Abstract: A visualization system comprising a persistent memory, storing a dataset, and a non-persistent memory implements a pattern visualizing method. The dataset contains discrete attribute values for each first entity of a first type in a plurality of first entities of the first type and discrete attribute values for each first entity of a second type in a plurality of first entities of the second type for each second entity in a plurality of second entities. The dataset is compressed by blocked compression and represents discrete attribute values in both compressed sparse row and column formats. The discrete attribute values are clustered to assign each second entity to a cluster in a plurality of clusters.

Abstract: Methods for screening clonotypes are provided. Data representing a plurality of cells from a single subject is obtained. The data represents a plurality of clonotypes. The data includes a plurality of contigs for each respective clonotype in the plurality of clonotypes. Each respective contig in the plurality of contigs comprises (i) an indication of chain type for the respective contig and (ii) a contig sequence of an mRNA of the respective cell. There is determined, using the data, for each respective clonotype in the plurality of clonotypes, a number of the plurality of cells that represent the respective clonotype. In some instances, more than one cell in the plurality of cells have the same clonotype in the plurality of clonotypes. In some instances, the plurality of clonotypes comprises 25 clonotypes and where the plurality of cells includes at least one cell for each clonotype in the plurality of clonotypes.

Abstract: A dataset is obtained comprising data blocks, each representing a different characteristic, for a plurality of cells across a plurality of bins, each bin representing a different portion of a reference sequence. Cells are clustered on one such characteristic across the bins thereby forming a tree that includes root, intermediate, and terminal nodes, where the cells are terminal nodes and intermediate nodes have daughter nodes, themselves being intermediate nodes or a cell. A subset of the tree is displayed that includes the root and leaves, each leaf representing an intermediate node or a cell. A heat map of the characteristic is also displayed, the map including a segment for each leaf, across the bins. When a segment represents an intermediate node, it is an average of the characteristic across daughters of the node. Graphs of characteristics for the root across the bins are also displayed.

Abstract: Sharing data is disclosed. In some cases, sharing data includes receiving a request to share data from a first account to a second account, receiving an indication of a plurality of first account profiles associated with the first account to share with the second account, and establishing sharing from the plurality of first account profiles to the second account, wherein sharing comprises the second account having read access to a subset of nonpublic data associated with the plurality of first account profiles.

Abstract: Sharing data is disclosed. In some cases, sharing data includes receiving a request to share data from a first account to a second account, receiving an indication of a plurality of first account profiles associated with the first account to share with the second account, and establishing sharing from the plurality of first account profiles to the second account, wherein sharing comprises the second account having read access to a subset of nonpublic data associated with the plurality of first account profiles.

Abstract: A dataset is obtained comprising data blocks, each representing a different characteristic, for a plurality of cells across a plurality of bins, each bin representing a different portion of a reference sequence. Cells are clustered on one such characteristic across the bins thereby forming a tree that includes root, intermediate, and terminal nodes, where the cells are terminal nodes and intermediate nodes have daughter nodes, themselves being intermediate nodes or a cell. A subset of the tree is displayed that includes the root and leaves, each leaf representing an intermediate node or a cell. A heat map of the characteristic is also displayed, the map including a segment for each leaf, across the bins. When a segment represents an intermediate node, it is an average of the characteristic across daughters of the node. Graphs of characteristics for the root across the bins are also displayed.

Abstract: Sharing data is disclosed. In some cases, sharing data includes receiving a request to share data from a first account to a second account, receiving an indication of a plurality of first account profiles associated with the first account to share with the second account, and establishing sharing from the plurality of first account profiles to the second account, wherein sharing comprises the second account having read access to a subset of nonpublic data associated with the plurality of first account profiles.

Abstract: Sharing data is disclosed. In some cases, sharing data includes receiving a request to share data from a first account to a second account, receiving an indication of a plurality of first account profiles associated with the first account to share with the second account, and establishing sharing from the plurality of first account profiles to the second account, wherein sharing comprises the second account having read access to a subset of nonpublic data associated with the plurality of first account profiles.

Abstract: Sharing data is disclosed. In some cases, sharing data includes receiving a request to share data from a first account to a second account, receiving an indication of a plurality of first account profiles associated with the first account to share with the second account, and establishing sharing from the plurality of first account profiles to the second account, wherein sharing comprises the second account having read access to a subset of nonpublic data associated with the plurality of first account profiles.

Abstract: Sharing data is disclosed. In some cases, sharing data includes receiving a request to share data from a first account to a second account, receiving an indication of a plurality of first account profiles associated with the first account to share with the second account, and establishing sharing from the plurality of first account profiles to the second account, wherein sharing comprises the second account having read access to a subset of nonpublic data associated with the plurality of first account profiles.

