Evaluation of chemical weathering of sediments is the key factor for provenance study and characterization of various sedimentological processes involved in weathering. The various Weathering Indices (WIs) models are available to estimate major elemental geochemistry of the sedimentary package including CIW, CPA, CIA, PIA, CIX, ICV, WIP, R, V, STI and MWPI. The present investigation is to improve and correlation of the earlier models with our development of a computer program using R programming environment to establish various statistical measures, correlation of chemical indices of weathering and to plot different compositional variation diagrams and their analyses. The present results reveal that the correlation of Different correlation plots suggest a significant level of relationship and positive correlation coefficients in CIW – PIA, CIA – PIA, CPA – CIX, ICV – MWPI pairs while significant level of relationship and negative correlation coefficients in CIW – ICV, CIA – WIP pairs. Besides, boxplot of WIs indicates a skewed left or negatively-skewed distribution of CIW and CIA while a skewed right or positively-skewed distribution of CPA, CIX and WIP. Different compositional space diagrams (A – C – N, A – CN – K, A-K – C – N, M – F – W, A – CNK – FM, A – N – K) constrain sediments and rock/mineral composites major elemental geochemistry and demonstrate weathering profiles and source rock chemical makeup. R environment provides flexibility to alter the code as per the data and user requirement by altering different arguments in the code and to include further relevant charts & plots. The applicability of the programming tool is demonstrated by its performance in evaluating the chemical weathering of Surma and Barail sandstones, Mizoram Foreland Basin, NE India and sediments of Manasbal Lake, Kashmir, India, having contrasting provenance histories.
RCy3: Network biology using Cytoscape from within R
