The TCR repertoire is a mirror of the human immune system that reflects processes caused by infections, cancer, autoimmunity, and aging. Next generation sequencing (NGS) is becoming a powerful tool for deep TCR profiling; yet, questions abound regarding the methodological approaches for sample preparation and correct data interpretation. Accumulated PCR and sequencing errors along with library preparation bottlenecks and uneven PCR efficiencies lead to information loss, biased quantification, and generation of huge artificial TCR diversity. Here, we compare Illumina, 454, and Ion Torrent platforms for individual TCR profiling, evaluate the rate and character of errors, and propose advanced platform-specific algorithms to correct massive sequencing data. These developments are applicable to a wide variety of next generation sequencing applications. We demonstrate that advanced correction allows the removal of the majority of artificial TCR diversity with concomitant rescue of most of the sequencing information. Thus, this correction enhances the accuracy of clonotype identification and quantification as well as overall TCR diversity measurements.