Abstract: Sharing data is disclosed. In some cases, sharing data includes receiving a request to share data from a first account to a second account, receiving an indication of a plurality of first account profiles associated with the first account to share with the second account, and establishing sharing from the plurality of first account profiles to the second account, wherein sharing comprises the second account having read access to a subset of nonpublic data associated with the plurality of first account profiles.

Abstract: Sharing data is disclosed. In some cases, sharing data includes receiving a request to share data from a first account to a second account, receiving an indication of a plurality of first account profiles associated with the first account to share with the second account, and establishing sharing from the plurality of first account profiles to the second account, wherein sharing comprises the second account having read access to a subset of nonpublic data associated with the plurality of first account profiles.

Abstract: Sharing data is disclosed. In some cases, sharing data includes receiving a request to share data from a first account to a second account, receiving an indication of a plurality of first account profiles associated with the first account to share with the second account, and establishing sharing from the plurality of first account profiles to the second account, wherein sharing comprises the second account having read access to a subset of nonpublic data associated with the plurality of first account profiles.

Abstract: A dataset is obtained comprising data blocks, each representing a different characteristic, for a plurality of cells across a plurality of bins, each bin representing a different portion of a reference sequence. Cells are clustered on one such characteristic across the bins thereby forming a tree that includes root, intermediate, and terminal nodes, where the cells are terminal nodes and intermediate nodes have daughter nodes, themselves being intermediate nodes or a cell. A subset of the tree is displayed that includes the root and leaves, each leaf representing an intermediate node or a cell. A heat map of the characteristic is also displayed, the map including a segment for each leaf, across the bins. When a segment represents an intermediate node, it is an average of the characteristic across daughters of the node. Graphs of characteristics for the root across the bins are also displayed.

Abstract: Sharing data is disclosed. In some cases, sharing data includes receiving a request to share data from a first account to a second account, receiving an indication of a plurality of first account profiles associated with the first account to share with the second account, and establishing sharing from the plurality of first account profiles to the second account, wherein sharing comprises the second account having read access to a subset of nonpublic data associated with the plurality of first account profiles.

Abstract: A visualization system comprising a persistent memory, storing a dataset, and a non-persistent memory implements a pattern visualizing method. The dataset contains discrete attribute values for each first entity of a first type in a plurality of first entities of the first type and discrete attribute values for each first entity of a second type in a plurality of first entities of the second type for each second entity in a plurality of second entities. The dataset is compressed by blocked compression and represents discrete attribute values in both compressed sparse row and column formats. The discrete attribute values are clustered to assign each second entity to a cluster in a plurality of clusters.

Abstract: Sharing data is disclosed. In some cases, sharing data includes receiving a request to share data from a first account to a second account, receiving an indication of a plurality of first account profiles associated with the first account to share with the second account, and establishing sharing from the plurality of first account profiles to the second account, wherein sharing comprises the second account having read access to a subset of nonpublic data associated with the plurality of first account profiles.

Abstract: Sharing data is disclosed. In some cases, sharing data includes receiving a request to share data from a first account to a second account, receiving an indication of a plurality of first account profiles associated with the first account to share with the second account, and establishing sharing from the plurality of first account profiles to the second account, wherein sharing comprises the second account having read access to a subset of nonpublic data associated with the plurality of first account profiles.

Abstract: A visualization system comprising a persistent memory, storing a dataset, and a non-persistent memory implements a pattern visualizing method. The dataset contains discrete attribute values for each first entity in a plurality of first entities for each second entity in a plurality of second entities. The dataset is compressed by blocked compression and represents discrete attribute values in both compressed sparse row and column formats. The discrete attribute values are clustered to assign each second entity to a cluster in a plurality of clusters. Differences in the discrete attribute values for the first entity across the second entities of a given cluster relative to the discrete attribute value for the same first entity across the other clusters are computed thereby deriving differential values. A heat map of these differential values for each first entity for each cluster is displayed to reveal the pattern in the dataset.

Abstract: Methods for screening clonotypes are provided. Data representing a plurality of cells from a single subject is obtained. The data represents a plurality of clonotypes. The data includes a plurality of contigs for each respective clonotype in the plurality of clonotypes. Each respective contig in the plurality of contigs comprises (i) an indication of chain type for the respective contig and (ii) a contig sequence of an mRNA of the respective cell. There is determined, using the data, for each respective clonotype in the plurality of clonotypes, a number of the plurality of cells that represent the respective clonotype. In some instances, more than one cell in the plurality of cells have the same clonotype in the plurality of clonotypes. In some instances, the plurality of clonotypes comprises 25 clonotypes and where the plurality of cells includes at least one cell for each clonotype in the plurality of clonotypes.