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ÇѱÛÁ¦¸ñ(Korean Title) |
¸Ê¸®µà½º ±â¹ÝÀÇ ¾Ï ƯÀÌÀû ´ÜÀ§ ¹Ýº¹ º¯ÀÌ ¿µ¿ª ÃßÃâ |
¿µ¹®Á¦¸ñ(English Title) |
Detection of Cancer-specific Copy Number Variation Regions with MapReduce |
ÀúÀÚ(Author) |
½ÅÀç¹®
È«»ó±Õ
°øÁøÈ
ÀÌÀºÁÖ. À±ÁöÈñ
Jae-Moon Shin
Sang-Kyoon Hong
Jin-Hwa Kong
Un-Joo Lee
Jee-Hee Yoon
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¿ø¹®¼ö·Ïó(Citation) |
VOL 40 NO. 05 PP. 0305 ~ 0318 (2013. 10) |
Çѱ۳»¿ë (Korean Abstract) |
¸ðµç ¾Ï ¼¼Æ÷´Â ü¼¼Æ÷ º¯À̸¦ µ¿¹ÝÇÑ´Ù. ¾Ï À¯Àüü º¯ÀÌ ºÐ¼®¿¡ ÀÇÇÏ¿© ¾ÏÀ» ¹ß»ý½ÃÅ°´Â À¯ÀüÀÚ ¹× Áø´Ü/Ä¡·á¹ýÀ» ã¾Æ³¾ ¼ö ÀÖ´Ù. º» ¿¬±¸¿¡¼´Â Â÷¼¼´ë ½ÃÄö½Ì µ¥ÀÌÅ͸¦ ÀÌ¿ëÇÏ¿© ¾Ï ƯÀÌÀû ´ÜÀ§ ¹Ýº¹ º¯ÀÌ(copy number variation, CNV) ¿µ¿ªÀ» ã¾Æ³»´Â »õ·Î¿î µ¥ÀÌÅÍ ¸¶ÀÌ´× ¾Ë°í¸®ÁòÀ» Á¦¾ÈÇÑ´Ù. Á¦¾ÈÇÏ´Â ¹æ½Ä¿¡¼´Â ¾Ï ȯÀÚÀÇ ¾Ï À¯Àüü¿Í µ¿ÀÏÀÎÀÇ Á¤»ó À¯Àüü¿¡ Á¸ÀçÇÏ´Â CNV Èĺ¸ ¿µ¿ªÀ» °¢°¢ ÃßÃâÇÑ ÈÄ, ÀÌ µé °á°ú¸¦ »óÈ£ ºñ±³ ºÐ¼®ÇÏ¿© ¾Ï ƯÀÌÀû CNV ¿µ¿ª¸¸À» ¼±º°Çس½´Ù. º» ¿¬±¸¿¡¼ °³¹ßÇÑ º´·Ä ¾Ë°í¸®ÁòÀº ¾Ï°ú Á¤»ó À¯Àüü µ¥ÀÌÅ͸¦ µ¿½Ã¿¡ ºÐ¼®ÇÏ¿© ¾Ï ƯÀÌÀû CNV ¿µ¿ªÀ» ÃßÃâ/º¸°íÇϸç, ÇϵÓ(Hadoop) ȯ°æÀÇ ¸Ê¸®µà½º(Map/Reduce) ÇÔ¼ö¿¡ ÀÇÇÏ¿© ÀÌµé µ¥ÀÌÅ͸¦ ºÐ»ê, º´Çà ó¸®ÇÑ´Ù. ¼º´É Æò°¡¸¦ À§ÇÏ¿© ¾Ç¼º Èæ»öÁ¾°ú À¯¹æ¾Ï ȯÀÚÀÇ ¾Ï/Á¤»ó À¯Àüü µ¥ÀÌÅ͸¦ ÀÌ¿ëÇÑ ½ÇÇèÀ» ¼öÇàÇÏ¿´À¸¸ç, ±× °á°ú¸¦ ÅëÇØ Á¦¾ÈµÈ ¹æ½ÄÀÌ ´ë±Ô¸ðÀÇ À¯Àüü µ¥ÀÌÅͷκÎÅÍ ¾Ï ƯÀÌÀû CNV ¿µ¿ªÀÇ Å¸ÀÔ ¹× À§Ä¡¸¦ È¿À²ÀûÀ¸·Î ÃßÃâÇÏ°í ÀÖÀ½À» º¸ÀδÙ. |
¿µ¹®³»¿ë (English Abstract) |
The genomes of all cancer cells carry somatic mutations. Therefore, analyses of cancer genomes provide insight for understanding cancer-causing genes, diagnosis and therapy. In this work, we propose a data mining algorithm to detect cancer-specific copy number variation (CNV) regions by using next generation sequencing (NGS) data. The proposed method detects the candidate CNV regions from a cancer genome and the matched normal genome from the same individual, respectively, and identifies the cancer-specific CNVs by comparing the candidate CNV regions of a cancer genome with those of the matched normal genome. In this study, we also propose a novel parallel algorithm which simultaneously analyzes data from the cancer and patient-matched normal samples to identify cancer-specific CNV regions. This method is able to simultaneously perform tasks with large numbers of computing nodes using map and reduce functions in Hadoop project. The preliminary results conducted with the malignant melanoma and breast cancer data showed the prominent efficiency in identifying the types (gains or losses) and the exact locations of the cancer-specific CNVs. |
Å°¿öµå(Keyword) |
¾Ï À¯Àüü
´ÜÀ§ ¹Ýº¹ º¯ÀÌ
Â÷¼¼´ë ½ÃÄö½Ì ±â¼ú
À¯ÀüÀû ±¸Á¶ º¯ÀÌ
¸Ê¸®µà½º
cancer genome
copy number variation
next-generation sequencing technology
genetic structural variation
map/reduce
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