresponding to the maximum absolute binary segmentation score. Gene fusion events may be detected in a partner agnostic manner, i.e. without prior knowledge of the specific fusion partner genes or specific breakpoint information.

Methods for partner agnostic gene fusion detection

Systems and method for identifying variants associated with a genetic disease can include obtaining calls for a plurality of individuals for a list of variant positions. The calls can be compared to identify variants that are found in affected individuals and absent in non-affected individuals. Such variants can include loss of heterozygosity, trans-phased compound heterozygotes, increased frequency mitochondrial variants, homozygous recessive variants, de novo variants, sex-linked variants, and combinations thereof.

Systems and methods for identifying sequence variation associated with genetic diseases

Systems and methods for analyzing overlapping sequence information can obtain first and second overlapping sequence information for a polynucleotide, align the first and second sequence information, determine a degree of agreement between the first and second sequence information for a location along the polynucleotide, and determine a base call and a quality value for the location.

Systems and methods for paired end sequencing

Systems and method for identifying somatic mutations can receive first and second sequence information, determine if a variant present in the first sequencing information is also present in the second sequence information, and identify variants present in the first sequence information are somatic mutations when the variant is either not present in the second sequence information or the presence of the variant in the second sequence information is likely due to a sequencing error.

Systems and methods for identifying somatic mutations

A targeted panel with low sample input requirements from a tumor only sample may be processed to estimate mutation load in a tumor sample. The method may include: detecting variants in nucleic acid sequence reads corresponding to targeted locations in the tumor sample genome; annotating detected variants with an annotation information from a population database; filtering the detected variants, wherein the filtering rule set retains the somatic variants and removes germ-line variants; counting the identified somatic variants to give a number of somatic variants; determining a number of bases in covered regions of the targeted locations in the tumor sample genome; and calculating a number of somatic variants per megabase, provides an estimate of the mutation load per megabase in the tumor sample genome.

Methods for detecting mutation load from a tumor sample

Systems and method for validation of sequencing results can amplify a target region of a nucleic acid sample in the presence of a primer pool including target specific and variant specific primers. The variant specific primers can include variant specific barcodes and variant specific sequences. An amplicon can be sequenced to determine the sequence of the variant specific barcode. The variant can be identified based on the sequence of the variant specific barcode, and the location of the variant can be determined by mapping the amplicon to a reference sequence.

Systems and methods for validation of sequencing results

Systems and method for identifying long deletions can obtain sequencing information for a plurality of amplicons in and around a potential region from a nucleic acid sample. The sequencing information can include a plurality of reads that can be mapped to a reference sequence. Using information, such as where reads map to a reference sequence and relative abundance of reads for the amplicons, structural variants can be identified and a determination can be made if the nucleic acid sample is homozygous or heterozygous for the structural variant.

Systems and methods for detecting structural variants

A computer-implemented method for classifying alignments of paired nucleic acid sequence reads is disclosed. A plurality of paired nucleic acid sequence reads is received, wherein each read is comprised of a first tag and a second tag separated by an insert region. Potential alignments for the first and second tags of each read to a reference sequence is determined, wherein the potential alignments satisfies a minimum threshold mismatch constraint. Potential paired alignments of the first and second tags of each read are identified, wherein a distance between the first and second tags of each potential paired alignment is within an estimated insert size range. An alignment score is calculated for each potential paired alignment based on a distance between the first and second tags and a total number of mismatches for each tag.

Systems and methods for sequence data alignment quality assessment

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San Mateo, CA, United States of America

Fiona Hyland