Partha P. Majumder

Bio: Partha P. Majumder is an academic researcher from Indian Statistical Institute. The author has contributed to research in topics: Population & Haplotype. The author has an hindex of 52, co-authored 285 publications receiving 11849 citations. Previous affiliations of Partha P. Majumder include Jawaharlal Nehru Centre for Advanced Scientific Research & Kalyani Government Engineering College.

International network of cancer genome projects

Abstract: The International Cancer Genome Consortium (ICGC) was launched to coordinate large-scale cancer genome studies in tumours from 50 different cancer types and/or subtypes that are of clinical and societal importance across the globe. Systematic studies of more than 25,000 cancer genomes at the genomic, epigenomic and transcriptomic levels will reveal the repertoire of oncogenic mutations, uncover traces of the mutagenic influences, define clinically relevant subtypes for prognosis and therapeutic management, and enable the development of new cancer therapies.

The Human Cell Atlas

Abstract: The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.

Mapping human genetic diversity in Asia

Abstract: Asia harbors substantial cultural and linguistic diversity, but the geographic structure of genetic variation across the continent remains enigmatic. Here we report a large-scale survey of autosomal variation from a broad geographic sample of Asian human populations. Our results show that genetic ancestry is strongly correlated with linguistic affiliations as well as geography. Most populations show relatedness within ethnic/linguistic groups, despite prevalent gene flow among populations. More than 90% of East Asian (EA) haplotypes could be found in either Southeast Asian (SEA) or Central-South Asian (CSA) populations and show clinal structure with haplotype diversity decreasing from south to north. Furthermore, 50% of EA haplotypes were found in SEA only and 5% were found in CSA only, indicating that SEA was a major geographic source of EA populations.

Polarity and temporality of high-resolution y-chromosome distributions in India identify both indigenous and exogenous expansions and reveal minor genetic influence of Central Asian pastoralists.

Abstract: Although considerable cultural impact on social hierarchy and language in South Asia is attributable to the arrival of nomadic Central Asian pastoralists, genetic data (mitochondrial and Y chromosomal) have yielded dramatically conflicting inferences on the genetic origins of tribes and castes of South Asia. We sought to resolve this conflict, using high-resolution data on 69 informative Y-chromosome binary markers and 10 microsatellite markers from a large set of geographically, socially, and linguistically representative ethnic groups of South Asia. We found that the influence of Central Asia on the pre-existing gene pool was minor. The ages of accumulated microsatellite variation in the majority of Indian haplogroups exceed 10,000–15,000 years, which attests to the antiquity of regional differentiation. Therefore, our data do not support models that invoke a pronounced recent genetic input from Central Asia to explain the observed genetic variation in South Asia. R1a1 and R2 haplogroups indicate demographic complexity that is inconsistent with a recent single history. Associated microsatellite analyses of the high-frequency R1a1 haplogroup chromosomes indicate independent recent histories of the Indus Valley and the peninsular Indian region. Our data are also more consistent with a peninsular origin of Dravidian speakers than a source with proximity to the Indus and with significant genetic input resulting from demic diffusion associated with agriculture. Our results underscore the importance of marker ascertainment for distinguishing phylogenetic terminal branches from basal nodes when attributing ancestral composition and temporality to either indigenous or exogenous sources. Our reappraisal indicates that pre-Holocene and Holocene-era—not Indo-European—expansions have shaped the distinctive South Asian Y-chromosome landscape.

Ethnic India: A Genomic View, With Special Reference to Peopling and Structure

Abstract: We report a comprehensive statistical analysis of data on 58 DNA markers (mitochondrial [mt], Y-chromosomal, and autosomal) and sequence data of the mtHVS1 from a large number of ethnically diverse populations of India. Our results provide genomic evidence that (1) there is an underlying unity of female lineages in India, indicating that the initial number of female settlers may have been small; (2) the tribal and the caste populations are highly differentiated; (3) the Austro-Asiatic tribals are the earliest settlers in India, providing support to one anthropological hypothesis while refuting some others; (4) a major wave of humans entered India through the northeast; (5) the Tibeto-Burman tribals share considerable genetic commonalities with the Austro-Asiatic tribals, supporting the hypothesis that they may have shared a common habitat in southern China, but the two groups of tribals can be differentiated on the basis of Y-chromosomal haplotypes; (6) the Dravidian tribals were possibly widespread throughout India before the arrival of the Indo-European-speaking nomads, but retreated to southern India to avoid dominance; (7) formation of populations by fission that resulted in founder and drift effects have left their imprints on the genetic structures of contemporary populations; (8) the upper castes show closer genetic affinities with Central Asian populations, although those of southern India are more distant than those of northern India; (9) historical gene flow into India has contributed to a considerable obliteration of genetic histories of contemporary populations so that there is at present no clear congruence of genetic and geographical or sociocultural affinities.

The cBio Cancer Genomics Portal: An Open Platform for Exploring Multidimensional Cancer Genomics Data

Abstract: The cBio Cancer Genomics Portal (http://cbioportal.org) is an open-access resource for interactive exploration of multidimensional cancer genomics data sets, currently providing access to data from more than 5,000 tumor samples from 20 cancer studies. The cBio Cancer Genomics Portal significantly lowers the barriers between complex genomic data and cancer researchers who want rapid, intuitive, and high-quality access to molecular profiles and clinical attributes from large-scale cancer genomics projects and empowers researchers to translate these rich data sets into biologic insights and clinical applications.

Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal

Abstract: The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.

A framework for variation discovery and genotyping using next-generation DNA sequencing data

Abstract: Recent advances in sequencing technology make it possible to comprehensively catalogue genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (1) initial read mapping; (2) local realignment around indels; (3) base quality score recalibration; (4) SNP discovery and genotyping to find all potential variants; and (5) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We discuss the application of these tools, instantiated in the Genome Analysis Toolkit (GATK), to deep whole-genome, whole-exome capture, and multi-sample low-pass (~4×) 1000 Genomes Project datasets.

Signatures of mutational processes in human cancer

Abstract: All cancers are caused by somatic mutations; however, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here we analysed 4,938,362 mutations from 7,042 cancers and extracted more than 20 distinct mutational signatures. Some are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are confined to a single cancer class. Certain signatures are associated with age of the patient at cancer diagnosis, known mutagenic exposures or defects in DNA maintenance, but many are of cryptic origin. In addition to these genome-wide mutational signatures, hypermutation localized to small genomic regions, 'kataegis', is found in many cancer types. The results reveal the diversity of mutational processes underlying the development of cancer, with potential implications for understanding of cancer aetiology, prevention and therapy.