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10.1073/pnas.1617317113 http://scihub22266oqcxt.onion/10.1073/pnas.1617317113 C5187682!5187682 !27930330     free     free     free Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\27930330 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Proc+Natl+Acad+Sci+U+S+A 2016 ; 113 (51 ): 14662-14667 Nephropedia Template TP {{tp|p=27930330 |t=2016. Simultaneous dimension reduction and adjustment for confounding variation |pdf=|usr=}}{{27930330 }} gab.com Text Simultaneous dimension reduction and adjustment for confounding variation JO: Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=27930330 #FOAvip Dimension reduction methods are commonly applied to high-throughput biological datasets. However, the results can be hindered by confounding factors, either biological or technical in origin. In this study, we extend principal component analysis (PCA) to propose AC-PCA for simultaneous dimension reduction and adjustment for confounding (AC) variation. We show that AC-PCA can adjust for (i) variations across individual donors present in a human brain exon array dataset and (ii) variations of different species in a model organism ENCODE RNA sequencing dataset. Our approach is able to recover the anatomical structure of neocortical regions and to capture the shared variation among species during embryonic development. For gene selection purposes, we extend AC-PCA with sparsity constraints and propose and implement an efficient algorithm. The methods developed in this paper can also be applied to more general settings. The R package and MATLAB source code are available at https://github.com/linzx06/AC-PCA. Twit Text FOAVip Simultaneous dimension reduction and adjustment for confounding variation ????Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=27930330 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27930330 #FOAvip English Wikipedia <ref>{{Cite pmid|27930330 }}</ref> Simultaneous dimension reduction and adjustment for confounding variation #MMPMID27930330 Lin Z ; Yang C ; Zhu Y ; Duchi J ; Fu Y ; Wang Y ; Jiang B ; Zamanighomi M ; Xu X ; Li M ; Sestan N ; Zhao H ; Wong WH Proc Natl Acad Sci U S A 2016[Dec]; 113 (51 ): 14662-14667 PMID27930330 show ga Dimension reduction methods are commonly applied to high-throughput biological datasets. However, the results can be hindered by confounding factors, either biological or technical in origin. In this study, we extend principal component analysis (PCA) to propose AC-PCA for simultaneous dimension reduction and adjustment for confounding (AC) variation. We show that AC-PCA can adjust for (i) variations across individual donors present in a human brain exon array dataset and (ii) variations of different species in a model organism ENCODE RNA sequencing dataset. Our approach is able to recover the anatomical structure of neocortical regions and to capture the shared variation among species during embryonic development. For gene selection purposes, we extend AC-PCA with sparsity constraints and propose and implement an efficient algorithm. The methods developed in this paper can also be applied to more general settings. The R package and MATLAB source code are available at https://github.com/linzx06/AC-PCA. |*High-Throughput Nucleotide Sequencing [MESH] |*Principal Component Analysis [MESH] |*Sequence Analysis, RNA [MESH] |Algorithms [MESH] |Brain Mapping [MESH] |Brain/*metabolism [MESH] |Computer Simulation [MESH] |Data Interpretation, Statistical [MESH] |Exons [MESH] |Humans [MESH] |Models, Statistical [MESH] |Software [MESH]Simultaneous dimension reduction and adjustment for confounding variat(epmc).pdf DeepDyve Pubget Overpricing